5 Ways Retail Banks Can Leverage Customer Data Effectively

Collecting data with no way to use it is like learning to drive without a car; it just doesn’t make sense. For retail banks, and most organizations, collecting data is only half the battle in the world of customer experience. Whether it be transactional surveys, online reviews, or a market research report about your customers, the data you collect needs to not just be analyzed, it needs to serve as a road map of future business decisions.

Using customer data to influence your business decisions will lead to a more streamlined, profitable banking organization that actively engages customers. Don’t just take our word for it, research shows that companies who adopt data-driven marketing are six times more likely to be profitable year-over-year. 

Every day, your customers produce data across a vast amount of touchpoints, whether that’s on your banking app, in your call center, or across any of your other channels. That data is there to help you understand their behavior, their needs, and even predict their future behavior. But, in order to do this, that data has to be in a centralized platform in order to be readily available for evaluation and future strategic planning. 

Once you have this data at your disposal, there are a number of ways you can use it to improve experiences for your banking customers. With so many ways to use customer data, we have picked 5 strategies for retail banks looking to leverage customer data.

5 Strategies for Retail Banks to Get the Most Out of Their Customer Data

Strategy #1: Capture Meaningful Data

You need to capture data that is meaningful to your bank, and that is related to the current objectives you have in mind. If you run a local credit union, there’s no point in asking your members what their favorite flavor of ice cream is. This is a more extreme example, but you get what we’re trying to say. If your goal is to improve the digital experience, you don’t want to ask about the in-branch experience.

By designing an experience program with your end goals in mind, you’ll know what data you need to collect to achieve those goals. Knowing what data you need to collect will outline what questions you need to be asking your customers in order to get that data, and consequently, achieve those goals you originally planned. 

Retail banks already have access to critical customer data. Age, gender, geographic location, and spending habits are data points that can already be leveraged. But, mixing these data points with structured feedback via social media or surveys, as well as meaningful data captured in order to achieve a desired goal, will allow retail banks to get a holistic view of their customer and their customer experience. 

Wondering how you can refine your data-gathering strategy to leverage the right listening methods at the right time? Check out this quick article.

Strategy #2: Master Omnichannel Experiences

Retail banking customers today demand consistent, intuitive omnichannel experiences that are personalized and accessible anywhere. However, most retail banks fail to deliver this and are unable to monetize customer data through their products and services. 

Research shows that online banking has increased by 23% and mobile banking has increased by 30%. This means that customers are stepping away from the teller, and toward the chat assistant on your bank’s website or app. Although the medium is changing, customers still expect the same experience that they received inside a branch to be consistent with the one they receive online. 

By mastering omnichannel experiences, you will set yourself apart from the competition, and keep your customers coming back time and time again, whether they are on their phone, computer, or visiting you in person. 

Strategy #3: Break Down Data Silos

Breaking down data silos and combining data from multiple sources across a banking organization can increase efficiency and control in a fast-changing and demanding environment. 

Retail banks receive data from multiple sources and departments. If these various pathways of customer data do not converge on a central location, retail banks risk having a distorted view of the customer experience and risk an increase in customer churn. 

By having all of your customer data in one place, you can easily access multiple data points from different locations across your organization. This will provide you with a 360-degree view of a customer’s activity and engagement with the bank and will allow you to make well-informed decisions with your customer base in mind. 

Strategy #4: Collect Data Across the Entire Customer Journey

Retail banks can achieve their goals by tracking the customer journey, and finding areas of improvement. When doing this, it is important to track the entire customer journey. While a traditional bank may track the customer journey as opening an account, transactions, and borrowing, you should be tracking the steps it took for a customer to open an account, such as their first visit to your website. Where other banks track transactions, you should track specific spending habits in order to know your customer and personalize their experience. 

Retail banks must keep the customers at the heart of the journey by tracking key moments in their experiences and improve these moments in the customer journey.

Strategy #5: Analyze Behavior and Emotions

Throughout the data collection process, it is important to remember that your customers cannot be reduced to just a mix of data points. Your customers have emotions, and they make emotional decisions. Without cultivating positive emotions in customers, banks risk being forgotten. You need to know your customers behavior, so that you know where to focus to make the biggest impact on them. 

According to J.D. Power, Customers in the retail banking industry are not happy with the level of personalization they experience in their transactions—but the customer feedback you collect could help change all that! Designing experiences to create positive emotions increases customer lifetime value and reduces risk of customer churn. Learn how retail banking giant Virgin Money analyzed customer emotions across the journey to create specific improvements and positive emotions in this video!

Leveraging Your Customer Data

Your customer data should be one of your biggest assets. It can be used to solve problems, and make decisions with your customers’ needs in mind. But remember, data alone cannot make those changes—you need to make sure you’re leveraging the right technology, taking the advice of experts, and taking action based on the insights you derive from that data. Put in place a framework that ensures that type of continuous experience improvement, and you are sure to attract new customers, retain old ones, and, ultimately, make your customer experience program a key part of your retail bank’s success!

For more information about how retail banks can leverage customer data effectively, checkout this white paper on how to stand out in your industry!

3 Areas of Customer Experience Where Human Expertise Is Absolutely Vital

Customer experience (CX) measurement has become a priority for most large organizations. Systematically gathering and analyzing data from online surveys and other sources such as product reviews, customer complaints, etc., is viewed as an imperative. And for good reason.  21st century business is won and lost based on who can deliver the best customer experience.

However, as we become more comfortable and rely more heavily on intelligent systems to collect and interpret data for us, there is still an opportunity for a human element to play an important role in customer experience programs.  

This is a belief I’m incredibly passionate about. My name is Len Ferman and I am a senior consultant at InMoment. In 2019, I published a college textbook, “Business Creativity and Innovation: Perspectives and Best Practices”, which is now being used at several universities including in my classes as an adjunct professor at the University of North Florida. In my role at InMoment, I work with brands to generate and evaluate ideas to attract new customers, delight existing customers and identify strategic initiatives.

In this article, I’ll discuss three areas in which human expertise can make a valuable contribution. Let’s dive in!

3 Areas Where Human Expertise Makes a Valuable Contribution to Customer Experience

  • Qualitative Research
  • Customer Journey Mapping
  • Ideation to Improve the Customer Experience

Qualitative Research

In 2021, the Wall Street Journal ran an article titled, “Why Companies Shouldn’t Give Up on Focus Groups.” The premise was that in this era in which big data is running the show, taking the time to listen to live customers can still be hugely beneficial.

Qualitative research can take on many forms including live or online focus groups, in person interviews or phone interviews. The distinguishing feature of qualitative research is that a trained interviewer is interacting live with an engaged respondent. 

As a qualitative researcher with 30 years of experience, I consistently find that there is no substitute for gaining a complete understanding of a customer’s story than by talking to customers live, whether it’s in person, on the phone, or via video conference.    

The value that qualitative research brings to a customer experience program is in being able to definitively probe with customers about why they respond and behave the way they do. Only in live, qualitative research can you fully leverage the “5 Why’s” technique to drill down to the root cause of a customer’s behavior.

The “5 Why’s” technique was developed by Sakachi Toyoda, the founder of the Toyota Industries in Japan. The technique is a simple but powerful method of questioning. For any problem that you hear the customer describe, you ask, “why?” And then when you have the answer, you ask, “why?” again.  The idea is that by asking “why?” five times you are likely to drill down to the root cause of a problem. This method can only be effectively deployed in live, qualitative research.

Customer Journey Mapping

Understanding the experience a customer has, from their perspective, across their end-to-end journey with your company, products, services or processes is what customer journey mapping is all about. Customer journey maps can be a simple yet powerful tool to enable your employees to empathize with and fully understand the customer experience.

The best customer journey maps are produced when there is a human element involved in the core data collection and final map development.  

Qualitative research is necessary for the foundation of a customer journey map since it is necessary to hear customers describe their journey. And the creative design of the final map to adequately portray and communicate a visual depiction of the customer journey remains a uniquely human endeavor.

