The financial sector is at the forefront of a significant transformation, driven largely by the buzzword of the decade: artificial intelligence. This somewhat novel tech isn’t just a tool, but a revolution of sorts. CX will be forever changed in the world of retail banking in the coming years by the unstoppable wake of AI. Our take: most industries are already there in large part.
AI’s ability to analyze and interpret vast data sets is redefining how financial institutions interact with their customers, offering more personalized, efficient, and secure services.
We’ll explore the multifaceted role of AI and integrated CX in reshaping the financial customer experience, highlighting how it’s paving the way for a future where banking is not only about transactions, but intelligent, customer-centric experiences.
Hyper-personalization at Scale
AI’s role in personalizing the banking experience is, in a word, profound. By integrating customer signals from a multitude of sources, such as surveys, reviews, social media interactions, and transactional data, we’re now provided with a 360-degree view of the customer.
AI uses these three types of data to further aid banks in personalizing their customer experience:
Descriptive Insights: These insights offer a detailed view into the customer’s financial dealings, including transaction history, spending trends, asset holdings, and the performance of their financial portfolio. This level of detail helps sketch a comprehensive picture of the customer’s financial activities.
Diagnostic Insights: These insights delve into understanding the reasons and mechanisms behind customer behaviors. They provide answers to the ‘why’ and ‘how’ of financial behaviors, giving banks a deeper understanding of their customers’ financial habits and preferences.
Predictive Insights: These are forward-looking insights that help banks predict future financial scenarios for their customers. They can alert customers about potential financial challenges like cash flow issues, unexpected large payments, or even opportunities for advantageous loan settlements. Predictive insights are also key in identifying and preventing potential fraudulent activities by recognizing patterns in customer data.
It won’t replace financial advisors in offering financial advice–at least for now–but it can expedite the process of providing customers personalization at scale; a windfall for institutions with a large clientele.
This level of personalization not only enhances customer satisfaction but can also significantly boost engagement and loyalty. Banks are now moving beyond one-size-fits-all products to create unique, individualized banking experiences for each customer.
Efficiency and Accessibility
The efficiency and accessibility of banking services is changing, too.
AI-powered chatbots and virtual assistants are capable of handling a multitude of customer queries in real-time, from balance inquiries to complex transactional queries. It’s not just about efficiency, but about redefining accessibility. Customers can now access banking services outside traditional banking hours, from the comfort of their homes, and in their preferred language.
Implementing these chatbots and virtual assistants enables banks to offer a continuous, tailored experience to their customers. These conversational AI tools not only facilitate seamless interactions but also efficiently discern when a customer’s query necessitates human intervention, directing them to the right staff member. This approach significantly cuts down on waiting times and enhances customer satisfaction.
A prime instance of this technology in action is Bank of America’s Erica, a digital financial assistant. Erica engages customers in customized, forward-thinking, and insightful dialogues, drawing on data like account balances, previous transactions, spending habits, payment notifications, and instances of double charges. In a similar vein, the UK’s Monzo bank utilizes user behavior analysis to pinpoint specific issues customers face. This strategy enables their customer service team to resolve 85% of daily inquiries independently, reducing their reliance on Monzo’s data team for assistance.
This proactive approach, fueled by an integrated understanding of customer data from various touchpoints, is setting new standards in customer-centric banking.
Security and Advanced Fraud Detection
Security is the fortress of financial institutions; AI is the standing army.
By leveraging machine learning algorithms, AI systems can detect and analyze patterns across a vast array of transactions to identify potential fraud. This capability is enhanced by integrating data from various customer interaction points, providing comprehensive risk assessment.
AI’s real-time processing abilities mean that suspicious activities are detected and addressed quicker than ever before, safeguarding customer assets effectively.
The advent of AI-driven biometric technologies, like facial recognition and fingerprint scanning, has introduced a new era of secure customer authentication, adding a robust layer to the overall security framework in banking.
The encryption will get even more sophisticated in time, constructing an impregnable wall between valuable customers and bad actors’s incessant, attempted breachings.
Challenges and Ethical Considerations
The integration of AI in banking, while transformative, is not without its challenges.
Key among these is the balance between personalization and privacy. Banks must ensure that the use of AI in analyzing customer data from various sources, including social media and personal transactions, adheres to strict data privacy standards.
Three Key Things to Know:
AI is a “Black Box”: Where does the information come from? What datasets and algorithms are being implemented? What happens when the wrong person has control? With progressively more large institutions constructing and implementing their own, internal machine learning algorithms, the information output can be better understood–corrected quickly if necessary.
AI is Everywhere: From pet communication devices, smart toilets, dating coaches–AI is becoming intertwined with every facet of society. With its reach touching virtually everything, what happens when this technological web is used for mal intent? It’s a precarious line we tote, and one that needs hurried, buttressed policy support.
AI is Biased: AI can be biased, or in worst-case-scenarios, give incorrect information entirely. It can be the most problematic for banks when using external systems & software, that, as the aforementioned paragraph suggested, is less understood, and can’t be as easily corrected. As AI is used more frequently by financial advisors, the assurance of accurate and objective information is paramount; especially when this novel tech begins to play a bigger role in helping advisors give financial advice.
Ensuring transparency in AI processes and maintaining an ethical framework is essential in building and retaining customer trust. As AI continues to evolve, banks must remain vigilant and proactive in addressing these challenges to harness AI’s full potential responsibly. We could say the same for any industry.
A Final Word
AI’s role in transforming the financial customer experience is undeniable and growing.
By leveraging AI to integrate and analyze customer data from diverse sources, banks are offering unprecedented levels of personalization, efficiency, and security.
This revolution is not just enhancing the way customers interact with their banks but is also redefining the very essence of customer experience in the financial sector.
As we move forward, the successful integration of AI in banking will hinge on balancing innovation with ethical and responsible use of technology. The future of banking, therefore, lies in creating AI-driven CX that are not only intelligent and personalized but also equitable and secure, fostering a new era of trust and engagement in the financial world.
If you want to build your CX strategy and understand it in a broader context, InMoment’s unified dashboard compiles your customer signals from across the web to give you a holistic view. It structures all of your data, ensuring that every decision you make for your CX strategy keeps the bigger picture in mind.
AI has rapidly evolved from a concept to a crucial tool in retail, allowing retailers to deliver personalized experiences through data-driven insights. However, this transformation also introduces challenges, such as balancing personalization with privacy and ensuring transparency to maintain consumer trust.
Artificial Intelligence (AI) was no more than a vague, abstract concept for the vast majority of people until recently. Today, AI has gone mainstream, infiltrating both our personal and professional lives.
While still in its infancy, AI is transforming the way businesses across all sectors and industries engage with their customers. Retail is one industry that’s experiencing major disruption.
How Retail Companies Can Use AI to Improve Customer Experience
Retailers have no shortage of data, but they often struggle to make sense of disparate sets – much less identify ways to leverage that data to optimize the customer experience. Integrated CX platforms, powered by AI, have the ability to analyze and interpret these vast, disjointed data sets. Retailers that strategically leverage these platforms, and other AI-powered tools, are better equipped to deliver outstanding experiences throughout the customer journey.
Let’s dive into the role of AI and integrated CX in shaping retail customer experiences – and how this winning combination is empowering retailers to deliver intelligent, outstanding experiences that attract, convert, and retain customers.
Ultra-Personalized Experiences for Every Shopper
In the world of retail, generic, one-size-fits all communication and experiences were once the norm. A retailer would air a commercial on TV or run an ad in a magazine – and cross their fingers that it would resonate with at least a portion of viewers.
Today, generic experiences no longer cut it.
Retail consumers expect, and sometimes demand, experiences that are tailored to their unique needs and preferences. What’s more, they expect a brand to keep pace as their needs and preferences evolve over time.
Integrated CX platforms, powered by AI, unify customer signals from a myriad of sources, including historic transactions, different types of surveys, reviews, social media interactions, and more. Collectively, those signals provide a complete, 360-degree view of each customer. Retailers can tap into this holistic view to power ultra-personalized experiences for every customer.
Efficiency Across All Touchpoints
The way consumers interact with retailers (and want to interact with them) is evolving. During the pandemic, this evolution accelerated.
Browsing and buying in a brick-and-mortar store was once the default, but today, is far from reality.
They’re engaging with brands via mobile browsers, apps, messaging channels, and social media—just to mention a few. They expect instant feedback–-whenever and wherever a need arises.
AI-powered chatbots allow retailers to deliver the instant engagement consumers expect. These chatbots and virtual assistants are equipped to handle all sorts of inquiries—whether the shopper is just starting to explore options or has already made a purchase.
If a shopper is early in the purchase journey, an AI-powered chatbot can answer questions and provide personalized recommendations based on previous transaction history (if known) or on the customer’s answers to a few basic questions. Some chatbots also allow customers to quickly make a purchase right in the chat. After a purchase is made, virtual assistants provide order updates and help resolve any issues that may arise.
Conversational AI tools can help retailers deliver seamless, connected interactions. They can accurately determine when a customer’s inquiry requires the assistance of a real human—and can then transfer them to the right person for the task. This cuts down wait-times, which is a top frustration among consumers.
Analyzing Feedback to Optimize Experiences
Customer feedback has always been key to optimizing retail CX. That’s nothing new.
Traditionally, surveys were the primary way for collecting customer feedback. Make no mistake: surveys are still valuable. However, many consumers are facing “survey fatigue”, decreasing their likelihood of engagement. Retailers need to diversify their feedback mechanisms.
Consumers leave plenty of signals (feedback) across these platforms—some direct, some implicit. But many retailers struggle to decode this hodgepodge of both structured and unstructured data.
Integrated customer experience platforms, using AI, empower retailers to amalgamate diverse datasets. All those customer signals are translated into actionable insights that will improve CX and increase customer satisfaction and retention.
AI Presents Retailers With New Challenges
AI is improving the way retailers interact with their customers. By and large, this is a good thing. However, AI does present some unique challenges to retailers.
One key challenge is balancing personalization and privacy. Retail consumers have come to expect personalized experiences, wherever they are on the shopping journey. Of course, such experiences depend on data. Retailers must ensure their customer data – and their use of AI to analyze it – is safe and secure.
When it comes to AI, there are three additional, major concerns:
AI Operates as a “Black Box”: To the average person, the ins and outs of AI are largely a mystery. For example, there’s usually no visibility into:
Which datasets are being used
Where the data comes from
Which algorithms are being implemented
As such, it’s difficult – if not impossible – to discern how a specific recommendation or decision was made.
Bias is Common: In the world of AI, inherent biases are rampant. This can lead to skewed or biased outputs.
There is Risk: In today’s world, AI is everywhere. It’s woven into the fabric of our personal and professional lives. People are leveraging AI for just about everything, from creating a household budget to drafting professional correspondence to finding a spouse. The sheer volume of data being channeled into public spaces introduces risk.
Consumers are loyal to retailers they trust. Retailers must be laser-focused on earning and preserving the trust of their patrons.
Though it’s tempting to go “all in” on AI, retailers, and everyone else for that matter, must do so responsibly. Retailers must recognize the challenges presented by AI – and then work to address them. In addition, retailers must prioritize transparency to foster consumer trust.
A Final Word
Though it’s a relatively new technology accessible to the public, AI is already transforming the retail customer experience.
Retailers have a wealth of data available to them to fuel better experiences. Integrated CX is integral to making sense of data from disconnected sources—and shedding light on opportunities to act on those insights.
Retailers must make it a priority to use AI ethically and responsibility in order to preserve customers’ trust. In today’s competitive marketplace, the most successful retailers will be those that create intelligent, personalized AI-driven CX, that are safe, private, and secure.
See how InMoment is leading this charge with its award-winning, integrated CX platform.
References
Mckinsey & Company. The value of getting personalization right—or wrong—is multiplying (https://www.mckinsey.com/capabilities/growth-marketing-and-sales/our-insights/the-value-of-getting-personalization-right-or-wrong-is-multiplying/). Access 12/20/23.
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In an increasingly data-driven world, it is no longer enough to understand the past. Successful businesses utilize prescriptive analytics to aid in data-driven decisions that will improve their bottom line. Whether it’s reducing your cost to acquire a customer, decreasing your churn rate, or anything in between. Your business can use analytics to drive success and improve customer experiences.
What is Prescriptive Analytics?
Prescriptive analytics is a type of advanced analytics that focuses on providing recommendations and insights to optimize decision-making. Prescriptive analytics uses a combination of mathematical models, algorithms, and business rules to analyze data and generate recommendations. It takes into account various factors, constraints, and objectives to suggest the best course of action in a given situation. This type of analytics is particularly valuable in complex and dynamic environments where decision-makers need guidance on how to respond to different scenarios.
What is the Primary Goal of Prescriptive Analytics?
The primary goal of prescriptive analytics is to provide actionable recommendations that help organizations or individuals make informed decisions to achieve desired outcomes. Unlike descriptive analytics, which focuses on summarizing historical data, and predictive analytics, which forecasts future events, prescriptive analytics takes it a step further by suggesting the best course of action.
With InMoment’s award-winning XI Platform, businesses have access to comprehensive analytics and prescriptive actions represented in customizable dashboards. These tools allow your business to digest analytical insights in the way that makes the most sense for your company.
How Does Prescriptive Analytics Work?
Prescriptive analytics works by using advanced analytical techniques to recommend actions that optimize decision-making. It involves analyzing data, creating mathematical models, and considering various constraints and objectives to suggest the best course of action.
Consider a retail company using prescriptive analytics to optimize its pricing strategy. The process would involve analyzing historical sales data, market trends, and external factors. Predictive analytics forecasts the demand for products under different price points. The optimization models factor in costs, competitor prices, and revenue objectives.
The prescriptive analytics system then recommends specific pricing adjustments for each product to maximize overall revenue while considering factors like customer demand elasticity and market conditions. The recommendations are not only based on historical data and predictions but also on the optimization of pricing strategies to achieve the desired financial outcomes for the company. Decision-makers can follow these recommendations to adjust prices and potentially improve the company’s profitability.
