CX Design: What It Is, How It Works, and How It Creates Experience Improvement

If you’ve ever heard the terms “CX” or “customer experience” before, you probably know that they and similar phrases refer to organizations’ attempts to scour every interaction for feedback and insights. You might also know that customer experience is generally considered to be a more specific subset of user experience (UX). But how do those organizations design CX programs? What goes into deciding which interactions to scrutinize, the goals formed around that work, and so much more? If you’re curious about CX design and how organizations wield it, you’ve come to the right place!

Today’s discussion breaks down the wider universe of CX design, but we’re also going to talk about the best ways for organizations to leverage this discipline. Many brands consider merely “managing” experiences to be the finish line of CX design, but there’s a lot more that organizations can accomplish, including genuine Experience Improvement (XI). Let’s get into it!

What Is CX Design?

The idea of CX design was relatively simple for many years. Basically, when an organization’s leadership decided to engage in customer experience design, they would deploy surveys (sometimes physically) for customers to fill out and hand back. We’ve all seen the little surveys that sometimes pop up after buying a sandwich, getting a car serviced, visiting a retailer, and the like. For a long time, this was considered cutting-edge CX technology and a valuable means of soliciting feedback. Other methods, like mystery shopping, were often used as well.

However, as technology has grown more sophisticated, so too has our understanding of not just how to manage customer experience, but how to improve it. Our understanding of what customers truly seek in experiences has broadened as well, and so the job of a CX designer (and the role of CX strategy in general) became more about understanding customers’ minds, not just getting their feedback. It became about optimizing journey touchpoints to delight customers and nurture relationships!

Unfortunately, even though technology and new learnings have made CX design so much more powerful than in years past, many organizations seem content to use it to gather numbers and react to problems only as they arise. This principle is reflected in how these companies’ programs are designed; CX teams don’t deploy to fix a problem until it’s been submitted by a customer, and discussions on program progress are centered around how today’s metrics compare to yesterday’s.

The issue with this sort of CX design is that while it can give you a superficial temperature reading of how customers like your brand… that’s about all you’re getting from it. Organizations that take this tack with their CX design miss opportunities to, yes, fix glaring flaws, but also meaningfully improve experiences and get to know their customers on a more human level. That is where the true power of CX design comes into play, and the brands that wield it are, more often than not, at the top of their vertical because of it.

What Does the CX Design Process Look Like?

If CX design can really help organizations achieve such dramatic transformations and high goals, what’s the first step toward actually doing that? 

As we mentioned earlier, many brands start their CX design process by looking at a handful of channels their customers might use to communicate (contact centers, social media, etc.) and deciding to pay more attention to those channels. However, while going about CX design this way might net you a few insights here and there, it’s actually much more effective to design with the end in mind.

In other words, before you even turn any of your listening posts on, take some time to consider which goals you actually want to achieve with your CX program. The sky’s the limit, too! Don’t be afraid to stake out some truly ambitious goals in your design. Experience programs can be used to achieve some pretty amazing things.

What those things are depends on what your business needs. For example, if your customers are churning a lot more than you’d like, you can build your CX design around better customer retention. Or, perhaps you’d like to use your experience program to improve workplace culture or get a better sense of what’s going on in the marketplace around your organization.

Whatever your Experience Improvement goal is, just having that as a guiding ethos will make a world of difference for your CX design. However, while your goal should be aspirational, it also needs to be quantifiable—to revisit the churn example, make sure that you tie a specific percentage or number to your goal. That will further define the finish line you want your CX program to help you cross, and it will also make your initiative’s value more tangible and therefore more visible!

Why Is CX Design Important?

Once organizations establish the goal(s) they want to achieve with their CX design and attach some sort of target number to it, it’s time to take the next step and consider which CX tools to use. This is another reason why setting a goal before doing anything else is so helpful, because it helps you determine not just which tools and channels to focus on, but also which groups of customers.

For example, if you see a chance to improve new customer acquisition, it doesn’t make sense to deploy tools geared for that goal toward all of your customer segments. Rather, you can free yourself and your CX design to focus all your efforts towards new customers. And if you have the bandwidth for additional CX goals, you can deploy your remaining tools where they most make sense. This more deliberate and thoughtful approach to design goes a long way toward achieving those goals!

This approach will also help you find and listen to the channels most relevant to your CX goals. To revisit the customer acquisition example, a CX team that sets that goal might research the areas where new customers most talk about your brand, then set up surveys and other listening tools there to capture that customer intelligence at its most organic. The team will have honed in on the channel most relevant to its goals and successfully filtered out noise from customer segments that are less relevant to those goals.

You don’t have to be a CX expert to know that brands and organizations love data. In fact, some companies love data so much that they gather it just for the sake of having it! Having data is certainly important, of course, but much like the CX metrics we talked about earlier, just having it won’t create Experience Improvement for your customers. The only way to do that is to actually take that data and mine it for valuable insights.

Data hygiene is yet another area that conventional CX design struggles with. A lot of programs are designed to gather lots of data very efficiently, but that creates a whole new challenge for the people running that program—namely, how much time does it take to sift through a mountain of data? What insights should CX teams look for and which ones should they disregard? And how can those teams make progress finding insights when their program is gathering data from every corner at every moment?