Well developed customer journey maps have multiple benefits for a customer experience program including stronger customer experience survey design and a common understanding of the customer journey among all employees. One particular benefit is the ability of customer journey mapping to help identify the key moments of truth a customer has in the journey.

Ideation to Improve the Customer Experience

Ideation to generate and evaluate ideas to improve the customer experience is a process that every organization can benefit from. Experienced ideation facilitators can leverage processes that guide a team through creative exercises. 

These creative exercises use data generated in customer experience programs as a starting point. And they also tap into the expertise of your own employees to generate ideas that leverage the core competencies of the company. A second set of evaluative exercises provides the team with the discipline to narrow down and select the optimal ideas for development.

Leveraging Human Expertise

These three areas, which all require human expertise, can enhance your overall customer experience program and provide you with an advantage over your competition.

At InMoment, our consultants are available to perform these three types of human-led services. Contact your client success director to inquire about how you can engage with InMoment for qualitative research, customer journey mapping, or ideation to improve the customer experience.

Closing the Outer Loop with the Six Sigma Methodology

Customer feedback is critical for helping your customer service agents tackle problems—whether closing the inner loop directly with customers, or closing the outer loop with problems that keep surfacing over and over again.

Organisations are typically quite comfortable tackling inner loop programs. If you have agents that review and action customer feedback, and enough resources to contact unhappy customers, you’re off to a good start. 

However, closing the outer loop means addressing structural issues, and this is where it gets a bit harder.

In the data science department, I’m often asked how an outer loop process should work. My name is Ton Luijten, Customer Success Director + Data Science Lead in APAC—I’m also a Lean Six Sigma Black Belt. Here are my thoughts about how the Six Sigma methodology can be used as a template to help CX leaders close the outer loop and address systemic issues.

What Is Six Sigma? 

Six Sigma is a methodology that uses data analytics and statistics to analyse business processes and services in order to understand how they’re performing and how they can be optimised. The objective is to increase business outcomes (for example, improving customer experiences) by reducing defects and improving services and processes

Since collecting and analysing data is at the core of both Six Sigma and CX programs, it struck me that they seem like a natural fit.

The 5 Steps of the Six Sigma Methodology

Six Sigma follows the DMAIC process made up of the following steps:

  1. Define
  2. Measure
  3. Analyse
  4. Improve
  5. Control

We’ll go through these one by one:

Define

The first step is to prioritise the pain points that you want to tackle as a business. With Six Sigma we typically ask 3 questions:

  • Is there a gap between the current process and the customer expectations around that process?
  • Is the cause of the issue understood?
  • Is the solution known?

You should be able to answer the first question with your voice of customer data, meaning you should be able to work out what issues are causing the most dissatisfaction across your customer base. You can use a simple approach by looking at NPS or satisfaction by drivers or text analytics’ tags, or you can go with a more advanced approach and run driver analyses to understand what the key focus areas should be. This can be done on both unstructured and structured data.

For the second and third point, you might be able to answer “yes” for some simple issues. If that’s the case, then you can just implement that solution. However, we recommend proceeding with caution, as it’s easy to make assumptions.

Once you have found some issues that are not meeting customer expectations to which you don’t know the root cause or solution, there’s a good chance you can turn this into a Six Sigma project.

Measure

Normally this is where you go and measure the problem to establish a baseline. However, with a CX program, you typically already have plenty of data on your issue, so you can simply use your existing data to create that baseline.

Analysis

This is where it gets interesting—the analysis phase involves identifying the root cause, which is critical if you want to find an effective solution. We typically start with brainstorming different ideas and then once we settle on some hypotheses we can test, we can then check if we have the data available to us to check this hypothesis or if we need to collect more data in order to test it.

It’s important to understand the true root cause. It’s quite easy to find correlated themes that do not directly cause the issue. Driver analysis on both structured and unstructured data can help with this process.

Improve

Once we have identified the root cause, it’s time to come up with solutions to address it. This is where customer experience professionals can use their creative side to dream up all kinds of ideas—then the ideas can be evaluated to identify the most promising ones.

Once we’ve settled on the most promising ideas, it’s time to start A/B testing the concepts, which involves trialing the solution(s) with test groups and then comparing the performance against a control group.

In the end, there’s typically a cost benefit analysis to understand which action would have the most impact. This needs to be contrasted against the relevant investment.

Control

Once the best course of action has been identified, it can be implemented. Now it’s time to track the improvement. At InMoment, we have a tool called Watchlist to help you with this. Watchlist does the work for you by tracking customer outcomes after new initiatives have been launched.

Wrapping Up

Often companies struggle with putting a framework in place to tackle the outer loop in an effective manner. Six Sigma is one method that can be utilised to put a structure in place that can be used to root cause structural issues, identify potential solutions and identify the most effective one. Finally, it can track the effectiveness of the final solutions after implementation.

Want to learn more about how you can take action to close the loop or make other improvements to your customer experience? Check out this guide!

Employee Advocacy: Improving Experiences for Employees and Customers

This article was originally posted on Quirk’s Media.

Every successful business outcome benefits from having a reliable, flexible, actionable and amply proven template and improvement guide. This is as true for employee experience (EX) as customer experience (CX).

There is a clear path to greater, more progressive employee experience, insights and greater stakeholder centricity for any organization, and it begins with understanding the concept of experience improvement (XI) as it proceeds and matures.

The most basic definition of employee experience often has to do with overall happiness on the job (or what is generally understood as employee satisfaction). Subsequent stages in EX maturity build upon that first step. Exploring that progression, and how it will lead to experience improvement for everyone in your organization’s universe, is the focus of this discussion.

Employee Satisfaction: Providing a Little More Than the Basics

Employee satisfaction typically encompasses basic job functions like compensation, workload, flexibility, teamwork, resource availability and so forth. It’s built on the basic premise that if employees are happy, they will be productive and remain with their employer. Satisfied employees, then, are generally not aspirational and remain positive if things stay pretty much the same. Much like customer satisfaction, employee satisfaction is largely attitudinal and tactical.

A major challenge with employee satisfaction, though, was identified some time ago. Companies want to keep employees happy and reduce turnover, of course, but it was found that programs and strategies that support improved satisfaction can often result in demoralized staff – especially among employees who either want to perform at higher levels or are unmotivated to contribute more.

Even consultants and professional HR associations like the Society for Human Resource Management have determined that even high-level satisfaction doesn’t necessarily mean closer connection to the employer or greater employee performance.

Here’s a brief example of what can occur through satisfaction-based initiatives, irrespective of intentions. A large national financial services company, concerned that it was experiencing over 30% turnover among new employees, decided to give them a 13% bonus. Those employees who were “satisfied” happily took the additional money, but the result was no discernible decrease in churn.

Employee Engagement: Doing What (Almost) Everybody Else Does

The predominant EX construct that most organizations follow these days is, at its core, to consider employees as necessary costs of doing business. The overall objective of this construct is to optimize employees’ overall fit, utility and productivity within the enterprise. This construct is engagement, which also seeks to quantify emotional and rational job satisfaction (as well as motivation to think, feel, and act). The principal intents of employee engagement, then, are to identify:

  • What originally drew individuals to the company.
  • What keeps them there.
  • What they see as their jobs and how involved they are in them.
  • How aligned they are with the company’s overall business goals and culture.

Engagement, however, represents a mix of loosely related concepts and ideas rather than a single, objectively defined term. As a result, it only marginally impacts customer experience and downstream behavior. In 2006, The Conference Board published “Employee Engagement: A Review of Current Research and Its Implications.” According to findings in this report, a total of 12 major studies on employee engagement had been published over the prior four years by top research firms. Each of the studies used different definitions and, collectively, came up with 26 key drivers of engagement. For example, some of the studies emphasized underlying cognitive issues, while others addressed underlying emotional issues. What is absent from these drivers, though, is a focus on how employee behavior connects to, and drives, customer experience. And, though these findings from The Conference Board’s research are, as of this writing, close to 20 years old, the concept of engagement still puts very little emphasis on employees’ role(s) in customer focus and value delivery. In other words, though many companies might infer that happy employees equal happy customers, that relationship isn’t necessarily real or causal.