How Does Prescriptive Analytics Differ From Other Types of Analytics?
When it comes to data analytics, organizations leverage various approaches to extract meaningful insights and guide decision-making. Each type of analytics serves a distinct purpose, contributing to a comprehensive understanding of data. There are four key types of analytics: prescriptive, predictive, diagnostic, and descriptive.
Predictive vs Prescriptive Analytics
While predictive analytics is instrumental in understanding likely future scenarios, prescriptive analytics takes it a step further by providing actionable insights that empower organizations to make optimal decisions and drive positive outcomes. Both methodologies, when used in tandem, contribute to a comprehensive and strategic approach to data-driven decision-making. Here are some key differences between the two types of analytics:
Predictive analytics focuses on forecasting future events, while prescriptive analytics recommends actions to influence or achieve desired outcomes.
Predictive analytics is more concerned with “what will happen,” while prescriptive analytics is concerned with “what to do about it.”
Predictive analytics helps organizations prepare for the future, while prescriptive analytics guides decision-makers in shaping the future.
Diagnostic Analytics vs Prescriptive Analytics
Diagnostic analytics and prescriptive analytics are two distinct approaches within the realm of data analytics, each serving different purposes in the decision-making process. Diagnostic analytics is focused on understanding the reasons behind past events or performance. Diagnostic analytics helps organizations understand the factors contributing to past outcomes, prescriptive analytics empowers decision-makers with actionable recommendations to shape future events. Here is a breakdown of some differences between these two types of analytics:
Diagnostic analytics looks backward to understand past events, while prescriptive analytics looks forward to recommending actions for future outcomes.
Diagnostic analytics is retrospective and focused on root cause analysis, while prescriptive analytics is proactive and provides actionable insights for decision-making.
Diagnostic analytics helps uncover the “why” behind events, while prescriptive analytics guides decision-makers on “what to do” to achieve desired results.
As an example, consider an e-commerce platform employing diagnostic analytics to investigate a sudden drop in website traffic, examining factors such as marketing campaigns, website usability, and external events.
Descriptive and Prescriptive Analytics
Descriptive analytics is centered around summarizing historical data to provide a comprehensive understanding of past events and trends. It seeks to answer the question, “What has happened?” by using data aggregation, visualization, and statistical analysis to present a clear and concise overview of historical performance. Prescriptive analytics takes a more proactive stance by answering the question, “What should be done?” Integrating both approaches offers a comprehensive strategy for effective decision-making.
Consider a retail company that uses descriptive analytics to review sales reports from the previous quarter, visualizing key metrics such as total sales, product categories, and customer demographics. By integrating prescriptive analytics into the decision-making process, the retail company can move beyond analyzing past performance to actively shaping and optimizing its strategies for the future.
Advantages of Prescriptive Analytics
Prescriptive analytics offers several compelling advantages that make it a valuable tool for organizations seeking to optimize decision-making. One key benefit is its ability to provide actionable insights. By leveraging optimization models and algorithms, prescriptive analytics goes beyond predicting outcomes and offers specific recommendations on the best course of action. This empowers decision-makers with a clear and informed path forward, leading to more effective and strategic choices.
Another advantage is adaptability. Prescriptive analytics systems often incorporate feedback loops, allowing them to continuously learn and refine their recommendations based on new data and changing conditions. This adaptability enhances the relevance and accuracy of the insights provided, particularly in dynamic and evolving environments.
Additionally, prescriptive analytics enables organizations to consider various factors and constraints simultaneously. This holistic approach ensures that decisions align with multiple objectives, leading to outcomes that are not only optimized for a specific goal but also take into account broader organizational priorities.
Disadvantages of Prescriptive Analytics
Despite its benefits, prescriptive analytics comes with certain challenges and disadvantages. One notable concern is the complexity of implementation. Building and maintaining prescriptive analytics models requires expertise in advanced analytics, mathematics, and algorithmic development. Organizations may face obstacles in terms of the technical skills needed, as well as the resources required for ongoing maintenance.
Another challenge is the reliance on data quality. Prescriptive analytics heavily depends on accurate and relevant data. If the input data is incomplete, inaccurate, or biased, it can compromise the reliability of the recommendations. Ensuring data quality becomes a critical aspect of successful prescriptive analytics implementation.
Privacy and ethical considerations also come into play. Prescriptive analytics often involves processing sensitive information, raising concerns about data privacy and the ethical implications of decision-making based on algorithmic recommendations. Striking the right balance between data-driven insights and ethical considerations becomes essential in the deployment of prescriptive analytics.
While prescriptive analytics offers powerful advantages in guiding optimal decision-making, organizations must navigate the complexities of implementation, address data quality concerns, and carefully consider ethical implications to fully realize its potential benefits.
How Does Prescriptive Analytics Help in Business Decision-Making?
Prescriptive analytics plays a pivotal role in enhancing business decision-making by providing valuable insights and actionable recommendations. One key contribution lies in its ability to optimize choices. By leveraging sophisticated mathematical models and algorithms, prescriptive analytics evaluates multiple decision scenarios, considering various factors, constraints, and objectives. This process goes beyond predicting outcomes; it guides decision-makers on the most effective actions to take, ultimately leading to decisions that align with organizational goals.
Moreover, prescriptive analytics contributes to strategic planning and resource allocation. Organizations face numerous challenges in allocating resources efficiently, whether it’s managing production schedules, optimizing supply chain logistics, or determining marketing budgets. Prescriptive analytics analyzes complex datasets to offer recommendations that maximize efficiency, minimize costs, and improve overall resource utilization. This, in turn, enables businesses to allocate resources in a manner that yields the greatest return on investment.
Prescriptive analytics also facilitates risk management. By considering potential scenarios and their associated risks, decision-makers can make informed choices that mitigate uncertainties. Whether it’s in financial investments, supply chain disruptions, or market fluctuations, prescriptive analytics aids in identifying and addressing risks preemptively. This proactive approach empowers businesses to navigate volatile environments more effectively.
How to Get Started with Prescriptive Analytics
Implementing prescriptive analytics involves a strategic approach to harness its benefits effectively. The first step is to establish a clear understanding of organizational goals and challenges. Identify specific decision areas where prescriptive analytics can make a significant impact, such as resource allocation, supply chain optimization, or pricing strategies.
Once the focus areas are defined, the next step is to gather and prepare the necessary data. Data quality is paramount in prescriptive analytics, so organizations should ensure that they have access to accurate, relevant, and comprehensive data. Integration of data from various sources may be necessary, requiring robust data preprocessing to create a unified dataset suitable for analysis.
Collaboration between data scientists, domain experts, and decision-makers is essential throughout the process. Domain experts provide valuable insights into the contextual nuances of decision-making, while data scientists leverage their analytical expertise to build and refine prescriptive analytics models. A collaborative approach ensures that the models align with organizational objectives and are practical in real-world scenarios.
Pilot projects can be instrumental in validating the effectiveness of prescriptive analytics in a controlled environment. Start with a specific use case, implement the prescriptive analytics model, and assess the outcomes. The insights gained from the pilot project can inform adjustments and improvements before scaling up to broader applications.
Continuous monitoring and optimization are critical components of a successful prescriptive analytics initiative. Regularly review the performance of models, update them with new data, and refine algorithms based on feedback. This iterative approach ensures that the prescriptive analytics system remains adaptive and aligned with evolving business needs.
Utilize Prescriptive Analytics with InMoment
InMoment’s prescriptive analytics capabilities give your business the ability to transform raw data into strategic insights. These insights provide actionable recommendations that empower decision-makers to make informed choices and drive optimal outcomes. With the power of prescriptive analytics at your fingertips, you can not only understand historical performance but also proactively shape future strategies, enhance operational efficiency, and stay ahead of the competition in today’s dynamic business landscape. Schedule a demo to learn more today!
In the dynamic world of hospitality, the ability to manage and enhance the guest experience often spells the difference between those who win and those who get left behind. With today’s travelers raising their expectations while being exposed to a seemingly unlimited number of hospitality solutions, it is critical that operators deliver experiences that reflect the lives of their customers.
What is Guest Experience?
Guest experience refers to the overall impression and satisfaction that a guest has during their interactions with a hospitality brand or establishment, such as hotels, restaurants, resorts, and attractions. It encompasses every aspect of their stay or visit, from the booking process and arrival to the accommodation, services, and departure.
A positive guest experience involves going beyond basic customer service. (More on this later.) In hospitality, factors that contribute to the guest experience include personalized attention, efficient service, cleanliness, ambiance, health, wellness, and safety, and the overall atmosphere of the establishment, among others.
Operators today should strive to exceed guest expectations and create memorable guest experiences to encourage repeat visits and positive word-of-mouth recommendations. By understanding and anticipating the needs and preferences of your guests, you make them feel valued and ensure that every touchpoint in their journey contributes to positive and enjoyable experiences.
The Importance of Guest Experience Management
Guest experience management is vital for hospitality brands looking to build a positive reputation, foster customer loyalty, achieve competitive differentiation, and ultimately drive long-term success and profitability.
Guest experiences impact reputation. Positive experiences build a favorable reputation, while negative experiences can harm it. With the prevalence of online reviews and social media, managing and enhancing guest experiences is crucial to maintaining a positive brand image.
Positive guest experiences lead to higher customer satisfaction levels. A memorable and positive guest experience drives customer satisfaction and fosters customer loyalty. Happy customers are more likely to choose the same hospitality brand for future stays or visits, while also recommending the brand to others, contributing to repeat business and long-term profitability.
Guest experience differentiates your brand. With travel consumers exposed to seemingly limitless hospitality solutions, providing an exceptional guest experience helps differentiate your brand from competitors.
Guest experience management drives data-driven decision-making. It often involves collecting and analyzing integrated CX data, which can be valuable for gathering actionable insights, making informed business decisions, improving service offerings, and tailoring experiences to meet customer expectations.
The Difference Between Guest Experience vs. Customer Service
You may be wondering, “What is the difference between managing the guest experience and delivering customer service?”
Traditionally defined, customer service is the act of taking care of your guests’ needs by providing service and assistance before, during, and after their requirements are met. This is provided, for example, by the receptionist at the front desk checking in hotel guests upon arrival; the tour operator explaining the historical or cultural significance of landmarks in a local area; or the sommelier giving detailed advice about which wines pair best with which dishes.
Many think of customer service as the act of reacting and responding to guests at certain points of contact: a hotel check-in, a tour, or a restaurant visit. It is often transactional in nature and focuses on meeting immediate needs or resolving issues.
The guest experience encompasses all these touchpoints and is part of a larger strategic effort in which customer service plays a crucial part.
A single point of contact doesn’t determine the guest experience. It encompasses the entire customer journey — through processes, policies, and people. It can include the guest’s initial awareness or discovery of your brand and can begin long before they set foot in any of your property locations. This means that all interactions and touchpoints the guest has with your brand are considered.
Guest experience isn’t a department. It’s a core value that should involve everyone in your organization, from the C-suite to the front-facing staff. Every team or department, from marketing and sales to front office, customer support, and after-sales, has a stake in managing the guest experience.
Guest experience management isn’t reactive. You don’t wait for a phone call, an email, or a slew of negative reviews to resolve the guest’s problem or meet their requirements. The premise behind guest experience management is that operators become truly proactive and intuitive, with the goal of seeing through guests’ eyes and better understanding their needs, wants, and expectations.
Key Trends Impacting the Guest Experience in Hospitality
Hospitality is a dynamic industry and new trends continue to emerge, raising expectations in a way that forces operators to rethink boardroom strategies, marketing and sales processes, and business models. Here are some key trends that are currently shaping the guest experience in hospitality.
A Multi-Channel Strategy is Essential
To validate their booking decisions, travel buyers are navigating multiple digital channels to conduct research and find solutions that are suited to their needs. These include online travel agencies (OTAs), social media, mobile apps, and brand websites. Deal-seeking behavior is also on the rise due to the cost of living crisis and record-shattering inflation rates.
A multichannel strategy is therefore essential for hospitality brands looking to reach a broader audience and maximize reach and visibility. Today’s consumers expect seamless and convenient interactions across multiple channels. A multichannel approach allows your organization to meet these expectations and provide guests with the flexibility to engage through their preferred channels.
Each channel should also provide an opportunity for you to collect valuable data about guest behavior, preferences, and booking patterns. By integrating data from multiple channels, you can gain insights into customer trends and make data-driven decisions to improve your marketing and service strategies.
Guests Want More Tailored Experiences
More tailored and personalized experiences, from customized room preferences to targeted offers, are a growing trend in the hospitality sector. Today’s travelers appreciate options and flexibility, choosing providers and operators that go the extra mile to make their stay unique.
Tailored experiences can also create a sense of exclusivity, with things like VIP treatments, exclusive access, and special privileges for repeat guests contributing to a feeling of being valued.
To meet these expectations, a growing number of brands are leveraging customer experience analytics and artificial intelligence (AI) to understand guest preferences and deliver tailored services.
There’s an Increased Demand for Local / Regional Experiences
The rise of the independent traveler means that guests are seeking both extreme personalization and unique, authentic local experiences. Guest experiences that give back to local communities or support the local economy are in demand, as are niche properties, staycations, and holidays and retreats that integrate attractions and activities within the local community where the business operates. More travelers than ever are also drawn to properties that reflect the local character and charm.
This is why hospitality brands are incorporating local elements into their services, from locally inspired decor to partnerships with local businesses for unique guest experiences. Operators are also focusing more on local and hyperlocal sourcing, establishing close partnerships with farmers, artisans, producers, and suppliers.
Guests are Focused on Health, Safety, and Wellness
While health, cleanliness, and hygiene have always ranked among the top factors for travelers when choosing a hotel property, it has risen to the top of the list in the post-pandemic landscape. When making booking decisions, guests are researching sites that specifically offer cleanliness and safety information.