Further compromising the enterprise value and actionability of engagement is the fundamental issue of measurement. Again, there has never been a reliably clear and consistent definition of employee engagement on which to base performance since the term was first coined by an academic almost 30 years ago. Combine that with the current job market landscape, and it’s clear that employee engagement can no longer be considered a sufficient behavioral standard or organizational goal.

Employee Commitment: Joining the Ranks of the Advanced and Progressive

Employee commitment represents that which most directly shapes and creates the full (and current) EX landscape. It considers employees actively contributing stakeholders who are connected to company culture, derive fulfillment and purpose from their work, and create value for customers. Fundamentally, the concept of commitment recognizes and leverages the employees and their behavior as highly valued enterprise assets and contributions to business outcomes.

Essentially, commitment draws on key elements of both behavioral science and behavioral economics – emphasizing an employee’s emotional connection to the culture, goals, practices and customers of the enterprise – as critical operating resources. Employees have become center stage in optimizing customer behavior and perceived personal benefit in this stage, and have three key traits:

  • Commitment to the organization itself, its purpose and its culture.
  • Commitment to the organization’s value proposition, its products and its services.
  • Commitment to the organization’s customers and fellow employees.

The HR objectives of staff fit, alignment and productivity emphasized in employee satisfaction and engagement are also important in employee commitment; however, this stage of the

employee experience maturity journey recognizes the extent to which employees are in direct and indirect contact with, and providing benefit for, customers. Employees should be enthusiastic and actively supportive representatives of the brand. If, today, employee satisfaction and engagement are not designed to meet this critical objective of the customer experience, then customer-perceived value and customer experience will almost assuredly be impacted.

Employee commitment behavior (and the culture, processes and programs that support it) produce consistently stronger business outcomes (lower staff turnover, more effective experiences for customers, greater loyalty behavior, etc.) in both hard- and soft-cost terms. This more progressive approach to EX also enables companies to directly link, and intersect, employee behavior with customer behavior, making it more powerful than either satisfaction or engagement in creating brand equity.

But there’s even more for ambitious, stakeholder-centric organizations and employees to attain here, and that’s the last, and ultimate, stage of our experience improvement journey: employee advocacy.

Employee Advocacy: Becoming One of the World’s Best

The select brands and organizations that have implemented employee advocacy and its correlating outcomes use stakeholder value creation as the central flow point for operations, processes and culture. Emotional foundations, experience memories and how employees communicate them play a much greater role in employee behavior here (as almost defacto personas). This can be viewed in Figure 1 and Figure 2, which identify levels of both customer and employee value. 

Organizations can use employee advocacy to identify the drivers behind employees’ emotional and rational commitment to both their own experience and that of customers. In some instances, though, brands and groups will emphasize social media, image and other related factors as vital facets of employee responsibility. Such factors certainly have their value, of course, but understanding them doesn’t automatically correlate to meaningful experience improvement.

The advocacy concept optimizes employee commitment to the organization, its goals, its value proposition and its customers. Recognition has become especially pronounced in recent years, at least in part due the upheaval produced by the COVID-19 pandemic and subsequent Great Resignation. This, and the impact on employee dynamics, has incentivized many brands to finally invest substantially in a previously underfunded (or unfunded) myriad of employee support resources.

Additionally, advocacy creates a state in which every employee is tasked with delivering customer value as part of not just his/her job description, but as part of their broader role within the enterprise.

Customer value is delivered irrespective of employee location, function or level. In short, everyone from frontline teams to CEOs must understand how their role affects customer experience and remember that it does so regardless of how far they are from the front lines.

Summarizing the Stages, and Trajectory, of Experience Improvement

Regardless of which of stage your organization currently resides in its journey to experience improvement, it’s imperative to regularly assess both goals and priorities, understand what each of these steps has to offer and then work toward a culture of employee commitment and advocacy. A combination of recent talent landscape dynamic events and extensive research has cemented the notion that merely satisfying your employees is insufficient for retaining them or making them feel valued (let alone improving employee or customer experience).

Figure 3 shows a guide that organizations can follow as they pursue employee experience improvement.

By adopting this more progressive and outcomes-oriented set of approaches, organizations can create commitment within their employees, adopt an advanced culture of stakeholder experience centricity and continuously achieve experience improvement for themselves and their customers. The benefits, and the human connections underlying them, are immense.

Staying Ahead of the Game: Behind Foot Locker’s Innovative CX Program to Fit the Modern Athlete

We at InMoment have had the pleasure of working with some of the world’s greatest brands—and one brand that definitely stands out on that list is global footwear retailer, Foot Locker. Foot Locker is constantly striving to deliver the most memorable, innovative experiences to their “modern athlete” customers, and they have some incredible exciting initiatives planned for the next year!

InMoment sat down with Tyler Saxey, Senior Director of Global VoC and OMNI at Foot Locker, as he shared four innovations that have fearlessly driven their innovative customer experience program. We delve into what those innovations look like and how Foot Locker delivers, then sum it up with four tips you can leverage to drive innovative experiences. Let’s dive in!

4 Tips to Drive Innovative Customer Experience

Innovation Tip #1:  Understand Your Audience

Foot Locker punted a traditional view of what an “athlete” is for an all-inclusive approach they call the “modern athlete.” So what is the modern athlete? According to Saxey, the term “modern athlete” encompasses every athlete at any age, stage, and sport. 

These athletes are bringing their “A” game to their sport (whether that’s on the field, in their home, or at the gym). When they come into a Foot Locker store, log onto the app, or peruse the website,  these modern athletes are looking to “talk shop” on the latest trends and products, and ultimately to take part in a more human and memorable experience beyond basic transactions. 

By understanding their consumer, Foot Locker knows its role is to provide expertise with tools, products, and experiences to keep athletes fired up. 

Innovation Tip #2: Integrate Flexible Innovation

Foot Locker considers every possible opportunity for the customer to leave feedback. In fact, Saxey says they are “pulling every data point [they] can get [their] hands on!” Social media and social care have been a massive opportunity for the legendary footwear retailer. Also, Foot Locker enables customers to use Apple and Google to message on-call agents as if they were texting a friend. 

Saxey shares, “We’ve had success with video feedback, as it helps layer in the sentiment. Interestingly, we initially thought that our younger demographic would gravitate to video feedback. However, it’s such a user-friendly feedback tool that we’ve seen many responses from our older demographic utilizing video feedback as well because it’s so much easier for them.”

“From a company and customer perspective, having the freedom of innovation and the flexibility to simply hit record and share their thoughts is incredible! Sometimes we get three, four, or five-minute-long videos, and the unspoken details in the facial expressions, tones, and mannerisms are invaluable. You could never duplicate that feedback from a single comments box, and these elements add to the powerful integration of unstructured data.”

It is ultra important to the success of Foot Locker and the happiness of their consumers to be an actively listening company that prioritizes the voice of customer at the highest levels of the organization. And that means giving customers the most varied and innovative opportunities to leave feedback.

Innovation Tip #3: Plan for Upcoming Trends & Expectations

Foot Locker has long kept their voice of customer (VoC) program front and center of its organization, and is diligent in amplifying its innovative CX program at every level. 

This customer-centric hyper focus (as well as always on technology) detects trends and allows the company to pivot quickly to meet the need. Some of these trends may only have a 2-3 month window of opportunity for Foot Locker to supply its modern athletes with hot ticket items. Saxey shared, “We have to be able to shape our customer experience to meet those needs.”

“How we design surveys is crucial in ensuring we do our due diligence as practitioners to assure they aren’t immediately closed and deleted. Customers don’t naturally gravitate toward surveys, but they appreciate the opportunity to give feedback. We have excellent partners like InMoment working to identify trends so we can be precise and agile with limiting time frames.”

Innovation Tip #4: Stay Ahead of the Game

How do you mine through that data to find what’s valuable and take action to stay ahead of the game? Saxey says, “We rely heavily on InMoment, and they are a huge partner with us in mining and sifting through text analytics. We like to keep our surveys super short with a primary comment box, and the only way to succeed in doing that is if you partner with  the right vendor to help you mine the unstructured data.” 

In partnering with InMoment, Foot Locker has the tools to make more informed decisions and can pull and consolidate data to get a more complete picture of the customer experience. This integration has allowed Foot Locker to break out of traditional survey silos like NPS and CSAT.

Saxey says, “ We want our modern athletes to feel like they have a wonderful experience, but we know sometimes things happen. Thankfully, we can sift out no-purchase data through observation and interactions on our sites.”

“The ability to sort data offers precision in looking at the customer who may not be pleased and gives clues to why they are not purchasing, if they had a bad experience, or couldn’t find the product. This ability is invaluable to our strategy moving forward.” 

We enjoyed learning from Foot Locker’s Tyler Saxey about how innovative CX programs benefit the modern athlete and help companies bring their a-game. If you want to learn more about the  ability to prioritize, and drive the most effective actions at every level of your business click here.

How to Use Survey Templates to Drive Your Customer Feedback Efforts

Have you ever needed to get information from your customers, but weren’t sure what the best way to get it was? Or you weren’t sure which questions were the right ones to ask? Or you simply don’t have the time to build an entirely new survey from scratch? That’s where survey templates come in. 

Whether you are a small business owner looking to run your first survey, or you’re building a new transactional survey for all your locations nationwide, survey templates are there to guide you through the whole process. 

New to survey templates? Don’t worry, in this article we will cover:

  1. What is a Survey Template?
  2. What are the different types of Survey Templates?
  3. How Can I Create a Survey Based on a Survey Template?

What Are Survey Templates?

As you know, surveys are a great way to gather data from customers, do market research, and understand how the public views your brand. But, not every survey is built from scratch. 

Survey templates are guides for a survey that you would send out to your target demographic. You can select a template based on what you are looking for, and then fill out the building blocks with questions that you want answered! 

What Are the Different Types of Survey Templates?

Do you want to know how your customers felt the last time they purchased something from you? Or maybe you’re curious to understand how customers feel about your latest product? For every question, there is a survey template to help you answer it. 

Different templates help you answer different questions. Here are some of the major survey template categories:

  • Employee Experience Survey Templates: Helps you measure employee satisfaction and motivation. Allows you to turn feedback into actionable insights. 
  • Academic Evaluation Survey Templates: If you’re curious what students think about professors, curriculum, or facilities, this is the survey template for you. 
  • Satisfaction Survey Templates: If you’re looking to measure how a client feels about your services, or how your employees felt about an event, look no further! This is the survey template for you. 
  • Marketing and Market Research Survey Templates: Want to understand which demographic is gravitating towards your business? A Market Research Survey is right for you. 
  • Product and Industry Survey Templates: After releasing a new product, a Product Survey Template is a great way to understand how your customers feel about it! 
  • Customer Evaluation Survey Templates: Looking to get customer feedback or why a customer no longer wants your services? A Customer Evaluation Survey will help you to recover that at-risk revenue. 

How Can I Create a Survey Based on a Survey Template?

Once you have identified what kind of survey template is best for you, it’s time to build your survey. Don’t worry, it’s a breeze. 

When you are creating surveys with InMoment’s XI Platform, you have everything you need to have successful surveys. You’ll be able to easily collect feedback, customize questions, edit existing surveys, and invite customers and employees to provide feedback. 

Whether you choose the freedom to create your own surveys or solicit InMoment’s expert services to develop surveys as a service, you’ll receive seamless survey creation.  

When you are creating surveys, you can choose a pre-built survey template that already comes loaded with questions and is ready for launch! Then, just sit back, monitor response rates and watch the data come in. 

If you would rather see a survey with your own questions, you can take one of our customizable survey templates and customize them how you see fit!

Interested in using InMoment’s survey templates to take your business to the next level? Check them out here!

How to Improve Customer Retention

There is something to be said about how vital it is to leverage market research to understand your non-buyers so you can convert them into customers. But focusing on how to improve customer retention is just as important, if not more. It is more profitable to invest in existing customers, especially since acquiring a new customer is anywhere from five to 25 times more expensive than retaining an existing one.

The market may be vast, but there is a finite number of potential customers, so making a good lasting impression is key to keeping the customers you have already won, regardless of the industry you’re in. That is why your customer retention efforts are so important.

What Is Customer Retention?

The definition of customer retention is pretty simple: it’s your business’s ability to keep your existing customers coming back to you time after time. But with such a crowded market, that is easier said than done.

Did you know that the average business today loses between 10-30% of its customers annually? Additionally, research by CarlsonMarketing shows that U.S. companies lose 50% of their customers every five years. 

The fact of the matter is that today’s customers have more options than ever before when it comes to purchasing products and services. So, if you aren’t working purposefully to keep those customers, it’s likely they will go somewhere else.

How Is Customer Retention Measured?

We’ve already mentioned a few customer retention statistics, so you might be wondering how those are calculated. Well, let’s do some math here.

Assume the following definitions:

  • CE = The total # of customers when the period ends
  • CN = The total # of new customers that you acquired during the period
  • CS = The total # of customers at the beginning of a period

To calculate retention rate, you need to use the following equation:

  • Retention Rate = ((CE-CN)/CS)) X 100

What Is Considered a Good Customer Retention Rate?

It goes without saying that a retention rate of 100% is virtually impossible. But a “good” retention rate is highly varied by the industry you’re in. Here are some industry-average customer retention rates for you to benchmark against:

IndustryAverage Customer Retention Rate (%)
Media84
Professional Services84
Automotive and Transportation83
Insurance83
IT Services81
Construction and Engineering80
Financial Services78
Telecommunications78
Healthcare77
IT and Software77
Banking75
Consumer Services67
Manufacturing67
Retail63
Hospitality, Restaurants, Travel55

Why Is Customer Retention Important?

Regardless of the industry you’re in, retaining your customers should be one of the top four goals of your overall business (alongside acquiring customers, increasing customer lifetime value via cross-sell and upsell efforts, and reducing operating costs). After all, it is your customers that keep you in business.

If you fail to keep track of your customers, their experiences, and how many of them are staying with you versus leaving for a competitor, you could be bleeding customers (and money) without even realizing it. Need some more convincing? Here are some additional facts for you:

  • 68% of sales come from recurring customers
  • Loyal customers are more likely to share their experience with the company and they are also more likely to purchase from the company again in the future
  • Loyal customers who continue to support your brand will increase your profits
  • iLoyal customers will also recommend your brand and give positive reviews to their family and friends”
  • Returning customers tend to spend more on your brand over time.
  • You get a greater return on your investment (ROI) from repeat customers than trying to acquire a first-time customer
  • Even though only 12% to 15% of customers are loyal to a single retailer, they represent between 55% to 70% of the retailer’s sales. 

How to Improve Customer Retention

The most effective way to improve customer retention? You guessed it! By leveraging your customer experience (CX) program. Your CX program gives you direct insight into how satisfied your customers are with their experience, and then identifies the areas in which you need to improve in order to keep those customers.