This means that operators should double down on efforts to ensure that guests feel safe, secure, and clean. Beyond simply meeting compliance requirements issued by authorities, your company should work to respond to guest expectations amidst heightened sensitivity around cleanliness and safety.
Wellness is also a significant focus, with hotels offering amenities like fitness facilities, healthy dining options, and wellness programs. Some brands are incorporating spa services, mindfulness activities, and sleep-focused amenities to deliver a better experience for guests.
How to Measure Guest Experience
You cannot manage something you aren’t measuring. Hospitality brands can measure the guest experience using these common approaches:
Guest surveys and feedback forms: Implementing surveys allows guests to provide direct feedback on their experience. To gather both structured and unstructured feedback data, your team can use Likert scales, open-ended questions, and the Net Promoter Score (NPS) survey methodology.
Online reviews and social media listening: Tracking reviews as well as mentions and comments from social media platforms provides a valuable source of unsolicited feedback, which operators can analyze for common themes, areas for improvement, and high-impact issues impacting the guest experience.
Employee feedback: Gathering feedback from employees who directly interact with guests can offer insights into the guest experience and areas that may need improvement.
Operational metrics: Monitoring and managing metrics such as check-in/check-out times, room cleanliness, and service response times should help you identify areas where operational efficiency can enhance the overall guest experience.
Customer experience metrics: Connecting feedback data and operational metrics to customer experience KPIs such as NPS, Customer Satisfaction Score (CSAT), and Customer Effort Score (CES) lets your organization achieve a more complete and accurate view of the guest experience.
Loyalty program engagement: The level of engagement guests have with your loyalty program will also help you look into repeat bookings, member satisfaction, and redemption patterns in order to gauge overall loyalty and guest satisfaction.
By combining insights from these various sources, hospitality brands can get a more comprehensive understanding of the guest experience and make data-driven decisions that enhance customer satisfaction and loyalty.
How to Enhance the Guest Experience: Best Practices
Learning how to enhance the guest experience is essential for attracting and retaining customers. Here are some best practices applied by today’s top hospitality brands.
Improve Guest Communication
Effective communication plays a crucial role in shaping the overall guest experience. It can enhance guest satisfaction, foster loyalty, and contribute to positive reviews; meanwhile, poor communication can lead to misunderstandings, dissatisfaction, and negative feedback. Throughout the customer journey, ensure that you’re sharing relevant information with your guests to make their visit or stay as comfortable as possible.
Pre-arrival: Information about amenities, policies, and local attractions enables guests to plan their visit and enhances their overall experience.
Check-in: Smooth and efficient check-in procedures contribute to a positive first impression. Welcoming and friendly communication sets the tone for the guest, making them feel valued and comfortable.
Problem Resolution: Handling guest complaints or issues quickly can turn a negative experience into a positive one, and helps demonstrate your commitment to guest satisfaction.
Post-stay: Seeking feedback through surveys or follow-up emails allows guests to express their opinions and provides an opportunity for your company to address any concerns.
Map the End-to-End Guest Journey
Customer journey mapping allows hospitality brands to gain insights into guest behavior, preferences, and pain points at each stage of their interaction with the brand. Understanding how guests navigate their journey provides valuable information for improving services and anticipating needs.
Mapping the customer journey also helps identify various touchpoints where guests interact with the brand, both online and offline. This includes pre-booking research, booking processes, on-site experiences, and post-stay interactions. Recognizing these touchpoints allows brands to optimize each stage of the journey. With a customer journey map, you can pinpoint areas that may need improvement or innovation to enhance the overall guest experience.
Embrace Digital Transformation
Hospitality consumers demand tools that simplify and streamline the entire booking or buying process — from research and planning, through engagement, to the post-sales phase. This makes it critical to invest in smart technology that will better engage consumers and make every part of the customer journey pain-free.
Undergoing a digital transformation should help streamline your operations, reducing wait times and improving the overall guest experience.
Having free Wi-Fi for guests isn’t enough. Investment areas you can focus on include digital and contactless services (like contactless payments, voice control, and biometrics); mobile check-ins; smart home devices in rooms; AI-powered chatbots on your digital properties; virtual tours that recreate a digital environment for consumers to picture themselves in; and instant messaging channels that direct guests to management for any questions and issues. For larger chains and enterprise-level organizations, deploying a local listing management solution should also help maximize your visibility and support your brand’s multichannel strategy.
Personalize the Guest Experience
Personalization plays a significant role in meeting the diverse preferences and expectations of travelers. It also fosters a sense of loyalty among guests. When a company consistently delivers personalized services and memorable experiences, guests are more likely to choose the same brand for future stays, leading to repeat business and long-term loyalty.
Examples of tactics used to personalize the guest experience include:
Optimizing your local business listings and refining your marketing content based on guest personas
Providing options to specify room preferences
Giving personalized welcome letters and amenities
Creating targeted offers and promotions (for example: emailing guests with their membership details, unique vacation ideas, or personal offers that are in line with their preferences and expectations)
Curating local experiences and recommendations
Incorporating voice-activated assistants in rooms
Personalization is impossible if operators don’t have the ability and the means to relate to and understand the needs of their guests. To address this, you can implement technological tools like a customer relationship management (CRM) or customer experience management (CEM) solution, which analyzes big data to create highly customized one-to-one interactions between the guest and the host at scale.
Leverage Guest Experience Surveys to Capture Insights
Guest experience surveys help your team capture valuable insights essential to improving your brand, products, services, and overall customer experience. Organizations that can distribute surveys and solicit feedback efficiently also often have a more complete understanding of their guests and can more easily measure satisfaction and loyalty.
The challenge is to move beyond simply collecting data. As part of your strategy, consider investing in a Voice of the Customer program or guest experience software to ensure you are hearing your guests and extracting rich, meaningful insights from their feedback.
Invest in Online Reputation Management
One of the most important aspects of guest experience management in hospitality is your ability to build a strong brand reputation and respond to online reviews and customer feedback. People are drawn to brands that know how to respond to negative reviews, promptly answer phone calls and emails, and proactively join conversations on social media. Online reviews are especially important:
94% of consumers say a bad review has convinced them to avoid a business.
53% of guests expect management to respond to negative reviews within 7 days, but 63% say that a business has never responded to their review.
45% of consumers are more likely to choose an operator that knows how to respond to negative reviews.
If a guest wrote a 5-star review or gave your team a nice compliment via email, take the time to say thank you. If the feedback is negative or the review came with a low rating, acknowledge the guest and work quickly on resolving any issues related to their experience.
Power Your Guest Experience Management with InMoment
The future of hospitality is bright for customer-centric operators, restaurants, and hotels that are demonstrating a commitment to managing the guest experience. With InMoment, the leading provider of Experience Improvement solutions, you can adapt to meet evolving expectations, leverage experience data from every touchpoint, and power your guest experience program. Schedule a CX demo to learn more about how InMoment can help elevate your guest experiences.
Unlock Expert Guidance on Today’s CX Challenges & Opportunities
Whether you’re struggling with limited resources, data fragmentation, or evolving customer expectations, this guide offers the expert advice you need to elevate your CX strategy. Download now to discover how to transform these challenges into growth opportunities.
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Artificial Intelligence (AI) is being used by more and more businesses every day. Specifically, the world’s leading brands have begun using contact center AI to create a more efficient and effective customer service experience. By integrating these advanced technologies, these companies aim to streamline customer interaction, automate routine tasks, and optimize their overall operations.
What is Contact Center AI?
Contact Center AI, also known as contact center artificial intelligence is the technology that leverages artificial intelligence and machine learning to optimize customer interactions within a contact center. It aims to streamline and improve various aspects of customer service, from handling routine inquiries to providing personalized assistance.
How Does Contact Center AI Work?
Contact Center AI works by leveraging advanced technologies such as artificial intelligence (AI), machine learning (ML), natural language processing (NLP), and automation to enhance and streamline customer interactions within a contact center. The process involves several key components and steps:
Data Collection: Contact center AI starts by collecting and aggregating data from various sources. This data may include historical customer interactions, transcripts of conversations, customer profiles, and information from other relevant databases.
Natural Language Processing: NLP is a crucial component that enables AI systems to understand and interpret human language. Contact center AI employs NLP to analyze and comprehend the meaning of customer inquiries, regardless of the channel used (voice, chat, email).
Intent Recognition: Once the customer’s input is processed through NLP, the system identifies the user’s intent. This involves categorizing the customer’s query to determine the specific action or information the customer is seeking.
Routing and Automation: Based on the identified intent, Contact center AI can automate the routing of the inquiry to the appropriate department or system. For routine tasks, the AI may directly handle the request without human intervention, significantly reducing response times.
Virtual Agents and Chatbots: Virtual agents or chatbots, powered by AI, interact with customers in real-time. These agents can engage in text-based or voice-based conversations that provide assistance, answer queries, and guide users through processes.
Will Contact Center AI Replace Call Center Agents?
The simple answer is no. Artificial intelligence will not replace agents in the near future but provide readily available resources and insights to empower them to effectively solve customer inquiries and deliver exceptional customer experience.
What are the Benefits of Contact Center AI?
Contact Center artificial intelligence offers a range of benefits that contribute to the efficiency, effectiveness, and overall improvement of customer service operations. Many businesses with a contact center would benefit from using AI.
Operational Efficiency and Resource Optimization
Contact center AI solutions streamline operational workflows by automating repetitive and time-consuming tasks. Routine inquiries, such as checking account balances, tracking orders, or providing basic information, can be handled seamlessly by AI-powered virtual agents. This automation reduces the workload on human agents, allowing them to focus on more complex and high-value interactions. As a result, the overall efficiency of the contact center improves, leading to quicker response times and enhanced productivity.
By automating routine tasks, contact enter AI enables businesses to optimize their resource allocation. Human agents can be strategically deployed to handle more intricate issues that require empathy, creativity, and critical thinking. This resource optimization not only improves the utilization of skilled human agents but also contributes to cost savings as the need for additional staff to handle routine tasks decreases.
Scalability and Flexibility
Contact Center AI provides businesses with the flexibility to scale their operations based on demand. During peak hours or high-volume periods, AI systems can seamlessly handle a surge in customer inquiries without the need for immediate human intervention. This scalability ensures that the contact center can adapt to varying levels of customer service demand, maintaining service quality even during peak times.
Enhanced Customer Satisfaction
Through quick and accurate responses, personalized interactions, and proactive issue resolution, Contact Center AI directly contributes to enhanced customer satisfaction. Customers appreciate the convenience of instant assistance, personalized recommendations, and the ability of businesses to anticipate and address their needs. Improved customer satisfaction not only fosters loyalty but can also lead to positive word-of-mouth, attracting new customers to the brand.
In essence, Contact center AI serves as a catalyst for positive change within customer service operations, fostering efficiency, optimizing resources, and ultimately contributing to an elevated customer experience. The integration of AI technologies empowers businesses to navigate the evolving landscape of customer service with agility and responsiveness, ensuring sustained success in meeting and exceeding customer expectations.
AI Use Cases in Contact Center & Examples
Contact center AI is actively transforming customer service across various industries. Here are some real-world examples of Contact Center AI in action:
Banking and Financial Services
Virtual Agents for Account Inquiries: Many banks employ virtual agents powered by AI to handle routine account inquiries, such as checking balances, transaction history, or updating account information. This frees up human agents to focus on more complex financial matters.
E-commerce
Chatbots for Customer Support: E-commerce platforms often use AI-driven chatbots to provide instant assistance to customers. These chatbots can help with order tracking, product information, and even suggest personalized recommendations based on the customer’s browsing history and preferences.
Telecommunications
Interactive Voice Response (IVR) Systems: Telecommunications companies utilize AI-driven IVR systems to efficiently route customer calls. These systems understand natural language and can guide customers through troubleshooting processes or direct them to the appropriate department for support.
Hospitality
Virtual Concierge Services: Hotels and travel agencies employ virtual concierge services powered by AI to provide guests with information about amenities, local attractions, and hotel services. These virtual concierges enhance the overall guest experience.
Automotive Industry
Appointment Reminders and Service Notifications: Automotive service centers leverage AI to send automated appointment reminders and service notifications to vehicle owners. This ensures timely servicing and keeps customers informed about their vehicle maintenance schedules.
What to Look for in Contact Center AI Software
Selecting the right contact center AI software is crucial for maximizing the benefits of artificial intelligence in customer service operations. Here are key factors to consider when evaluating contact center AI solutions:
Scalability
Ensure that the contact center AI software is scalable to handle fluctuations in customer service demand. The solution should seamlessly adapt to varying call volumes and support business growth without compromising performance.
Integration Capabilities
Look for AI software that easily integrates with existing contact center infrastructure, including customer relationship management (CRM) systems, ticketing tools, and communication platforms. Compatibility with other systems ensures a cohesive and interconnected customer service ecosystem.
Customization Options
Opt for a contact center AI solution that offers customization options. Businesses have unique requirements and industry-specific needs, and the AI software should be adaptable to cater to these specifics, allowing for a tailored customer service experience.
Multichannel Support
Consider AI software that supports various communication channels, including voice, chat, email, and social media. The ability to operate seamlessly across multiple channels ensures a unified and consistent customer experience, regardless of the platform customers choose for interaction.
Analytics and Reporting Features
Prioritize AI software that includes robust analytics and reporting tools. These features provide insights into customer behavior, agent performance, and overall contact center efficiency. Analytical capabilities contribute to data-driven decision-making and continuous improvement.
Questions to Ask When Selecting a Contact Center AI Solution
When evaluating contact center AI solutions, asking the right questions is crucial to ensure that the chosen software aligns with your business needs and objectives. These questions will get you on the right track in determining whether or not a software solution will work for your company.
1. Can the contact center AI software integrate with current systems and workflow?
Integration is vital for a seamless operation. Compatibility with existing systems ensures that the AI software complements your current infrastructure, avoiding disruptions and facilitating a more efficient workflow.