There are four cornerstones of customer retention that your CX program helps to support. They are:

Understand Why Customers Leave

  • Exit Interviews: Drive true learnings from the people who understand why customers leave the most (ex customers)
  • Market Pulse Programs: Stay ahead of the competition and learn from our competitor’s customers, other industry customers, and identify other opportunities in the market.
  • Invest in the Right Analytics: Predictive models help to extend lifetime value (LTV) by warning you when specific customers are likely to churn

Eliminate Customer Friction

  • Customer Journey Mapping: Understand moments of impact and potential frustration across your customer journey
  • Employee Forums: Access the employee perspective—and socialize that perspective up the chain of command to create effective change
  • Leverage All Information Sources: Look beyond traditional surveys to include other forms of experience data, such as social data, review site data, operational data, and more!
  • Deploy Microsurveys at Key Touchpoints: Get customer feedback in the moments that matter

Recover Customers Effectively

  • Closed Loop Programs: Address concerns when it matters most
  • Multichannel Listening: Fix broken processes before they become retention detractors
  • Empower Employees: Encourage and train your employees to use their best judgment and make things right without layers upon layers of approval

Drive Deep Relationships

  • Support Teams Consistency: Identify fundamental customer needs and create customized value and benefits
  • Formal Relationship Surveys: Create goal-oriented relationship surveys; look for churn warning signs specific to your business
  • Leverage Loyalty Programs: Leverage your best customers to be your most outspoken advocates

Calculating the Value of Customer Retention Using Customer Lifetime Value (CLV)

At InMoment, we frequently sit down with brand executives and look at real-time metrics that show how much revenue has been recovered due to their closed loop program. Here is the equation we use to prove that value.

Begin with the lifetime value (LTV) of your customer— for example, a prominent pizza chain has publicly stated that their LTV of each customer is $10,000. So, let’s use that for our example. Because your CX efforts are listening to the voice of your customer across all channels, you have the ability to report that last week (hypothetically) you had 300 service lapse incidents across your digital and retail journeys. Multiply that 300 by your customer LTV of $10,000 and you now have $3M of at risk revenue. (Yikes!)

Studies tell us that 50% of those customers will continue to do business with your brand, however, 50% will defect—this is where your closed loop program comes into play. If we resolve the issues with half of that 50% that might defect, we know we have recovered $750,000 of revenue across your brand just in the last week!

From these numbers, it’s clear that, although it can be complex, focusing your efforts on improving customer retention is well worth it! And if you’re using your customer experience program to guide you, you’re sure to create the types of experiences that keep customers around for a lifetime!

To learn more about how to improve customer retention, download this whitepaper that teaches you how to use your customer experience program to improve customer retention and become a revenue generating machine!

How to Create Winning CX Surveys for Bank Customers

Constant engagement is key to creating a quality, meaningfully improved customer experience (CX). And for banks especially, the quality of the experiences customers have with a brand is the key factor in determining a customer’s longevity and willingness to maintain a relationship with a company. Banks can and should engage with customers via CX surveys and other feedback methods to see what customers love about the experience and what might need a little tweaking. Even more importantly, banks should engage with customers to let them know that they’re cared for not just as customers, but people.

Customers who feel heard and seen in this way will keep coming back even when the competition out there is fierce (and as you well know, it’s always fierce in the banking world). But what best practices should you follow to create winning CX surveys for bank customers?

Most banks rely on surveys to engage with their customers and gather this valuable intelligence, which is why today’s conversation focuses not ‘just’ on how to build a great survey, but how to do so in a way that speaks effectively to banking customers. So, with that in mind, let’s kick things off by going over our two favorite survey types: relationship surveys and transactional surveys.

Relationship Surveys

Relationship surveys are all about the big picture—brands in every industry use them to get a glimpse of the entire customer-company relationship instead of one or two transactions. A good relationship survey gives banks not only how their customers feel about experiences now, but also helps highlight which experience elements might be even more influential tomorrow.

What follows is the secret sauce for a great relationship survey. You want to include metrics that measure overall satisfaction and loyalty. You also need questions about brand perception, channel usage and satisfaction, product usage and satisfaction, and the experiences that impacted, or are impacting, your customers the most. Questions about marketing communication perception never hurt either! All of these questions, when used together, will give your bank a 360-degree view of customer relationships that goes a long way toward Experience Improvement (XI).

Transactional Surveys

As its name suggests, a transactional survey is all about how well (or not) a transaction at your bank went for your customer. These surveys can be tuned to both in-person interactions and online banking. Though transactional surveys are of a smaller scale than relationship ones, they’re also much more specific, which is great when you’re trying to get into the details of individual interactions.

Generally speaking, you want your transactional survey to ask how well the transaction went, overall satisfaction with elements like application processes and bank teller interactions, and whether there were any problems with either the transaction itself or the resolution that followed. All of that makes for a good enough survey, but we challenge you to go beyond by also asking about elements like how knowledgeable your customers think your reps are, how complete your information is, and whether it’s easy to jump between channels for a more fluid experience.

The Next Step

Whether you’re looking to design your first survey or double-checking whether your current one is up to scratch, we also challenge you to bear something else in mind: having a survey is great, but knowing when and where to deploy it is even better. Hot alerts, contextual survey deployments, and being able to analyze unstructured survey feedback can help take your bank straight to the top.

Interested in learning more on how to do all that? Click here to read our full-length eBook on how banks like yours can use surveys to meaningfully improve experiences, strengthen your bottom line, and build meaningful relationships with customers!

CX 101: Everything You Need to Know About the Customer Satisfaction Survey

It’s every company’s dream to have loyal, lifelong customers. In order to get this, you need to understand what your customers want, how they view your brand, and how they feel about your products and/or services. To put it simply, you need to understand their entire customer experience, from beginning to end. 

One way to do this is through customer satisfaction surveys. Let’s dive into what they are, why they are important, and the different variants of them that you can use. 

What Is a Customer Satisfaction Survey?

Customer satisfaction surveys enable you to measure your customer’s satisfaction with your businesses products, services, experiences, or even your staff. These surveys offer a holistic view of different aspects of your customers’ experiences. They can use a rating system that can be tracked over time, offer specific insights into your customers’ pain points, and help you work to continue to meet your customer’s needs. 

Why Are Customer Satisfaction Surveys Important?

Customer satisfaction surveys are important because they are a direct insight into the customer experience. They help you understand how your business is viewed, and what you can do to improve that. Having high satisfaction rates is important to your brand for many reasons. Satisfied customers spread the word, satisfaction is a great indicator of retention, loyalty, and customer lifetime value. 

What Are the Four Types of Customer Satisfaction Surveys?

There are many ways to measure customer satisfaction, but there are a few that are more prominent, popular and productive than their counterparts. Here are three of the most common types of customer satisfaction surveys or measurements: 

Customer Satisfaction scores are an attempt at capturing how satisfied customers are with a company’s goods and services. A survey asks a customer to rate their satisfaction, typically on a scale from 1 to 5.

Net Promoter Score® (NPS) is a trademarked metric between -100 and 100 that captures in aggregate the propensity of a company’s customers to attract and refer new business or/and repeat business.

The Customer Effort Score is an index from 1 to 7 that measures how easy a company makes it for customers to deal with its products and services. A company that provides effortless service gets a 7 while a company that makes it difficult gets a 1. In other words, the higher the CES, the better.

To learn about other types of customer satisfaction surveys, you can find more info here.

What Types of Questions Should a Customer Satisfaction Survey Include?

There are a wide variety of questions you can ask across multiple types of surveys, it just depends on what you are looking to get insight on. Here are examples of categories of questions and example questions.

  • Product Usage
    • How long have you been using the product?
    • How often do you use the product or service?
    • Does the product help you achieve your goals?
    • What is your favorite tool or portion of the product or service?
  • Demographics
    • Where are you located?
    • What is your level of education?
    • Where do you work and what’s your job title?
    • What industry are you in?
  • Satisfaction Scale
    • On a scale of 1 to 10, how satisfied are you with your experience today?
    • Did you feel that our team answered your inquiry promptly?
    • Do you agree or disagree that your issue was effectively resolved?
    • How likely are you to return to our website?
  • Open-Text
    • How can we improve your experience with the company?
    • What can our employees do better?
    • How can our employees better support your business’s/your goals?
    • Why did you choose our product over a competitor’s?
  • Longevity
    • May we contact you to follow up on these responses?
    • Can we connect you with a customer success manager via chat?
    • Would you be open to discussing upgrade options for your product?
    • Can we send you a list of useful resources for getting the most out of your product?