2. What types of interactions are within the capabilities of contact center artificial intelligence?
Understanding the scope of the AI’s capabilities is essential. Different solutions may excel in specific types of interactions, whether it’s handling routine queries, providing technical support, or processing transactions. Ensure that the AI aligns with your business’s unique needs.
3. What’s the estimated time frame from implementing to utilizing contact center AI software?
Knowing the implementation timeline is crucial for planning. An efficient and timely deployment minimizes disruptions to ongoing operations, allowing your contact center to start realizing the benefits of AI without unnecessary delays.
4. Is extensive training required to use contact center AI software and how long will it take?
Assessing the training requirements is essential for a smooth transition. A user-friendly AI system with minimal training needs ensures faster adoption by contact center agents. Understanding the training duration helps plan resources effectively and ensures a quicker return on investment.
Asking these questions empowers businesses to make informed decisions, selecting a contact center AI solution that seamlessly integrates, meets interaction requirements, aligns with implementation timelines, and requires reasonable training for efficient adoption.
Challenges of Contact Center AI
While Contact Center AI offers numerous benefits, its implementation comes with its own set of challenges. Addressing these challenges is crucial for ensuring seamless integration and optimizing the performance of AI technologies in contact centers.
Customer Acceptance: some customers may prefer human interactions and find it challenging to adapt to AI-driven customer service. Building trust and acceptance for AI among customers is a significant hurdle.
Employee Resistance: Employees might resist the adoption of AI due to concerns about job displacement or changes to their roles. Proactively addressing these concerns and providing training to ease the transition is crucial.
Ethical Considerations: AI systems handle sensitive customer data, and ethical concerns arise regarding data privacy, security, and the responsible use of AI. Ensuring compliance with data protection regulations and establishing ethical guidelines for AI use is essential.
Training and Skill Gaps: Contact Center AI systems require continuous training and updates to adapt to changing customer behaviors and industry trends. Ensuring that human agents possess the necessary skills to work alongside AI and handle complex issues is essential.
Over Reliance on Automation: Over reliance on AI for all customer interactions without appropriate human oversight can lead to issues. Complex queries, emotional situations, or unique customer needs may require the intervention of human agents for optimal resolution.
Overcoming these challenges requires a strategic approach, collaboration between technology and business stakeholders, and a commitment to continuous improvement. By addressing these issues, organizations can unlock the full potential of contact center AI and provide enhanced customer experiences.
InMoment’s Solution for Contact Center AI
InMoment’s contact center solution gives organizations the power to use specialized text analytics models to understand nuanced exchanges in customer interactions. These models, which can be tailored to fit any industry, link customer experience insights to agent performance, call stage, and customer issues. Schedule a demo today and see what InMoment can do for you!
We surveyed 1,215 consumers to hear their preferred channels, their expectations, and their barriers to adapting to emerging digital support options. Here’s what we found:
81% of consumers still require an interaction to resolve issues (over self-serve channels)
61% expect brands to resolve their issues the first time, or they’ll start considering competitors
41% expect to be contacted within 5 minutes after reporting an issue
Consumer expectations have shifted. Your strategy should too.
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Future-proof your contact center with our comprehensive guide. Gain insight into how your business can stay ahead of industry trends and leverage AI-powered insights to drive customer satisfaction and business success.
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Discover what conversational intelligence is, its key benefits for businesses, and the must-have features to improve customer experience and team performance.
In today’s data-rich, insight-starved enterprise environment, conversations are one of the most underleveraged sources of customer intelligence. But with modern technology, businesses can now tap into that resource at scale. Conversational intelligence (CI) enables organizations to extract meaningful insights from natural language interactions, transforming recorded conversations into actionable data that drives smarter decisions, faster responses, and better outcomes.
At InMoment, we believe Conversational Intelligence is a crucial component of an integrated CX strategy. By pairing CI with surveys, reputation management, and real-time VoC programs, brands gain a 360-degree understanding of their customers and employees.
Let’s take a deep dive into what conversational intelligence is, how it works, and why it’s become a strategic necessity for enterprise organizations.
What is Conversational Intelligence?
Conversational intelligence is the technology that enables companies to capture, process, and analyze voice and text-based customer interactions across channels. It relies on a blend of artificial intelligence (AI), machine learning (ML), and natural language processing (NLP) to surface key trends, themes, sentiments, and intents from real customer conversations at scale.
Unlike traditional analytics, conversational intelligence focuses on the full context of a conversation, extracting not just what’s said, but how and why. It turns everyday conversations—support calls, emails, chat logs—into structured data to optimize service, reduce churn, and inform product development.
Should we include the original inline image here?
Conversational Intelligence vs. Conversational AI
It’s easy to confuse conversational intelligence with conversational AI, but they serve distinct functions.
Conversational Intelligence analyzes human-to-human interactions (like support calls or sales meetings) to extract insights.
Conversational AI powers automated interactions through chatbots or voice assistants using NLP and generative models.
Think of conversational intelligence as the analysis layer—listening, learning, and turning conversation data into insights. Meanwhile, conversational AI is the execution layer, which simulates conversations through automation.
Why is Conversational Intelligence Important?
Conversational intelligence matters because businesses are drowning in data but starved for insight. Every customer call, email, or message contains unfiltered feedback—if only brands could listen at scale.
With CI, companies can:
Understand pain points as they arise
Monitor agent performance and compliance
Surface product issues before they go viral
Identify the “why” behind churn or low satisfaction
It’s a powerful, often untapped lever for experience improvement.
How Does Conversational Intelligence Work?
Let’s break down how conversational intelligence works, step-by-step.
Data Collection
CI platforms collect data from a range of sources—voice calls, live chats, emails, SMS messages, social media interactions, and more. Integrations with CRMs, call center systems, and ticketing tools enable full-funnel visibility.
Preprocessing
Once data is collected, it must be cleaned and structured. This includes removing background noise from audio, redacting sensitive information, and formatting inputs for consistent analysis.
Audio Transcription
Voice interactions are transcribed to text using automatic speech recognition (ASR). Accuracy here is critical, as it directly impacts the quality of downstream analysis.
Understanding Language
Natural language processing and machine learning models interpret meaning, detect sentiment, and identify entities, keywords, and intents. This enables platforms to recognize frustration, praise, or common complaints, contextually.
Analytics and Reporting
The final layer transforms data into dashboards, trend reports, and alerts. Users can filter by topic, sentiment, region, team, or product line to find what matters most. The goal: give teams fast, actionable insights.
What’s the Difference Between Conversation Intelligence vs Call Tracking Software?
While both tools deal with calls, call tracking software primarily monitors call sources and routing, focusing on attribution and marketing ROI. Conversational intelligence, by contrast, focuses on the content of conversations, surfacing strategic insights from the dialogue itself.
Benefits of Conversational Intelligence
Conversational intelligence offers transformative benefits across CX, marketing, sales, and operations. Here’s how:
1. Optimizing Call Center Performance
By analyzing 100% of customer interactions, CI reveals agent performance trends, identifies call drivers, and uncovers friction in real time. Supervisors can pinpoint top performers, flag training gaps, and reduce average handle time (AHT) with laser precision.
2. Agent Nurturing and Training
CI enables continuous learning by highlighting standout calls and areas for improvement. Teams can create coaching playlists or QA workflows using real examples.
3. Extracting Valuable Insights
Executives and product teams gain a window into the voice of the customer (VoC), capturing unfiltered feedback that fuels innovation.
4. Personalized Customer Interactions
By understanding previous conversations and sentiment, agents can tailor interactions based on the customer’s tone, history, and intent, leading to better outcomes and stronger loyalty.
5. Efficient Resource Allocation
With clear data on call drivers and intents, teams can staff according to demand, automate low-value queries, and route issues to the right departments faster, reducing costs and boosting satisfaction.
6. Identifying Emerging Customer Trends
Analyzing thousands of conversations helps organizations spot shifts in preferences, product issues, or competitive mentions before they escalate, enabling proactive change.
7. Closing the Feedback Loop in Real Time
CI tools flag urgent issues and surface themes instantly, empowering teams to act on insights in the moment. Whether it’s resolving a product bug or recovering a frustrated customer, action happens faster.
Where should I put this internal link, peeps? https://inmoment.com/blog/conversational-intelligence-insights/
Conversation Intelligence Examples by Industry
Healthcare: Improve patient experience and understand concerns in scheduling, billing, or bedside manner
E-Commerce: Optimize sales and support workflows; uncover cart abandonment trends
Financial Services: Monitor compliance, detect fraud signals, and enhance service clarity
Retail: Pinpoint feedback around store layout, product availability, or service gaps
Hotels & Lodging: Understand friction in booking and check-in processes
Entertainment & Recreation: Enhance guest experience through feedback on events and services
Restaurants / Food Services: Monitor order issues, menu feedback, and staff performance
Insurance: Improve claims processes and policy explanation clarity
Health & Wellness: Identify coaching or service quality concerns
Automotive: Uncover dealership-level feedback and service concerns
Airlines: Track delays, cancellations, and gate agent interactions
Features to Look For in a Conversational Intelligence Platform
The right platform makes all the difference. Look for tools that not only collect and process data but make it accessible and actionable across teams. Key features include:
Omnichannel Data Capture: Collects conversations from calls, email, SMS, chat, and social
Real-Time Alerts: Flags urgent issues as they happen
Custom Dashboards and Reporting: Tailors views by department, region, or campaign
Sentiment and Intent Analysis: Goes beyond keywords to detect emotions and purpose
Integrations with CRM, CX, and Support Tools: Syncs data across platforms for unified insights
AI-Powered Coaching Tools: Supports team training with real interaction examples
Unlock Actionable Insights from Every Conversation with InMoment
Conversational intelligence is more than speech-to-text. It’s how leading brands transform customer conversations into strategic advantage. By tapping into CI, businesses reduce churn, optimize support, and understand their customers on a deeper level.
InMoment’s CI tools are built to scale with you. Paired with our Experience Improvement (XI) platform, reputation management tools, and survey programs, we help you close the loop and lead in customer experience.
Ready to hear what your customers are really saying? Request a demo and see what InMoment can do.
We surveyed 1,215 consumers to hear their preferred channels, their expectations, and their barriers to adapting to emerging digital support options. Here’s what we found:
81% of consumers still require an interaction to resolve issues (over self-serve channels)
61% expect brands to resolve their issues the first time, or they’ll start considering competitors
41% expect to be contacted within 5 minutes after reporting an issue
Consumer expectations have shifted. Your strategy should too.
Thank you
Your download will begin shortly. If it doesn’t, click on the download button.
Future-proof your contact center with our comprehensive guide. Gain insight into how your business can stay ahead of industry trends and leverage AI-powered insights to drive customer satisfaction and business success.
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Contact centers are not new by any means. As a matter of fact, the first employed call center agents date back to the 1950s. But, these agents only made and received phone calls. It wasn’t until the turn of the century that these call centers evolved into multichannel contact centers. However, even these are quickly becoming obsolete. The future of the contact center lies in the omnichannel contact center.
What is an Omnichannel Contact Center?
An omnichannel contact center is a customer service model that integrates and manages various communication channels in a unified and seamless manner. Unlike traditional multichannel setups, where each communication channel operates independently, an omnichannel contact center provides a cohesive and consistent customer experience across all channels.
What’s the Difference Between Omnichannel and Multichannel Contact Center?
In an omnichannel contact center, customers can interact with a business through channels such as phone calls, emails, chat, social media, and more. What distinguishes it from multichannel systems is the integration of these channels, allowing customers to switch between them without losing the context of their interactions. For example, a customer might start a conversation via chat and then continue it later over the phone, with the contact center retaining the history and context of the entire interaction.
Is an Omnichannel Contact Center Better Than A Multichannel Contact Center?
The debate between an omnichannel contact center and a multichannel contact center often revolves around the depth and quality of customer experience. While both models involve managing customer interactions across various channels, there are distinct differences in their approaches.
While a multichannel contact center provides various communication options, an omnichannel contact center is better positioned to meet the heightened expectations of today’s customers. It not only offers diverse channels but integrates them seamlessly, creating a unified and customer-centric approach that fosters satisfaction and loyalty. Ultimately, the choice between the two models depends on the organization’s commitment to delivering a superior customer experience.
What are the Benefits of an Omnichannel Contact Center?
Embracing strategies that bolster omnichannel contact centers facilitates the delivery of seamless, convenient, and efficient customer interactions. Through the integration of various communication channels into a cohesive system, businesses can enjoy a host of benefits that greatly elevate the customer experience.
Enhanced Customer Engagement
Omnichannel contact center solutions empower businesses to engage with customers on their terms. Whether a customer prefers email, phone, chat, or social media, an omnichannel system seamlessly integrates all these channels, allowing for consistent, real-time interactions. When customers can switch between channels without losing context, it reduces frustration and leads to a more positive experience.
Imagine a customer who initiates a support request through chat but needs to step away. With an omnichannel system, they can easily switch to a phone call later, and the agent will already have the chat history, avoiding the need to repeat the issue. This level of flexibility and continuity in customer feedback fosters better relationships and builds trust.
Efficient Closed-Loop Systems
In a contact center, the value of closing the loop is of the utmost importance. Omnichannel solutions can greatly improve the efficiency of closed-loop systems within a business. When agents have access to a unified view of customer data and interaction history across all channels, they can quickly understand the context of the customer’s issue. This is a crucial element of customer experience management as it ensures that no customer concern or query falls through the cracks and that each issue is tracked from initiation to resolution.
Omnichannel contact center solutions can also incorporate automation and AI-powered tools. These technologies can intelligently route customer inquiries to the most appropriate agent or department. For instance, a chatbot can handle routine queries, while complex issues are directed to specialized human agents. This streamlines the resolution process, ensuring that customers get the help they need as quickly as possible.
Consistent Brand Experience
Consistency is a key factor in creating a strong and recognizable brand. Omnichannel contact center solutions enable businesses to deliver a consistent brand experience across all customer touchpoints. From the tone of communication to the information provided, customers should feel that they are dealing with one unified entity, not a collection of disconnected departments.
This consistency helps to reinforce brand loyalty and trust. Whether a customer is engaging on social media, talking on the phone, or visiting a physical store, the brand experience should remain uniform. Omnichannel solutions can help achieve this by ensuring all customer-facing teams have access to the same information and guidelines for interacting with customers.
Data-Driven Insights
Omnichannel contact center solutions provide valuable data and analytics. By collecting and analyzing customer interactions across various channels, businesses gain insights into customer preferences, pain points, and behavioral patterns. These insights can inform strategic decisions, improve product and service offerings, and enhance the overall customer experience.
Data-driven insights also allow for more personalized interactions. When agents have access to a customer’s history and preferences, they can tailor their responses and recommendations, creating a more personalized and meaningful interaction. This not only improves the customer experience but can also lead to increased sales and customer retention.
What Does an Omnichannel Contact Center Solve?
An omnichannel contact center addresses several challenges and issues in customer service and provides solutions to enhance the overall customer experience. Here are key problems that an omnichannel contact center aims to solve:
Customer Friction
Issue: In a multichannel environment, customers may experience friction when transitioning between different channels, leading to a disjointed and frustrating experience.
Solution: Omnichannel contact centers eliminate friction by offering a seamless and consistent experience across all communication channels. Customers can switch between channels without losing context or having to repeat information.
Operational Efficiency
Issue: Multichannel centers may struggle with the inefficiency of managing different channels separately, leading to delays, errors, and increased workload.
Solution: Omnichannel contact centers centralize communication management, improving operational efficiency. Agents can access all channels from a unified dashboard, streamlining processes and reducing the risk of information silos.
Enhanced Insights
Issue: Siloed data from separate channels can make it challenging to gain a comprehensive understanding of customer behavior and preferences.
Solution: Omnichannel systems provide a holistic view of customer interactions, allowing businesses to gather valuable insights. This data-driven approach enables informed decision-making and the ability to tailor services to customer needs.
Features to Look for in an Omnichannel Contact Center
When deciding on omnichannel contact center solutions, there are many things to consider. The functionalities you need will be dependent on the uses and goals of your contact center. Regardless, there are a few main features that any successful contact center should have.
Agent Scorecards
Agent Scorecards are tools that provide a comprehensive evaluation of an individual agent’s performance within the contact center. These scorecards typically encompass a range of key employee and customer experience KPIs and metrics specific to the agent’s responsibilities. Metrics may include factors like average handling time, first contact resolution, customer satisfaction scores, and adherence to scripts or guidelines. By analyzing these metrics, managers gain insights into an agent’s efficiency, effectiveness, and overall contribution to the customer experience.
AI-Driven Text Analytics
AI-Driven Text Analytics refers to the application of artificial intelligence and machine learning techniques to analyze and derive meaningful insights from unstructured text data. In the context of an omnichannel contact center, unstructured data often includes customer interactions from various sources, such as emails, chat transcripts, social media comments, and survey responses. Traditional analysis of such data can be time-consuming and challenging due to its unstructured nature, but AI-driven solutions bring efficiency and accuracy to the process.
Transcription Services
Contact centers often deal with a significant volume of audio data, including customer service calls, feedback voicemails, and internal meetings. Manually processing and analyzing these recordings can be time-consuming and impractical. Transcription services streamline this by converting hours of audio content into text, making it more manageable for further analysis and exploration. This process is essential for making audio content accessible, searchable, and analyzable.
Quality Assurance
Quality Assurance in a contact center involves systematic monitoring and evaluation of customer interactions to ensure that they meet predefined standards of excellence. This process encompasses various elements, including adherence to scripts, accuracy of information provided, adherence to company policies, and the overall effectiveness of customer service.
Strategic Services
Strategic Services in an omnichannel contact center context involve a suite of specialized offerings designed to provide businesses with expert guidance and actionable insights. Engaging in strategic services allows businesses to tap into the expertise of professionals who specialize in optimizing contact center operations. These experts often have a deep understanding of industry trends, best practices, and emerging technologies. These services also include the provision of detailed and customized reports that dive into contact center analytics and answer key business questions. These questions could revolve around performance metrics, customer satisfaction, operational efficiency, and other critical aspects of contact center management.
Omnichannel Contact Center Examples
Numerous organizations across various industries have successfully implemented omnichannel contact centers to enhance customer experiences and streamline communication across multiple channels. To represent the practical uses of an omnichannel contact center solution, let’s examine two customers in two different industries.
Financial Services
A customer, Sarah, encounters an issue with a recent credit card transaction. She notices an unauthorized charge on her credit card statement and is concerned about potential fraud.
The Omnichannel Solution:
Mobile App Investigation: Sarah logs into the mobile banking app to review her recent transactions. The app provides detailed information about each transaction, allowing her to identify the unauthorized charge.
In-App Chat Support: Using the in-app chat support feature, Sarah initiates a conversation with a customer support representative. She explains the issue and provides details about the unauthorized transaction.
Live Video Call Option: The customer support representative, recognizing the sensitivity of the issue, suggests initiating a live video call through the mobile app. This allows Sarah to show any supporting documents or ID verification directly.
Context Preservation: Throughout the interaction, Sarah’s information and conversation history are seamlessly transferred from the mobile app to the video call, ensuring that she doesn’t need to repeat information and that the context is preserved.
Resolution and Follow-Up: The representative investigates the issue in real-time, verifies Sarah’s identity, and resolves the unauthorized charge. During the video call, the representative guides Sarah through the steps to secure her account and provides assurance. Follow-up communications are sent through secure channels, ensuring privacy.
In this financial services scenario, the omnichannel contact center enables a smooth and secure resolution for the customer, utilizing mobile app features, chat support, and live video calls to address the issue comprehensively.
Retail
Omnichannel contact centers can also succeed in other industries. Let’s say John, a retail customer, purchases a laptop online from a retail store. Unfortunately, the laptop arrives with a defect, and John needs assistance with returning and replacing the product.
The Omnichannel Solution:
Live Chat Support: Using the website’s live chat support, John initiates a conversation with a customer service agent. He explains the issue with the defective laptop and requests assistance with the return and replacement process.
Email Correspondence: To provide supporting documentation, John uploads pictures of the defective product through the live chat. The customer service agent suggests continuing the conversation via email to maintain a documented trail.
In-Store Return Option: The retailer’s omnichannel strategy includes an option for in-store returns. The customer service agent provides John with the option to return the defective laptop at a nearby physical store for quicker resolution.
Context Transfer: When John visits the physical store, the in-store staff has access to the email correspondence and live chat history, ensuring a seamless continuation of the resolution process. John doesn’t need to re-explain the issue.
Replacement Process: The in-store staff processes the return, facilitates the replacement of the laptop, and ensures that John leaves the store with a fully functional product. Any additional communications or confirmations are sent via email for John’s records.
In this retail scenario, the omnichannel contact center facilitates a convenient and efficient resolution for the customer, utilizing online order tracking, live chat support, email correspondence, and in-store returns to address the issue effectively.
Develop Your Omnichannel Contact Center
With InMoment’s omnichannel contact center software, you can house all your data in one place. This capability allows you to deliver consistent, quality, and customer-centric experiences. Schedule a demo to see what InMoment can do for you.
We surveyed 1,215 consumers to hear their preferred channels, their expectations, and their barriers to adapting to emerging digital support options. Here’s what we found:
81% of consumers still require an interaction to resolve issues (over self-serve channels)
61% expect brands to resolve their issues the first time, or they’ll start considering competitors
41% expect to be contacted within 5 minutes after reporting an issue
Consumer expectations have shifted. Your strategy should too.
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Future-proof your contact center with our comprehensive guide. Gain insight into how your business can stay ahead of industry trends and leverage AI-powered insights to drive customer satisfaction and business success.
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Guiding a loved one through the customer journey of senior living is an intimately personal and emotional endeavor. At the heart of it; senior care is more than finding a place for a loved one to reside. It’s about fostering a community steeped in care, safety, comfort, and boundless joy. In this context, maintaining a sterling reputation in the realm of senior living becomes pivotal—it’s the bridge aligning with the aspirations of those seeking unparalleled care for their cherished family members. Upholding this reputation ensures that your services deeply connect with and satisfy the needs of those pursuing exceptional care for their loved ones.
Why Reputation Management is Important for Senior Care
More than 90% of families heavily rely on online reviews when deciding on senior living communities, a significant increase from the 82% recorded in 2020. This highlights the critical need for a proactive reputation management strategy, not just for sustained success but as an essential component for care organizations aspiring to attract seniors and maintain a reputation for exceptional service acknowledged online. To effectively appeal to these families and surpass competitors, implementing targeted reputation management strategies within senior care is paramount.
Reputation Management Strategies for Senior Living
Crafting a robust reputation management strategy for senior living hinges on understanding your core audience, primarily the families of prospective residents. Their needs, concerns, and expectations form the bedrock of your approach. It’s vital to define clear messaging that resonates with this audience, conveying the essence of your care services consistently across all touchpoints. This consistency in messaging cultivates trust and reliability, crucial elements in building a positive reputation within the senior living landscape.
Once you’ve established alignment with your primary audience and messaging, there are three effective strategies to fortify your reputation: optimizing local business listings, amplifying positive reviews, and harnessing valuable insights from customer feedback. These actions work in unison to bolster your standing within the senior living community, enhancing visibility, credibility, and responsiveness to refine the overall resident experience.
Manage and Optimize Local Business Listings
The primary step toward building your online reputation involves either creating or claiming your business listing across prominent directories like Google Business, Facebook, Bing Places, and Yelp. Given that nearly half of all Google searches, 46% to be exact, incorporate local intent, there’s a significant surge in people actively seeking services like senior care within their local area. By creating or claiming your business listing, you could show up for common search terms such as “senior living near me” or “senior care near me”, while also securing placement in local search maps such as Google Maps or Bing Places.
Ensure Accuracy and Consistency of Your Business Information
Once your business listing is verified, the subsequent stride involves furnishing comprehensive business information, encompassing the business name, address, phone number, website, and operating hours. Maintaining not just accuracy but also consistency across these details is paramount. Even minor details like abbreviations and punctuations, should be unified across all your owned business listings.
Save Time with Listing Management Tools
Managing multiple locations across diverse business directories can be time-consuming and prone to errors, potentially resulting in misinformation that may dissuade families from exploring your offerings in favor of competitors. Additionally, inconsistencies in information can negatively affect your local listing rankings. To streamline this process and minimize errors, leveraging local listing management tools becomes imperative. These tools facilitate effortless monitoring and management of your business listings with minimal effort, ensuring that your business information remains consistently accurate and reliable for online users.
Crafting an Effective Approach for Gathering Reviews
Ensuring a thriving senior residence involves not just providing exceptional care but also fostering a sense of trust and community. One effective way to achieve this is by actively seeking and encouraging reviews from residents and their families. Begin by creating a positive environment that naturally elicits positive customer feedback and optimizes your senior living reviews. Train your staff to prioritize personalized care, addressing the unique needs and preferences of each resident.
Leverage Popular Review Sites
Encourage residents and their families to share their experiences on popular review sites. You can boost the volume of feedback you receive by simplifying the process like generating a feedback link such as a Facebook or Google review link and sending it directly via email. Another option worth exploring is the integration of QR codes into your mailing materials, contributing to a seamless and efficient feedback gathering process. Additionally, leverage the power of social media to engage with your community. Share heartwarming stories, testimonials, and encourage open conversations. Create an online space where residents and their families feel comfortable expressing their thoughts about the community.
Surveys and Follow-Up
Implementing a structured feedback system is crucial. Utilize online surveys and send follow-up emails after positive interactions to kindly request reviews. By showcasing the positive aspects of your senior living community and actively seeking feedback, you not only create a transparent and open atmosphere but also enhance your community’s online presence, attracting potential residents who value authenticity and personal care.
Highlight and Promote Positive Reviews
For families embarking on the journey to find the perfect senior living community is a significant step often guided by heartfelt experiences shared through reviews. While your messaging can do the best it can to persuade people to visit your community, it’s the sincere stories of families who have walked the same path that truly touch the heart and convince them to schedule a visit. Therefore, it’s important to highlight these positive reviews to showcase the compassionate care your facility provides.
Don’t be afraid to seek feedback, instead consider it a treasure trove of shared experiences that can guide others on their senior care journey. It also opens the door to uncover opportunities to improve care and trends to outperform local competitors. People prefer to read the authentic voices of those who have interacted with your staff and experienced the warmth of your facilities. These stories hold immeasurable value as they provide a genuine take on the senior living experience. Actively seek out these stories, the ones that capture the essence of your community, and bring them to the forefront. Share them within your marketing materials, website, and social media.
Managing these reviews and populating them on your website can be time-consuming and tedious. To help automate this process, there are many review widgets and software that can help including InMoment’s reputation management software. With this tool, your team can effortlessly weave review widgets throughout the website starting with the homepage, creating a virtual tapestry of shared moments as they navigate and explore living options. You can even dedicate a whole webpage to these stories highlighting appreciation and gratitude for current residents, offering solace and insight to those considering your community.
For many families and seniors, these heartfelt narratives become the deciding factor in choosing a senior care service or facility. By delicately placing recent testimonials alongside the commendations from other seniors, you not only simplify the research process but also cultivate trust. It’s a testament to your commitment to transparency and creating a genuinely compassionate senior living experience. Every review is not just a reflection of your facility; it’s a shared journey of care, empathy, and support.
Extract Valuable Insights from Feedback
An integral aspect of any senior care reputation management strategy involves enhancing the overall living experience. Testimonials go beyond attracting new residents; they serve as a reflection of the quality of care. For example, you may receive responses highlighting that cleanliness is frequently associated with positive feedback, while there may be negative sentiment often related to the lack of attentiveness. Therefore, tapping into recent reviews will not only reveal the strengths of senior living but also bring to light areas of improvement that might be overlooked.