One of the most important things to remember when designing customer acquisition surveys is that if your survey is too long, or too tedious, you will not get responses. Timing your surveys right, and designing them effectively will help you get all the information you need to keep your customers happy and satisfied with your products.

To learn more about customer satisfaction surveys and the best way to utilize them, download our free white paper here!

What Is Sentiment Analysis? Definition, Types, Importance, and More

There is so much more to communication than just the words we say. Take sarcasm, for instance. Sarcastic comments often rely heavily on irony, conveying the opposite meaning from the one being directly expressed. But this irony is hard to convey without the added benefit of voice inflection and bodily cues (which is why it can be so problematic when someone tries to be sarcastic in a text message or email). 

At the same time, non-verbal cues may even go so far as to reveal deeper meaning even beyond what a person intends to express—lack of eye contact during a conversation may indicate that one is uncomfortable with the situation while leaning forward can mean that they are actively engaged and paying attention. In fact, studies suggest that as much as 90% of communication is non-verbal. And while there’s some debate over the accuracy of that number, no one can deny that there’s more in what we say than is carried in the words we speak (or type). 

This can create real problems for your business. Given that most customer feedback is text-based (such as emails, social media posts, surveys, in-app feedback, SMS, live chat, etc.), it can be extremely difficult to discern the actual meaning behind the words. To keep up with expectations and provide a positive customer experience, companies in all industries need a more accurate way to understand and categorize their customer feedback. This is where sentiment analysis comes into play. 

What Is Sentiment Analysis?

Sentiment analysis is a term that describes the tools and strategies designed to help organizations extract unspoken meaning and emotion from text. By using sentiment analysis to contextually mine written communication for subjective information, your business can gain a greater understanding of how your customers view your brand, services, products, and more. 

At its most basic, sentiment analysis can, with reasonable accuracy, determine whether written or spoken feedback should be classified as favorable, unfavorable, or neutral, and how intensely that sentiment is being expressed. 

To make this possible, sentiment analysis is generally supported by sentiment scoring (also called polarity analysis). Often the polarity or overall sentiment is expressed using a numerical score ranging from -100 up to 100, with 0 representing a completely neutral sentiment. This kind of sentiment analysis scoring can be applied to specific phrases or points in the customer feedback or may be calculated for the entire text. Thus, your organization can apply sentiment analysis to create a mathematical data model representing the overall opinions or attitudes of your customers—either as individuals or groups. 

But sentiment analysis can also go beyond the basics, picking out subtle clues in messages to help you better understand what your customers are feeling and how you can help them have a positive experience. 

How Does Sentiment Analysis Work?

The origin of sentiment analysis as a field of study traces itself back to the mid-20th century, when researchers would comb through and compare written documents to better understand the authors’ intent. But it wasn’t until the advent of digital communication and big data mining that sentiment analysis became a viable business tool. Today, technology advancements in AI, deep learning, and natural language processing (NLP) make it possible for organizations to mine massive amounts of customer data to gauge public opinion, conduct market research, monitor reputation, and better understand the customer experience.

At the heart of modern sentiment analysis are algorithms designed to automate the identification of text sentiment based on specific methods and analysis models. And although individual organizations may differ somewhat in their approach, most sentiment analysis processes fall into one of three categories:

Machine-Learning Sentiment Analysis

Using automated techniques, machine-learning sentiment analysis allows computer systems to learn from provided texts and apply those learnings to future evaluations. To do this, companies will provide the sentiment analysis model with a training set of natural language feedback that has already been tagged with labels showcasing which words or phrases demonstrate a positive, neutral, or negative sentiment. The model takes these correlations and then applies them to new natural language sets. 

Over time, the machine-learning sentiment analysis model becomes more effective at automatically identifying emotional sentiment within text. 

Rule-Based Sentiment Analysis

Rule-based sentiment analysis relies more heavily on human-built rules to locate hidden sentiment within a text. In its most simple form, the algorithm is provided with a detailed lexicon of possible words, terms, and expressions, with each assigned a sentiment score ranging from negative to positive. Then the algorithm simply tabulates the total score from each word or phrase within the text to determine the overall sentiment of the data set. Rule-based sentiment analysis may require further refining to account for things like idioms, sarcasm, or other unique verbal cues.

Hybrid Sentiment Analysis

For increased accuracy, organizations will often combine rule-based and machine-learning sentiment analysis models to create a hybrid approach to sentiment analysis. This allows the model to retain the statistical accuracy of machine learning while also incorporating hand-written rules for a more stable sentiment analysis solution. In this approach to sentiment analysis, different types of classifiers back each other up, so that if one fails, the next can step in to ensure that no sentiment is overlooked.

Why Is Sentiment Analysis Important?

As communication technologies continue to improve, today’s customers expect their voices to be heard. As such, sentiment analysis has grown into an essential tool for monitoring and understanding opinions relevant to business.

Using sentiment analysis to mine these opinions from customer feedback, social conversations, service agent interactions, etc. can give your organization key insights into how customers and other stakeholders feel about your business and its offerings. You can then refine your processes, products, and services to better meet these expressed—and unexpressed—needs. The advantages of effective sentiment analysis range from being able to resolve customer concerns more quickly, to tracking and identifying trends and relevant factors in customer satisfaction scores across predefined periods.

Those businesses that offer a multichannel or omnichannel experience gain further benefits. Sentiment analysis empowers teams to automatically categorize feedback by the channel it was received in, and to develop an accurate picture of customer perception across individual platforms. 

Types of Sentiment Analysis

Even within the categories mentioned above, there are different ways to approach sentiment analysis. Some of the most widely used sub-types of sentiment analysis include:

Aspect-Based Sentiment Analysis

Aspect-based sentiment analysis tracks emotional sentiment related to specific aspects of a business or its products/services. For example, an organization that rolls out a new feature as part of its app may employ aspect-based sentiment analysis to better understand how users feel about the upgrade. Aspect-based sentiment analysis would identify feedback, comments, and conversations relevant to the new feature and determine whether customer sentiment is positive, negative, or neutral. 

Clause-Level Analytics

Clause-level sentiment analysis breaks feedback down into clauses rather than sentences. For example, if a customer were to comment that a clothing product they recently purchased “Looks great but isn’t comfortable to wear,” clause-level sentiment analysis could be applied to better understand just how satisfied or dissatisfied the customer is with their purchase. This makes it possible for businesses to correctly categorize responses that may include both positive and negative sentiments in a single sentence. 

Emotion-Detection Sentiment Analysis

Emotion-detection sentiment analysis goes further than tracking negative-to-positive sentiment polarity and instead detects the emotional state of the person originating the feedback. Like other forms of sentiment analysis, emotion detection relies on lexicons of emotionally-charged words, machine-learning algorithms designed to detect emotional cues in text, or a combination of both. 

Intent Analysis

Customers may reach out to your company or provide feedback for many different reasons—a client who wants a refund will naturally be motivated by intentions that are not the same as those who are merely looking for information. Intent-based sentiment analysis analyzes the objective of the customer, categorizing the message so that it can be more accurately addressed. 

Multilingual Sentiment Analysis

Multilingual sentiment analysis applies the same processes to messages and feedback originating from speakers of more than one language. This adds to the complexity of the algorithms and may require additional processing and resources. In many cases, organizations will train an individual sentiment analysis model to address sentiment in a specific language, rather than attempting to create a model that can analyze sentiment in multiple languages. 

Sentiment Detection

Sentiment detection is a form of sentiment analysis used to pick out emotionally-relevant text from neutral or objective information. For example, sentiment detection applied to a movie review would identify “It was exciting” as a positive sentiment while making note that “The run time was 122 minutes” is simply a statement of information with no positive or negative sentiment attached to it. 

Smart Text Analytics

Smart text analytics can help you gain vital insights from unstructured feedback. This approach to sentiment analysis breaks down silos and connects data from various sources, applying an AI-based adaptive sentiment engine capable of closely analyzing customer messages to identify trends and themes over time. Click here to learn more.