Streamline Analysis with AI
However, combing through every feedback can be a labor-intensive and time-consuming task. To accurately understand and uncover overarching themes, you would need to manually identify keywords indicative of positive or negative sentiments. This could take days or even weeks to organize and finalize insights into an actionable strategy that could improve your senior living reputation.
However, with today’s technological advancements, this process can be automated. By harnessing customer experience AI, hundreds or even thousands of reviews can be analyzed within minutes, providing accurate keyword analysis and trending data. Obtaining this accurate and insightful data in a shorter period of time, allows your team to quickly implement operational changes to positively impact the quality of care. This not only brings satisfaction to current residents but also leaves a lasting impression on those considering your senior care facility. Taking swift action based on review data demonstrates that you’re attuned to the needs of your seniors—a crucial factor for individuals seeking senior care options.
How to Pick the Right Reputation Management Partner
Selecting the appropriate reputation management partner for a senior living community is a pivotal step in ensuring a positive and trustworthy image in the eyes of residents and their families. Begin by clearly outlining the specific needs and goals unique to a senior living environment. Identify areas that require attention, whether it’s maintaining positive reviews, managing feedback, or enhancing the overall perception of the community.
Research and Proof of Success
Conduct comprehensive research to identify reputation management companies with expertise in the senior living industry. Explore their track record, focusing on case studies, client testimonials, and online reviews related to senior care facilities. Seek recommendations from other senior living communities or industry professionals who have faced similar challenges.
Open Communication and Transparency
Transparency is crucial in this partnership, particularly in the realm of senior care where trust is paramount. Opt for a reputation management partner who is open about their strategies, methodologies, and reporting processes. Effective communication is key, ensuring that the partner keeps you informed throughout the entire process, addressing concerns and aligning their efforts with the unique values and objectives of the senior community.
Evaluate Services
While budget considerations are important, prioritize value over cost. Evaluate the services offered by potential partners, looking for options that cater specifically to the needs of a senior living community. Assess the long-term benefits of their solutions, considering how their strategies can positively impact the community’s reputation and resident satisfaction.
Streamlined Services and Technology
Seeking a reputation management partner for your senior care facility should involve those equipped with modern, advanced technology to enhance operational efficiency. Look for a partner that simplifies the monitoring and management of your reputation, utilizing cutting-edge tools like Artificial Intelligence (AI) to streamline workflows. The objective is to reduce the workload on your team, ensuring that the technology doesn’t create additional burdens but rather facilitates smoother processes. By embracing such advanced solutions, your team can redirect their focus towards more vital strategies, particularly in enhancing the overall senior living experience.
Integrations
In addition to selecting a partner with dependable technology, it’s important that they can integrate with widely-used senior living platforms. An effective reputation management strategy for senior living entails the ability to effortlessly aggregate, view, and respond to reviews on these platforms. For example, InMoment’s award-winning feedback software can easily integrate with the well-known senior care network, A Place for Mom, where hundreds of thousands of reviews offer first-hand experience from seniors and their loved ones.
In essence, finding the right reputation management partner for a senior community involves meticulous research, transparent communication, and a keen understanding of the unique challenges and values within the senior care industry. This approach will help establish a partnership that safeguards the reputation of the community and fosters trust among residents and their families.
Take Charge of Your Senior Living Reputation Management with InMoment
Guiding a loved one through the senior living journey requires a reputation management strategy that transcends the traditional view of care facilities. It’s about fostering a community rooted in care, safety, and joy. As more than 90% of families turn to online reviews, implementing targeted reputation management strategies becomes imperative. Choosing the right reputation management partner involves thorough research and transparency, aligning strategies with the unique needs of the senior care industry. With the right approach, senior care facilities can thrive in the digital landscape, attracting contented families and standing out in the competitive senior living market. Discover how InMoment can help senior living communities navigate the evolving digital landscape successfully, by scheduling a reputation management demo. Start building a favorable reputation that not only draws in families but also distinguishes your senior living community in the competitive market.
References
LinkedIn. The Power of Reviews: Why Senior Living Communities Need to Prioritize Online Reputation Management. (https://www.linkedin.com/pulse/power-reviews-why-senior-living-communities-need/) Accessed 1/9/24.
Creating Results. 8 Senior Living Statistics You Should Know. (https://creatingresults.com/blog/2020/08/27/8-senior-living-statistics/) Accessed 1/9/24.
Safari Digital. 18 Local SEO Statistics that Matter in 2023. (https://www.safaridigital.com.au/blog/local-seo-statistics/) Accessed 1/9/24.
In the2025 Reputation Industry Benchmark Report, we analyzed31 million reviews from 226,500 business locationsto uncover the key trends separating industry leaders from those falling behind.
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Managing the B2B customer experience is a key growth strategy for organizations across a wide variety of industries. For good reason: delivering great customer experience (CX) leads to increased loyalty, lower churn, more referrals, positive word of mouth, and higher-value customers.
B2B (business-to-business) transactions often involve ongoing relationships and partnerships. Effective customer experience management helps build and maintain strong, long-term relationships by meeting the needs and expectations of your business customers consistently.
What is B2B Customer Experience?
B2B customer experience can refer to the interactions and overall relationship between a business and its business customers. It may also refer to a digital benchmark: your customers’ interactions on your website, mobile app, or software dashboard. The B2B CX may also refer to a company’s ability to respond to customer questions and cases.
Given these various interpretations, we can define the B2B customer experience as the cumulative impact of all interactions and experiences between your business and your business customers, at every touch point across the entire customer journey.
Why is B2B CX Important?
The B2B customer experience is a crucial aspect of building and maintaining successful and long-lasting relationships in the business world. Organizations that strategically allocate their resources to strengthen their customer experience focus stand to gain an edge over the competition.
Great customer experiences foster loyalty. B2B customers are more likely to continue doing business with a company that consistently delivers value, meets their expectations, and provides excellent service. Loyal customers are also more likely to recommend the business to others.
Great customer experiences help your brand achieve differentiation. In competitive B2B markets, where products and services may be similar, customer experience becomes a key differentiator. A great customer experience can set your company apart from competitors and help you win and retain clients.
Great customer experiences bolster your Customer Lifetime Value (CLV). When customers are satisfied and engaged, they are more likely to make repeat purchases, upgrade services, enter into partnerships with your company, and explore additional offerings over time.
Great customer experiences improve brand reputation. If you consistently deliver positive experiences, your brand is more likely to be seen as reliable, trustworthy, and customer-centric. This positive reputation can attract new customers and partners.
Ultimately, a positive B2B customer experience contributes to customer satisfaction, loyalty, and the potential for long-term partnerships and repeat business. It goes beyond individual transactions and focuses on building a strong foundation for ongoing collaboration.
What are Some B2B Customer Experience Examples?
Here are some examples of how B2B companies are applying tactics designed to improve the customer experience:
CRM platform HubSpot utilizes chatbots to connect with customers and encourage open communication. The chatbots automatically help users find responses to their questions and discover helpful content like help center articles, blogs, and resource pages.
Social media marketing platform Hootsuite leverages InMoment to make the Net Promoter Score (NPS) methodology central to its operation. By utilizing the in-app customer feedback software tool, Hootsuite can prioritize CX improvements that will have the most business impact and have been able to triple its Net Promoter Score.
Transport and business services brand FedEx launched a single external newsletter to streamline its communication with customers, instead of sending out multiple emails from various departments within the organization. This helped break down silos and made things simpler not only for FedEx’s customers but also for each of the company’s internal teams working together to deliver meaningful information and valuable content to customers.
Software company PandaDoc uses multiple surveys to monitor customer sentiment and improve product experience. The company also acts on insights from customer feedback in order to understand and improve the skills of its support agents, enabling them to become better at serving PandaDoc customers.
Every time a customer buys its cloud storage suite, tech company IBM assigns specialists to help with onboarding and setup. This gives customers a hassle-free experience at a critical stage of their purchase journey. Additionally, IBM specialists educate customers with tutorials, expert advice, recommendations, and best practices to foster long-lasting relationships.
High-tech industrial company GE operates customer experience centers to showcase the company’s capabilities. Customers can visit these centers to see GE’s manufacturing systems in action and discuss a personalized plan with the company’s CX representatives.
How Does the B2B Customer Experience Differ from B2C?
B2B CX strategies are often inspired by best practices in B2C customer experience management. However, there are key differences and nuances between the two due to the nature of the relationships, the complexity of transactions, and the unique needs of each type of customer.
Decision-making: B2B transactions are often characterized by a more complex decision-making process involving a group of decision-makers within the business, and the sales cycle may be longer. Relationship-building and addressing the needs of multiple stakeholders are crucial in B2B interactions.
Customer relationships. In B2B transactions, business customers often seek long-term partnerships, and the relationship extends beyond individual transactions. Personalized service, understanding the client’s business, and collaboration are key elements.
Customization and personalization. Unlike B2C products and services, B2B offerings usually present various options for customization and personalization in order to meet the particular needs of the business customer.
Support and service. B2C customer support often focuses on scalable solutions, such as online chat, email support, or call centers, to address the needs of a larger customer base. In B2B, customer support tends to be more hands-on and personalized, with dedicated account managers, CX representatives, and specialized support teams.
Similarities Between B2B and B2C Experiences
While your B2B and B2C customers might differ, your B2B client is a human who spends a lot of time on B2C sites such as Amazon. They’ve come to expect consumer-level digital experiences at work and play. Therefore, there has been more consumerization of B2B customer experiences. Here are 12 ways to “consumerize” B2B customer experience:
Freemium or trial access. Appcues found 90% of users want to try a product for free. Can you design a lite but still valuable-to-the-user version of your product? If so, this can be a great lead-generation channel. Give marketing adequate development resources and let them run it.
Fully digital. There’s no need for interaction with a live person to access and use the product. Users expect the app to understand their goals and take them step-by-step through the process to meet their goals.
Intuitive setup and use. No user wants to have to read an essay on how to get started; it should be one step clicks without confusion. There’s no need to look for what they need, no need to be trained by an admin — it’s right there.
Quick time to value. The user wants to do their job faster, easier, and better — make that happen quickly before they find another option.
Easy connections to existing tech. While you’re focused on the individual end-user, don’t forget your app needs to fit into the organization’s workflow, speeding time to value and allowing your power user to advocate for your app. Also, realize that while one user may need everything your app does, others just need to know the results. Make sure your app links to the app others work in the most. If others need the data from your app to work in Slack, then offer a single-click integration to send the data from your app to Slack.
Simple vs. feature-laden. Keep the interface as decluttered as possible, so it’s easy for users to find what they need. Visual clarity poses a challenge for feature-laden platforms, so design with a bias toward simplicity. And remember, there will be light users who don’t want to have to figure out, once again, how to run a report. You still need all the features for those power-user admins, but you must also prioritize the light user’s experience.
Mobile. The more people who adopt your app, the more mobile users you’ll have. While you don’t have to design to be mobile-first, you can offer a simplified version of your desktop platform, keeping all the features someone on the go will need when they’re away from their office.
Easy to share. People work on teams for the most part and shared apps help complete shared work. Make it easy for your power user to evangelize and share your product within the organization with a one-click invitation.
Real-time issue resolution. Digital is fast, and users expect to solve any problems encountered in real time. Offer help right in the product through a chat function. No one minds AI if it resolves their issue — they just want it handled now.
Easy to review. Purchase decisions today reflect the power of the end-user. Decisions are made based on word of mouth and 3rd party review sites, so make it easy for your promoters to evangelize for you. Use in-app surveys to identify your happiest customers and then automate the review to link to AppStore or G2 once the survey is completed.
Seamless upgrade to paid. The freemium or trial offer will demonstrate value. When more functionality is required, make it an easy click to the premium product version.
Customer feedback. Build improvement and growth into your product by asking for feedback right in the platform and mobile app. Your buyers and end-users expect you to be optimizing your product, so make it easy for end-users to give feedback in the moment through simple NPS, CSAT, and CES micro-surveys.
How Has the B2B Customer Experience Evolved?
The evolution of B2B customer experience has been influenced by various factors, including advancements in technology, changes in buyer behavior, and shifts in business practices. Here are some stats that reflect some of the ways CX has changed for B2B brands today.
B2B companies that offer a customized eCommerce experience tend to outsell their competitors by 30%.
Mobile ordering in the B2B sector has surged by 250% since the COVID-19 pandemic, highlighting a notable transformation in digital practices within the realm of professional procurement and purchasing.
100% of B2B customers want self-service options for at least some parts of the buying process.
Buyers increasingly look to B2B companies as thought leaders and strategic partners, with 84% of B2B executives saying it is very important to lean into their new positions as trusted thought leaders.
52% of B2B buyers say the buying cycle for new purchases has gotten longer, proving that the B2B customer experience journey is more non-linear than ever.
B2B CX continues to change as companies adapt to new technologies and expectations. Successful B2B companies recognize the importance of staying agile, customer-centric, and responsive to emerging trends in order to maintain a competitive edge in the marketplace.
How to Improve the B2B Customer Experience: Best Practices
Improving the B2B customer experience involves a combination of strategic planning, effective communication, and a customer-centric approach. Here are some best practices to improve B2B CX.
Create an Integrated CX Approach
In the B2B world, customers use a wide variety of channels to interact with your brand. However, the data most companies collect stays in those channels, and it is analyzed independently of the broader experience.
To improve customer experience, your organization must adopt an integrated CX approach so that you can unlock valuable insights from all sources of customer data, then take action and drive measurable outcomes for your customers. This means collecting and connecting CX data from every touchpoint and channel for a complete view of the B2B customer journey, then navigating and interpreting that data to understand where to focus for the highest impact for your customer and for your business.
Collect Customer Feedback
Invest time in understanding the unique needs and pain points of your B2B customers. Conduct surveys, interviews, and regular feedback sessions to gather insights into their challenges and expectations.
Using information from unsolicited feedback, companies can gain valuable insights into how to improve their brand, products, services, and overall customer experience. B2B companies that are able to monitor and manage customer feedback also often have a more complete understanding of their customers, and can easily measure customer satisfaction and loyalty.
Common sources of customer feedback include:
Customer feedback surveys
Comment cards
Emails and phone calls
Focus group discussions and roundtables
Online reviews and ratings
Social media comments
Customer interviews and business reviews
User experience and usability tests
The most successful companies listen to and act on feedback in order to understand their customers better and deliver improved customer experiences. The challenge is to move beyond simply collecting data. A number of successful B2B brands today deploy Voice of the Customer programs to ensure they are really hearing their customers and extracting rich, meaningful insights from their feedback.
Map the B2B Customer Journey
A customer journey map is a visualization of each step your customers take — from the moment they encounter your brand to when they make a purchase and how they react afterward. Using a customer journey map can help your company continuously identify and anticipate the needs, motivations, and actions of your customers.
Through customer journey mapping, your organization can construct customers’ decision-making scenarios — and better understand the factors that influence purchase decisions and move sales cycles forward. This then aids your efforts to deliver improved customer experiences, drive more sales, acquire and retain more customers, and improve your business processes.
Offer More Personalized Experiences
In a world where consumers are bombarded by hundreds or even thousands of marketing and sales messages every day, personalization holds the key to standing out and cutting through the noise.
There’s a wide range of personalization tactics, both online and offline, that you can apply to improve the B2B buyer’s customer experience — from customer-specific content and personalized packaging to responsive website design and insight into customers’ order histories.
By increasing personalization in interactions, touchpoints, and engagements, you give customers a sense of identity and can more easily attract their attention that way.
Personalization also serves as a sign of respect for customers’ loyalty and business. It signals that your business is interested in strengthening the relationship by providing relevant suggestions, better service, and more informed support. This is why IBM assigns specialists to help its cloud storage suite customers get set up: not only does it help customers maximize the value of IBM’s products and services; it also drives personalized experiences that resonate with individual organizations.
Ensure Timely Response, Delivery, and Resolution
Great customer service is a major component of great CX. This means ensuring timely response, delivery, and resolution of issues; it means attending to customer needs and solving their specific problems. It’s important to provide responsive customer service through various channels, including email, phone, and live chat. Also, be sure you work closely with customers to address challenges, gather their input, and implement solutions that align with their business objectives.
Maintaining open and proactive communication throughout the customer journey is also a critical aspect of B2B CX management. Keep customers informed about product updates, new features, and relevant industry trends. Clearly communicate pricing, terms, and conditions. Through proactive communication and transparency, you can inspire brand trust and establish a solid foundation for long-term relationships.
Provide Self-Service Options
With research showing that B2B customers want self-service options for parts of the buying process, it’s essential for your organization to explore and invest in self-service technologies.
Just as a person shopping online has a wide range of products and services to choose from, your B2B buyers should also be able to access content, support, scheduling, and purchasing independently, without direct assistance from a representative.
Examples of self-service tools that B2B businesses can use include:
Customer portals for account management, order history, and invoice tracking
E-commerce platforms for product catalog, online ordering, secure payment processing
Knowledge bases and customer support portals for troubleshooting guides, FAQs, ticket submission, case tracking, and self-help resources
Feedback and survey tools for sharing input on customers’ experiences and gathering insights for improvement
Collaboration tools for document sharing, project management, and communication channels
Chatbots for responses to common queries, product recommendations, and product and service guides
Offering self-service tools and options can directly impact customer satisfaction, as well as contribute to operational efficiency, allowing your team to focus on more strategic aspects of your relationship with clients.
Digitize the B2B Journey
B2B buyers demand tools that simplify and streamline the entire buying process — from research and planning, through engagement, to the post-sales phase. This makes it critical to invest in technology that will better engage consumers and make every part of the customer journey pain-free.
You can implement user-friendly online platforms, intuitive interfaces, and streamlined procedures for ordering, invoicing, and payment. Another good example is utilizing digital “track and trace” systems so that clients can see the status of their orders and actions in real time. As you digitize the B2B journey, ensure robust data security measures to instill trust in your B2B customers and help them build confidence in your partnership.
Achieve B2B Customer Experience Excellence with InMoment
Managing the B2B customer experience is not just about individual transactions but about building and sustaining successful, long-term relationships with your customers. With InMoment, you can integrate customer signals across all relevant channels, gain deeper insights into the B2B buyer’s journeys and experiences, and take informed action with the world’s most recommended CX platform.
References
SmartKarrot. “75 Must-Know Customer Experience Statistics to Move Your Business Forward” (https://www.smartkarrot.com/resources/blog/customer-experience-statistics/). Access 1/3/2024.
TrustRadius. “022 B2B Buying Disconnect: The Age of the Self-Serve Buyer” (https://solutions.trustradius.com/vendor-blog/2022-b2b-buying-disconnect-the-age-of-the-self-serve-buyer). Access 1/3/2024.
Edelman. “How B2B Companies are Adapting Customer Engagement Strategies During COVID” (https://www.edelman.com/expertise/business-marketing/how-b2b-companies-are-adapting-covid). Access 1/3/2024.
Korn Ferry. “The 2021 Buyer Preferences Study: Reconnecting with Buyers” (https://www.kornferry.com/content/dam/kornferry-v2/featured-topics/pdf/2021-Buyer-Preferences-Study.pdf). Access 1/3/2024.
Unlock Expert Guidance on Today’s CX Challenges & Opportunities
Whether you’re struggling with limited resources, data fragmentation, or evolving customer expectations, this guide offers the expert advice you need to elevate your CX strategy. Download now to discover how to transform these challenges into growth opportunities.
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All types of businesses leverage customer surveys, and they’re as important for small, growing businesses as they are for established corporations. When you’re creating a customer survey, whether it’s for the first time, or something you do each year, it’s helpful to understand what to expect. What is a good survey response rate? What are best practices for customer surveys? What is the competition encountering?
As businesses continue to evolve their customer listening channels as a part of their Integrated CX strategy, one source of feedback will always be around – customer surveys.
All types of businesses leverage customer surveys, and they’re as important for small, growing businesses as they are for established corporations. When you’re creating a customer survey, whether it’s for the first time, or something you do each year, it’s helpful to understand what to expect. What is a good survey response rate? What are best practices for customer surveys? What is the competition encountering?
We’ve collected customer survey statistics to help you understand the customer survey landscape. Whether you send out a standard survey via email or leverage the Net Promoter Score question in-app, knowing some statistics and trends can help you ensure that you get adequate feedback that helps build your business.
Customer Survey Statistics You Need to Know About…
Hearing from Customers
The average business hears from 4% of its dissatisfied customers. (Source: “Understanding Customers” by Ruby Newell-Legner via Help Scout)
For every customer who complains to a business, 26 other customers don’t voice their feelings. (Source: White House Office of Consumer Affairs via Help Scout)
95% of customers share bad experiences with others. (Source: Zendesk)
Asking for Feedback via Customer Surveys Statistics
Monday is the best day to get the highest amount of complete email surveys for B2B businesses. (Source: CheckMarket).
For B2C companies, there is not a best day to send surveys: Tuesdays, Wednesdays and Fridays all lead to a relative high response rates and Thursdays and Sundays can better be avoided. (Source: CheckMarket and SurveyMonkey)
The average response rate for email surveys is roughly 24.8%, according to a calculation by FluidSurveys.
The average response rate for telephone surveys are in the 8-12% range (Source: FluidSurveys)
Response rates can soar past85% when the respondent population is motivated and the survey is well-executed. (Source: People Pulse)
Response rates can also fall below 2% when the respondent population is less-targeted, when contact information is unreliable, or where there is less incentive or little motivation to respond. (Source: People Pulse)
Best practice is to keep your survey as short as possible. Data suggests that if a respondent begins answering a survey, there is a sharp increase in drop-off rate that occurs with each additional question up to 15 questions. (Source: SurveyMonkey)
Responding to Feedback Statistics
It takes 12 positive experiences to make up for one unresolved negative experience. (Source: “Understanding Customers” by Ruby Newell-Legner via Help Scout)
Resolve a complaint in the customer’s favor and they will do business with you again 70% of the time. (Source: Lee Resources)
Net Promoter Score (NPS) Survey Statistics & Benchmarks
Entelo saw 2x response rate using in-app NPS surveys versus email. For example, when Entelo, a recruiting software, first began to use in-app NPS survey, their response rate quickly jumped from around 24 percent to around 60 percent, before leveling off at about 50 percent. (Source: InMoment)
The top 10 NPS leaders (those with the highest NPS scores) are USAA Insurance (80%), USAA Banking (78%), Costco (78%), Apple – Laptop (76%), Dillards (75%), and Nordstrom (75%). (Source: Customer Guru)
Fortune 500 companies such as Delta Air Lines, General Motors, Zappos, Lego, and Procter & Gamble all use NPS to help gauge customer happiness. (Source: Net Promoter System)
Thinking Beyond Customer Surveys
While surveys remain a great way to learn about the experiences you are providing your customers, you are more than likely only hearing from 10% of them. To understand the other 90% companies are moving to a more integrated feedback signal approach to their customer listening. With InMoment’s Integrated CX, companies are now able to easily combine, analyze and act on multiple signals (i.e. surveys, phone/chat transcriptions, social, CRM notes, etc..) to improve CX.
WHITE PAPER
The Art and Science of Email Survey Invitations
The problem with your survey response rate may not be the survey itself. In fact, most non-responses are due to people not participating in the survey at all. Hence the question: what is in an invitation?
If you are looking for technical and non-technical solutions to create the ultimate e-mail survey invitation, look no further. Take a step towards higher response rates by downloading the document below!
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It can be argued that the customer experience is more important in retail than any other industry. With 93% of consumers reading reviews before making a purchase, and 58% of consumers being willing to drive further or pay more for a product with good reviews, a good customer experience and brand reputation management have never been more critical than it is today.
The retail customer experience is also a complex one. It encompasses the in-store experience just as much as it does the online experience. In order to master the retail customer experience, you first need to understand the whats, the whys, and the hows.
What is the Retail Customer Experience?
At its core, the retail customer experience encompasses every touchpoint a customer has with a brand, from the first interaction to post-purchase engagement. But, it goes beyond transactions, it also encompasses emotions, perceptions, and overall satisfaction with the brand from the view of the customer.
Why is the Retail Customer Experience Important
The retail customer experience has become increasingly significant in the success and sustainability of any business operating in the modern marketplace. Consumers can quickly become lifetime customers and brand advocates when they have continuous positive experiences with a brand. But, there are more benefits to a well-crafted retail customer experience that go beyond customer loyalty. Let’s examine a few:
1. Revenue Growth
Satisfied customers are more inclined to spend more and make repeat purchases. When the retail customer experience exceeds expectations, customers feel a connection with the brand, leading to increased spending and higher lifetime value. Positive experiences contribute directly to revenue growth as customers become more engaged and willing to invest in the brand.
2. Competitive Edge
In a crowded marketplace where products and services may seem similar, the retail customer experience becomes a powerful differentiator. Businesses that prioritize delivering exceptional customer experiences gain a competitive edge over their counterparts. Customers are more likely to choose a brand that provides not only quality products but also a memorable and positive overall experience.
3. Word-of-Mouth Marketing
Satisfied customers become brand ambassadors, sharing their positive experiences through word-of-mouth marketing. Recommendations from friends, family, or online reviews play a significant role in attracting new customers. A brand that consistently delivers excellent retail customer experiences is more likely to benefit from positive word-of-mouth marketing, expanding its customer base organically.
How to Improve the Retail Customer Experience
In order to improve your customer experience in retail stores, you will need to focus on two main types of experiences: in-store and digital. These two types of experiences are equally important in cementing customer loyalty and improving the overall experience that is associated with your brand.
Improving the Digital Retail Experience
Providing an exceptional online retail experience is crucial for capturing and retaining customers. Here are strategies to enhance the digital customer experience:
1. User-Friendly Website
Design and optimize your website for ease of use. Ensure intuitive navigation, quick loading times, and a seamless checkout process. A clutter-free and visually appealing layout enhances user experience and encourages visitors to explore and make purchases.
2. Personalization
Leverage data analytics and customer insights to personalize the online shopping experience. Implement personalized product recommendations, targeted promotions, and customized content based on individual preferences and past interactions. Personalization creates a more engaging and relevant experience for users.
3. Responsive Customer Support
Offer responsive and accessible customer support across various channels, including live chat, email, and social media. Providing real-time assistance and resolving issues promptly contributes to a positive online experience. Implement chatbots for immediate responses and streamline customer communication.
4. Mobile Optimization
Given the prevalence of mobile device usage, optimize your website for mobile responsiveness. Ensure that the online shopping experience is seamless and visually appealing on smartphones and tablets. Mobile optimization is essential for capturing the growing number of consumers who prefer to shop on mobile devices.
5. Secure and Transparent Transactions
Instill confidence in online shoppers by prioritizing the security of online transactions. Clearly communicate your website’s security measures, use secure payment gateways, and provide transparent information about shipping costs and return policies. A secure and transparent transaction process builds trust with customers.
Enhancing the In-Store Retail Customer Experience
While digital experiences are vital, the in-store customer experience remains a cornerstone of retail success. Here are strategies to enhance the in-store retail experience:
1. Store Layout and Design
Create an inviting and well-organized store layout that aligns with your brand identity. Consider factors like product placement, aisle navigation, and overall ambiance. An aesthetically pleasing and easy-to-navigate store layout contributes to a positive in-store experience.
2. Staff Training
Invest in comprehensive training programs for your staff to ensure they provide excellent customer service. Equip them with product knowledge, effective communication skills, and the ability to address customer queries. A well-trained and motivated staff enhances the overall in-store experience for customers.