Sentiment Analysis Examples

At the end of the day, most forms of sentiment analysis are tied directly to the words and phrases customers use when they discuss your brand, its business policies, and the products or services you offer. With this in mind, let’s take a look at some examples of sentiment analysis, and why some feedback may be easier to classify than others. 

  • “I love how the new menu is arranged!”
    The sentiment here is fairly straightforward; the customer is expressing a positive feeling and providing clear feedback. Most sentiment analysis tools would have an easy time identifying the sentiment.
  • “Oh man, I sure do love how you increased all the prices. Thanks so much for doing your part to drain my wallet.”
    The sentiment in this feedback is more difficult to identify from the text alone, requiring a more in-depth sentiment analysis. Although the customer is using positive terms (“love,” “Thanks”), they are clearly intending to convey a negative response.
  • “I’m not unhappy with how the product looks.”
    The feedback here uses a double negative to indicate that the reviewer is not fully pleased, but also not fully displeased. Poor sentiment analysis of this phrase may incorrectly attribute polarity beyond what is being expressed.
  • “The new slogan made me 😆.”
    Nonstandard characters can present a real challenge for sentiment analysis tools, unless the tools have been trained to recognize the sentiment of these characters.
  • “The service agent was salty about something.”
    Sentiment analysis tools need to be adaptable enough to take into account new slang as it evolves. In this case, the term ‘salty’ may be too new for some sentiment analysis models to accurately identify as a negative.
  • “The ending of the film was horrifying.”
    Often, whether a word or phrase carries positive or negative sentiment depends on the context. In this example, the “horrifying” ending may indicate a positive response, provided that horror was what the viewer was hoping to experience. To identify this, the sentiment analysis tool would need to be capable of taking other factors into account. 

In each case, the best sentiment analysis tools are those that can help you see beyond the words, and grasp the meaning and purpose behind your customers’ feedback. 

Sentiment Analysis with InMoment

Sentiment analysis can help your business more easily quantify your customer’s experience, providing you with unique insights into your reputation, service, and products. But as digital channels open up ever-expanding sources of customers and user feedback, sentiment analysis tools must likewise scale to meet increased demand. Without the right sentiment analysis solutions, you may find that keeping track of what your customers are saying (and how they are saying it) is prohibitively expensive in terms of cost, effort, and time.

If sentiment analysis is a concern for your business, then we have the solution. 

InMoment, the leader in people-oriented text analytics, brings advanced sentiment analysis to businesses in industries around the globe. leveraging industry-recognized metrics and real-time intelligence gathering, combined with powerful survey capabilities across every common digital channel, InMoment sentiment analysis tools give you the power to quickly and easily gather the insights you need to optimize onboarding processes, enhance product experience, improve customer support interactions, and boost customer relationships like never before. 

Don’t let hidden sentiments hamper your success. Learn how InMoment’s CXInsight sentiment analysis tool can help you get the most out of your customers’ feedback.

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Struggling to Prove the ROI of Customer Experience? You Could Be Missing These 3 Keys to Success

More than ever before, proving the ROI of customer experience is absolutely vital. Businesses are under pressure (amidst the Year of the Squeeze, declining employee retention, etc.) to look at cutting discretionary spending. And, unfortunately, customer experience programs may fall on the chopping block. In fact, research shows that 30% of businesses reported having budget related issues to their CX programs. 

Under all that pressure, how are you supposed to build a CX program that continuously demonstrates its value?

If you are looking to unlock a true return on investment in your experience program, you need to go beyond sending and collecting surveys. You need to craft a strategy that enables you to use customer and employee feedback to take action in strategic areas that actually improve the experience and map to business value.

To help our customers to do just that, we leverage a philosophy we like to call the “Continuous Improvement Framework.”  

The Continuous Improvement Framework: A Quick Summary

The Continuous Improvement Framework focuses on building an experience program that moves past measuring and managing what customers are saying and transforms into one that actually improves the customer experience and benefits your business.

To reach the goal of a truly effective, ROI-focused CX program, we cycle our customers through our five step framework. Those steps are:

Design

The road to true experience program success begins with clearly defining an experience strategy that aligns with overall business goals and brand promises and then designing a program purpose-built to support those goals.

Listen

Thoughtfully deploy modern listening strategies and data integrations to expand and enhance holistic understanding.

Understand

Centralize data streams and leverage advanced analytics and behavioral science experts to identify where and how to act—and the anticipated impact.

Transform

Create and implement dynamic actions plans, trainings, and policies that facilitate organizational change and promote revenue-generating activities.

Realize

Evaluate and demonstrate results of experience initiatives including organizational change, improved metrics, and financial impact while determining appropriate next steps.

A Common CX ROI Misperception

Where we’ve seen so many brands go wrong on their path to CX ROI is that they are too focused on the “Listen” and “Understand” steps of this framework, and not enough on the other three. 

In our latest webinar, “Designing, Actioning, and Realizing a ROI-Focused CX Program,” two of our esteemed experts, Jim Katzman and Eric Smuda, break down the truth behind common difficulties in proving the ROI of customer experience—and discuss why surveys alone do not create ROI.

And because we are all about sharing the best practices you need to overcome obstacles, here is a breakdown of those three necessary keys you need to take your experience program to the next level.

3 Keys to Prove the ROI of Customer Experience

  1. Design
  2. Transform 
  3. Realize

Key #1: Design

Design is arguably the most important phase of your experience program. If you build your program on a faulty foundation,  the results can be deadly for your program (think lack of actionable insights, false signals, and hours of work that don’t accumulate ROI).  

When designing the right program for your business, it is important to shift your focus away from scores, scores, scores. A program that relies too much on scores can hurt your chances of proving ROI. Additionally, if there is too much focus on the financial drivers of the past, there isn’t much room to ideate, test, and implement financial drivers for the future.

So what should you focus on when designing your program? The answer is simple: you need to focus on what you want to get out of the program. And if that’s ROI, you want to build a program that will allow you to capture insights that can be turned into actions that result in financial returns. 

In our experience, the four areas most programs prove the ROI of customer experiences in are:

Key #2: Transform

In order to completely transform your experience program, you need to focus on three key processes: organization, action planning and project management. 

Organization

Organization refers to how you are taking action, and how that is being implemented across your company. One major step in successful organization comes from developing cross-functional teams and avoiding siloing data from department to department. 

Each department needs to be connected to the customer experience and work to support front-line employees. Upward and downward organization will lead to a more holistic customer experience. 

Action Planning

Using the Net Promoter System (NPS), you can look at inner loop and outer loop processes for action planning. Inner loop processes are very 1:1 based. They refer to individual customer feedback and the learning, and actions that come from that. 

Outer loop processes are when teams meet and determine that they keep hearing similar feedback from multiple customers and that maybe something is going on systemically that is causing issues for many customers.

The inner loop is generally focused on short-term action, while the outer loop focuses on structural improvements that may take longer.

Project Management

Whether they be short-term or long-term, you will always have multiple projects going on at the same time. With so many things to do, how do you decide where to focus your efforts? You need to consider how many customers are going to be impacted by this project, what is the cost/benefit of this change, and how easy is the change to implement. 

Now, if you design your program thoughtfully, you should be able to use your findings to understand where you focus your efforts to help continuously improve the customer experience.

Key #3: Realize

After you collect insights and take action based on your findings, you need to measure success and then share that proof across the company. Because if you truly can prove the ROI of your customer experience but don’t share it with your stakeholders, how is it helping you in the long run?

It is important to share your wins! Be vocal about the success you have seen from your CX program. Not only will it help show how your program is helping the customer, it will also create a culture of commitment within your business and show your employees that their efforts are being successful. 

Additionally, when you are looking to prove the success of your CX program, it is important to partner with your finance department. They are the ones who will help you measure and validate your wins, then turn them into a cost analysis report that your c-suite will want to see. 