3. In-Store Events and Promotions
Organize in-store events, promotions, or exclusive sales to create a sense of excitement and urgency. These initiatives not only attract foot traffic but also provide customers with a memorable and enjoyable shopping experience. Consider incorporating interactive elements or entertainment to make the events more engaging.
4. Efficient Checkout Process
Streamline the checkout process to minimize wait times and enhance convenience. Implement technologies like self-checkout kiosks or mobile payment options to offer customers faster and more efficient ways to complete their purchases. An efficient checkout process contributes to overall customer satisfaction.
5. Customer Feedback Stations
Place feedback stations within the store to encourage customers to share their opinions and suggestions. Use this feedback to make informed improvements and adjustments. Actively seeking and acting upon customer feedback demonstrates a commitment to continuously enhancing the in-store experience.
Using InMoment’s predictive customer analytics tool, you get automated insights from unstructured feedback that help you notice what needs to be improved, or what is performing well.
By focusing on both the digital and in-store aspects of the retail customer experience, businesses can create a cohesive and comprehensive strategy that caters to the diverse needs and preferences of their customer base. Integrating these strategies ensures a well-rounded approach that fosters customer satisfaction and loyalty across various channels.
How to Measure Customer Experience in Retail
Effectively measuring customer experience in retail is essential for identifying strengths, areas for improvement, and overall customer satisfaction. There are three common customer experience metrics that most companies will use to measure customer experience.
1. Net Promoter Score (NPS)
What it is: The Net Promoter Score (NPS) is a widely used metric that assesses customer loyalty by asking a simple question: “How likely are you to recommend our brand to others?”
How to measure: Customers respond on a scale from 0 to 10, categorizing them into promoters (9-10), passives (7-8), and detractors (0-6). The NPS is calculated by subtracting the percentage of detractors from the percentage of promoters.
Why it matters: NPS provides a direct indicator of customer satisfaction and loyalty. Higher NPS scores indicate a greater likelihood of customers promoting the brand.
2. Customer Satisfaction (CSAT) Score
What it is: CSAT measures overall customer satisfaction by asking customers to rate their experience on a numerical scale.
How to measure: Typically, customers respond on a scale of 1 to 5 or 1 to 10, indicating their level of satisfaction. The average score represents the CSAT score.
Why it matters: CSAT offers a straightforward way to assess customer satisfaction after specific interactions or transactions. Regularly tracking CSAT scores helps in identifying trends and areas for improvement.
3. Customer Effort Score (CES)
What it is: CES measures the ease with which customers can achieve their goals or resolve issues.
How to measure: Customers rate their agreement with statements like “The company made it easy for me to resolve my issue” on a scale. The average score represents the CES.
Why it matters: Reducing customer effort enhances satisfaction and loyalty. A lower CES indicates a more straightforward and positive customer experience.
With InMoment’s reporting platform, your CX program performance can become quickly and easily digestible. We allow advanced data filters that allow you to segment insights for the audience that matters most to you. And, with our Reports and Dashboards Builder, you can create reports tailored to your business.
Retail Customer Experience Trends
As a retailer, you know that the vast majority of the insights you need to shape your merchandising, product development, e-commerce, and overall business strategy are on review sites, social media, from your employees, and beyond. In order to stay ahead of your customers, you need to be utilizing all of these channels to the best of your ability. But, in an effort to help you do so, our strategic insights team has conducted independent research to uncover two major trends in retail customer experience.
Trend #1: Consumers Will No Longer Settle for Convenience
Convenience-based experiences such as self-checkout, buy online and pick up in-store, and flexible payment options are no longer seen as above and beyond features, they have now become the standard. That doesn’t diminish the importance of these features. As a matter of fact, without these features, consumers may not shop with you at all.
In order to take your retail experiences to the next level, you need to embrace the power of social media and influencer marketing. In our research, we found that over 60% of retailers who had a strong TikTok and Instagram presence noted higher “purchase intent” sentiments.
Trend #2: Consumers Now Expect Hybrid Experiences
There is no longer a difference between your in-store customers and your online customers. One in three consumers now expect a blend of both in order to enjoy a seamless, hybrid experience. These hybrid experiences can take many different forms, but we asked consumers to rank the hybrid experiences they expect from retail brands:
In our research, it became clear that consumers were excited at the prospect of using their mobile devices as a part of their in-store experience in a variety of ways:
50% of consumers said they’d like to leverage their phone/an app to view product ratings and reviews while browsing in store
50% of consumers said they’d also like to be able to view product options (such as colors or sizes) by scanning a product with their smartphone in store
33% of consumers said they’d like to view recommended product pairings via an app/mobile site while in store
25% of consumers said they’d like to view social media product reviews/mentions while shopping at a brick-and-mortar location
Essentially, consumers want to bring their favorite digital experience elements into the physical store with them. Whether it’s seeing what other buyers had to say in the moment, getting product pairing recommendations, or other similar options, your consumers are looking to be wowed with personalization while in store. It’s time to start delivering!
Retail Customer Experience Examples
One InMoment client that consistently delivers best-in-class retail experiences is FootLocker. FootLocker was able to utilize the XI Platform to get all of their Voice of Customer and operational data into one, easy to digest platform. As a result, they achieved:
Increased OSAT score
Improved issue resolution
Added social media capabilities to their program
Take Your Retail Customer Experience to the Next Level
Are you curious to see how InMoment can help you improve your retail customer experience? Whether it’s our AI capabilities, customer reporting, or contact center software, we have just the solution for you. Schedule a demo to see for yourself today!
References
Trustmary. Online Reviews: Statistics That Will Blow Your Mind [2023]. (https://trustmary.com/reviews/online-reviews-statistics-that-will-blow-your-mind/). Access 1/3/2024.
Unlock Expert Guidance on Today’s CX Challenges & Opportunities
Whether you’re struggling with limited resources, data fragmentation, or evolving customer expectations, this guide offers the expert advice you need to elevate your CX strategy. Download now to discover how to transform these challenges into growth opportunities.
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Get a first look at the trends that matter most and how they can impact your customer relationships, drive growth, and strengthen your overall strategy.
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If you received an invitation to take a survey, you would probably be more likely to actually participate if the topic of the survey interested you. That’s the heart of voluntary response sampling. Like all other methods of sampling, voluntary surveys have their pros and cons. It’s one of the easiest ways to sample quickly and get responses, but it can also result in voluntary response bias.
What is Voluntary Response Bias?
A voluntary response is when someone volunteers to be a part of your sample. In doing so, you’re allowing them to skew your data and you don’t get results that are representative of the whole population. Thus, you get biased feedback.
Voluntary response bias refers to how allowing your sample to self-select skews your data, and you don’t actually get results that are representative of your whole population. Voluntary response bias isn’t always inherently bad; it’s not considered the worst of the biases that could arise in your sampling. But it can lead to more extreme results than would actually be true for your population as a whole.
Why Is Voluntary Response Sampling Biased?
When you create a survey, you want to get results that are representative of your population, so you can make the right decisions based on the data. If you’re allowing your sample to self-select, you’re not getting data that shows your entire population. You’re only getting data that reflects your sample. That leaves you with results that aren’t generalizable, and generalizing them anyway is where bias becomes a real problem.
Voluntary response also opens your survey up to the possibility of favoring more extreme results than your population actually experiences. Think about it this way: respondents are more likely to volunteer for a survey if they’re passionate about the topic. The passionate responses can skew your results. You’ll have the customers who loved your product the most (or had a terrible experience) responding instead of your average customer. That could lead to bias problems. You could end up making decisions on products and services that are slightly skewed by voluntary response bias.
What Is an Example of Voluntary Response Bias?
To illustrate voluntary response bias, let’s consider a scenario involving a survey on customer satisfaction with an online retail platform.
Survey Design:
Imagine a company conducts an online survey to gather feedback on customer satisfaction with its e-commerce platform. The survey is distributed through email newsletters and social media, allowing customers to voluntarily respond to questions about their shopping experience.
Voluntary Response Bias in Action:
Customers who had an exceptionally positive or negative experience with the online retail platform may be more motivated to participate in the survey.
Customers with neutral or average experiences may be less inclined to take the time to provide feedback, potentially leading to a skewed representation of customer satisfaction.
Resulting Bias:
The survey results may disproportionately reflect the views of customers who had either highly positive or negative experiences.
The findings might inaccurately suggest that the majority of customers either love or strongly dislike the platform, creating a potential misrepresentation of overall customer sentiment.
Impact on Generalization:
If the company relies solely on these biased survey results, they may make decisions based on an exaggerated understanding of customer satisfaction, potentially overlooking the needs and opinions of the more moderate majority.
This example emphasizes how voluntary response bias can manifest in retail surveys when individuals with extreme opinions are more likely to participate, leading to a sample that may not accurately represent the broader spectrum of customer experiences. Recognizing and addressing such biases is crucial for obtaining a more balanced and reliable understanding of customer sentiments in the retail sector.
How to Avoid Voluntary Response Bias
Voluntary response bias can significantly impact the quality of your research results, and potentially lead to skewed and inaccurate conclusions. There are several steps researchers can take to minimize or avoid voluntary response bias and enhance the overall quality of their research.
1. Use Random Sampling Techniques
Employing random sampling methods such as systematic sampling ensures that every member of the population has an equal chance of being selected. This reduces the likelihood of biased participation and contributes to a more representative sample.
2. Ensure Anonymity and Confidentiality
Assure participants of the anonymity and confidentiality of their responses. When individuals feel that their privacy is protected, they may be more willing to participate, reducing concerns about potential repercussions and encouraging a broader range of participants.
3. Implement Post-Stratification Techniques
After data collection, post-stratification techniques can be used to adjust the weights of different groups to match the known population distribution. This helps correct any imbalances that may have occurred during the voluntary response process.
4. Pilot Test Surveys
Before launching a full-scale survey, conduct pilot tests to identify and address any issues with clarity, wording, or potential biases in the questions. Pilot testing helps refine the survey instrument and improve the quality of data collected.
5. Be Transparent About Study Objectives
Clearly communicate the objectives and goals of the research to participants. Providing transparency can attract individuals who are genuinely interested in the topic, rather than those with extreme opinions or biases, leading to a more balanced representation.
By incorporating these strategies into the research design, researchers can minimize the impact of voluntary response bias and enhance the reliability and validity of their study findings. It’s essential to carefully consider the potential biases inherent in voluntary response sampling and take proactive steps to address them throughout the research process.
Advantages of Voluntary Response Sampling
Voluntary response sampling has its own set of advantages in certain situations. Randomly selecting a population and getting those chosen to participate in the survey can be difficult, time-consuming, and expensive. Voluntary response bias can eliminate that. You aren’t spending time tracking down participants and designing your survey since your sample is just those who are already willing to participate in your survey. Here are some key advantages to consider:
1. Cost-Effective
Voluntary response sampling is often a cost-effective method as it involves minimal resources to collect data. Participants voluntarily choose to respond, reducing the need for extensive outreach efforts or financial investment.
2. Quick Data Collection
The process of collecting data through voluntary responses is generally rapid. Since individuals willingly participate, there is no need for lengthy recruitment processes or follow-ups, making it a swift method for gathering information.
3. Ease of Implementation
Implementing voluntary response sampling is relatively simple. Researchers can easily distribute surveys or questionnaires through online platforms, social media, or other accessible channels, allowing for a quick and straightforward data collection process.
4. Wide Geographic Reach
Voluntary response sampling often allows for a broad geographical reach. Through online surveys or other digital means, researchers can attract participants from diverse locations, contributing to a more extensive and varied dataset.
5. Potential for Unbiased Insights
In some cases, voluntary response sampling may provide insights into niche or underrepresented groups. Participants who choose to respond may have a genuine interest in the topic, leading to a diverse set of perspectives that might not be captured through other sampling methods.
Disadvantages of Voluntary Response Sampling
Voluntary response sampling has some very obvious disadvantages. Using voluntary responses can allow bias to creep in on the results and skew data. Voluntary response also can introduce undercoverage bias. Your population could potentially be a complex and diverse group of people. When you use voluntary responses, only those who are inclined to respond are represented in the results. While voluntary response sampling has its advantages, it is crucial to be aware of its limitations and potential drawbacks. Here are some key disadvantages to keep in mind when deciding to participate in voluntary response sampling:
1. Selection Bias
One of the most significant challenges with voluntary response sampling is the potential for selection bias. Individuals who choose to participate may differ systematically from those who do not, leading to a skewed representation of the population and compromising the generalizability of the findings.
2. Lack of Randomization
Voluntary response sampling lacks the randomization inherent in more rigorous sampling methods. This absence of random selection can contribute to a non-representative sample, making it difficult to draw accurate conclusions about the broader population.
3. Limited Control Over Sample Composition
Researchers have limited control over the composition of the sample in voluntary response sampling. Certain demographic groups may be overrepresented or underrepresented, impacting the reliability of the collected data and potentially introducing confounding variables.
4. Potential for Misleading Conclusions
Participants in voluntary response surveys may have strong opinions or experiences related to the subject matter, leading to biased results. This can result in findings that are not reflective of the overall population and may lead to misleading conclusions.
5. Difficulty in Establishing Causation
Establishing causal relationships is challenging with voluntary response sampling, as the self-selected nature of participants makes it difficult to determine whether observed correlations are causal or influenced by other factors.
When utilizing voluntary response sampling, researchers should be aware of these disadvantages and carefully consider the appropriateness of this method for their specific research goals and the nature of the population under study.
Collecting Responses and Feedback
Voluntary response bias is a real risk researchers face when using voluntary response sampling. But considering what voluntary response bias does to a survey also opens up a discussion of the larger challenges with surveying. Choosing methods and creating accurate, simple, and powerful surveys is important, and shouldn’t be taken lightly. With InMoment, you’ll have access to best-in-class survey tools that will help you collect, analyze, and act on customer feedback. Schedule a demo today to see it for yourself!
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