If you are able to use the metrics your c-suite cares about (customer acquisition, customer retention, customer lifetime value and cost reduction) then your program will become a proven asset in your company, not a liability at risk of being cut. 

To Sum It All Up

Proving the ROI of your experience program is crucial. But, it is important to remember that it isn’t always about the money. 

Changing your CX program is as much about driving a culture of customer centricity as it is about driving revenue. This cultural journey can be reflected in an increase in employee commitment, and by building a program that delivers as many cultural wins as it does financial wins. 

To learn more about how you can transform your CX program into an ROI-Focused, revenue generating machine, watch the full webinar with experts Jim Katzman and Eric Smuda here!

CX 101: Sampling Methods

When you want to get information from customers, it might seem nice to be able to ask every single customer. To make that happen, you would need every customer to agree to be surveyed, and it would take an extreme amount of time, effort, and money to then ask every customer your survey questions. Even then, you would have an inordinate amount of data to sift through. It’s true that you could definitively make claims about what your customers are saying, but it’s not actually necessary to go through this level of work. In fact, most likely, it’s not possible to survey every single customer.

Instead of surveying every single person you want feedback from, most people use a concept called sampling instead and rely on sampling methods to research a group. Sampling allows you to get information from a group of people, and when done correctly, the information is also generalizable and usable. We’ll walk you through sampling, types of sampling methods, and how to begin using some of these techniques. 

What Is Sampling?

Sampling is using a group of your population to understand the population as a whole. Think of sampling as you would with sampling a cake. To see if a whole cake is delicious, you can usually tell by eating a slice of the cake. That slice of the cake can tell you a lot about the taste, texture, consistency, and overall balance of the cake—and it’s much easier to eat just a slice instead of an entire cake. Sampling for surveys works much the same way. 

You take a group of your population and survey just them. It’s typically much more manageable and affordable to do so when you’re doing large scale research. From there, your data team will be able to analyze the data from the sample—which is typically a smaller amount that’s easier to glean important insights from. The insights from sampling—if your sampling is done correctly—can then tell you about the whole group you’re researching. And it can help you gather these insights at a fraction of the cost and much less effort than it would take to survey the entire group. 

Difference Between Population and Sample

To better understand sampling methods, it’s important to distinguish between the population and the sample. The population is the entire group of people you want to learn about and to be able to draw conclusions about. For example, if you wanted to determine how your customers felt about a new product, your population would be every single customer that’s purchased the new product from you. If you wanted to research the grocery shopping habits of single mothers, your population would be every single mother. 

The sample is a representative group of your population that will be participating in your research or survey. The key is that the sample has to be an accurate representation of your population. For example, if you were researching the grocery shopping habits of single mothers, you couldn’t go to a local grocery store and survey every person who walked in. You would get data, but it wouldn’t be data about the population you’re trying to study. As with the cake analogy, the sample or slice has to accurately represent the entire cake. 

It’s important to remember that population doesn’t necessarily mean “big” and sample means “small.” Populations can be defined by so many factors: geography, age, gender, income, and so many more factors. You can have a tiny population of just a particular set of customers or a large population like the entire adult population of North America. The larger, more dispersed, or more diverse your population is, the harder it will be to sample. 

What Are Sampling Methods?

When you want to do a survey or perform research, you’ll need to use sampling methods to determine who will be a part of your sample and how it will be related to your population. Carefully consider how you will select a sample that is as representative of your population as possible. In general, there are two categories of sampling methods: probability sampling and non-probability sampling. 

Probability sampling is when each member of the population has an equal chance of being selected to be included in the sample. The sample participants are chosen randomly, and the results from the survey are generalizable to the population as a whole. Probability sampling methods are typically more accurate than others, but they are also more time consuming and expensive to make possible. 

On the other hand, non-probability sampling is when each member of the population does not have a chance of being selected. With these sampling methods, you could choose your sample based on convenience or other limiting criteria that make it so that every person isn’t eligible to be selected.

For example, if you wanted to study all of your customers, it would be a non-probability approach to then just select a sample of customers who have subscribed to an email list. In this situation, you would be limiting who could be selected to those on a list, which may or may not be accurate to your entire population. With non-probability sampling, it’s generally much more affordable and easier to do research, but you do run the risk of accumulating higher amounts of sampling error and reducing the likelihood of having a generalizable sample. 

Probability Sampling Methods

To perform a probability sampling survey, there are several methods that are commonly used. These are some of the most commonly used probability sampling methods: 

Simple Random Sampling

Simple random sampling is the simplest way to get a sample where every member of the population had an equal chance of being selected. To do a simple random sample, you will choose a way to randomly select a certain number of people from your population to survey. Some common methods include using a random number generator, drawing a name out of a hat or bowl, or any other type of chance. 

For example, you could number each customer you’ve had and use a random number generator to determine who will be a part of your sample. You could use a list generator to select certain customers from a list of names or emails. However you do it, the key is that it’s random. 

Systematic Sampling

Using simple random sampling can be extremely time consuming with a large population, so many will instead use systematic sampling. Systematic sampling is using some sort of designated system to choose randomly. For example, you could number all of your customers and choose the tenth individual. Choosing systematically saves you time and effort but still provides you with a random sample. 

Stratified Sampling

Stratified sampling is most useful when you have groups of people who should be sampled from equally. First, you divide your population into groups that don’t overlap (i.e. people from one group can’t be in another group). From there, you’ll randomly select a sample from each group. 

For example, if you were looking at your customers, you might want to break them up by annual income to see if that affects what you’re researching. Your stratified groups would then be done by income, and you would select a small sample from within each group. 

Cluster Sampling

Cluster sampling also involves splitting your population into groups, but these groups should be split randomly if possible. Then, instead of selecting from each group, you will randomly select groups and sample everyone in the group. For example, an airline might randomly select a certain number of flights each day and survey every passenger on those flights. 

Non-Probability Sampling Methods

Since probability sampling can be time consuming, some people will use non-probability sampling methods instead. These methods are generally not generalizable to the whole population as they may or may not be an accurate representation of the population. 

Convenience Sampling

Convenience sampling is choosing a sample based on ease of access. Instead of choosing from a population randomly, you choose from a population based on who is easy to communicate with. For example, standing in front of a grocery store and surveying everyone who walks past is convenience sampling. Not every member of your population has an equal chance to be chosen, and your data will only represent one day at one grocery store.

Choosing customers based on being subscribed to newsletters or who follow your company on Instagram could also be convenience sampling (if your population is larger than just “those who follow us on Instagram”) because it’s all about ease of access. 

Voluntary Response Sampling

Voluntary response sampling is when you select a sample based on who wants to be a part of the sample. The individuals can voluntarily choose to respond or not respond based on a general call for responses. For example, you could send out an email to every customer and ask them to join the study. Those with strong opinions or interest would be the most likely to join, which could mean your population isn’t representative. 

Purposive sampling

Purposive sampling selects a sample based on what a researcher decides. Essentially a researcher will be the one to determine if someone is in the sample or not. For example, you could put out a survey, and the researcher would then only look at the surveys for people who they decided met a certain criteria: like having purchased the most recent product. 

Snowball Sampling

Snowball sampling is used when a population is hard to reach. For example, if your research requires data from shelterless people, you may have a hard time reaching them for a survey. Snowball sampling is when you use just a few individuals you can find from this group or even choose participants based on whose family or associates you can contact. While snowball sampling isn’t random, it can be useful for certain populations that you may not be able to survey in another way. 

The Bottom Line

Overall, there are many sampling methods to choose from when planning your surveys. The end goal is to try to get your sample to be as representative as possible of your overall population, so you can use the results to generalize about the population and make conclusions. Poor sampling will give poor results. After all, as we all know, if we put crappy data in, we get crappy results, which don’t benefit anyone. Choose a representative sample instead for beneficial results
See how InMoment can help you with your sampling and survey efforts to help you choose the right sampling methods to get a representative sample.

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