This is yet another reason why a deliberate, more targeted approach to CX design is the way to go. If you build your CX programs around very specific goals, the data you gather will be much more specific as well. Your data mountain will be smaller and more manageable, and your CX team won’t have to go near as far to find the insights most helpful to their goals.

One final note about data is that it doesn’t have to come from the CX team alone. Pulling other employees and groups into your CX design process can help you get a complete, 360-degree picture of your customer, further cementing both your goals and your future success. Including others also lets them know that, no matter how far away their job may be from the front lines, their work still matters and is relevant to creating a great experience for customers.

Realizing Experience Improvement Through CX Design

This is the hardest part of customer experience design, but it’s also what the process that we’ve been talking about is designed to simplify for you, your CX team, and your entire brand. You’ve used this CX design process to learn what you need to change to create Experience Improvement for your customers; now it’s time to reach out to the right teams and work together to actually make those alignments.

Once you do, continue to track and quantify those changes. Quantifiable goals are like receipts for a CX program; they give you something to prove its worth when you go back to the board for additional funding (as a quick aside, if you hear any positive customer stories that come about as a result of your changes, save those too! Execs love them). Some changes take a while to blossom, but they’ll be worth the wait once they come through.

Ultimately, what is the point of great CX design? A stronger bottom line for your brand? Yes. Eliminating problems with your journey touchpoints? Absolutely! But there’s an even more ambitious goal that comes about as a result of great CX design, and that’s true Experience Improvement. In this context, Experience Improvement doesn’t just refer to individual interactions better and fixing journey touchpoints (though those are certainly important). It means aligning brand and CX design to achieve seamless experiences. It means understanding who your customers are on a deeply fundamental, human level.

Once organizations achieve that close-up understanding of their customers and thus a close bond with them, there’s almost nothing that can break that relationship. Customers who feel understood as human beings, not just clients, won’t ditch you for a competitor. They’ll evangelize your brand to anyone who will listen. And it’ll all be thanks to your stellar CX design and the Experience Improvement opportunities it created!

We hope that this conversation has given you more insights into what CX design is and how fundamentally it can transform your experiences and brand ecosystem. If you want to learn more about how Experience Improvement can help your organization, feel free to download this e-book!

We’re always up for chatting about all things experience, and our mission is to help you own the moments that matter.

CX 101: What Is a Cluster Analysis? 

Math and numbers are the ultimate in ‘exact science.’ When we work within the confines of mathematics, we can expect absolute precision in our results. In data analysis terms, this can be a real advantage, giving us clear, definite numbers on which to base future decisions. Unfortunately, sometimes the real world being represented by the data is anything but exact. And when it comes to grouping objects based on a somewhat nebulous idea of similarity, traditional statistical tools may fall short. 

Cluster analysis is an answer to this problem. With cluster analysis, data analysts can construct data groups (or clusters) based on a range of similarities and differences. The end goal is to distinguish data points in such a way that those within a group are as similar as possible and completely distinct from the data points belonging to separate groups.

Here, we take a closer look at cluster analysis, how to perform one, how to interpret the data, and what potential disadvantages you should be aware of before you get started. But first, let’s define the term itself.

What Is Cluster Analysis?

At its most basic, cluster analysis is a statistical methodology designed to allow analysts to process data by organizing individual objects into groups defined by their similarity or association. Also called segmentation analysis or taxonomy analysis, cluster analysis exists to help identify homogenous groups with a range of items when the grouping is not already known or defined. In other words, cluster analysis is exploratory; data scientists who apply cluster analysis don’t begin with any predefined classes or expectations.

Instead, cluster analysis takes a collection of data items and attempts to organize them based on how closely associated each one is with the others. Visually, this is often represented using a multi-axis graph to more accurately identify which data points are similar and which are not.

One common example of clustering is the arrangement of items within a grocery store—products are classified and grouped based on how similar they are in purpose.

Cluster analysis is an essential aspect of modern artificial intelligence (AI) and data mining, and businesses often rely on clustering to segment customer populations into different marketing or user groups. Cluster analysis may be used in a range of business and non-business applications.

Steps for Making a Cluster Analysis

There are nearly as many ways to cluster data points as there are groups to segment them into. As such, there is no single process that represents the standard mechanism of cluster analysis. The following process, however, is a reliable set of steps you can use when clustering data:

1. Confirm the Metricality of the Data

For effective clustering, your data needs to have actual numerical values. This is because you will need to define the ‘distance’ between data points. So even if you are working with non-metric data (such as people’s names), you still need to define the similarities in a numerical way (such as by saying that individuals with the same name have a distance defined as 0 and those with different names have a distance defined as 1). 

2. Select Variables

Selecting the right variables is essential to producing relevant, usable cluster data. Perform exploratory research beforehand so that you have a clear idea of which variables to use. 

3. Define Similarities

As with selecting your variables, choosing and defining similarity measures to chart the ‘distances’ between your observations is key to producing a usable cluster analysis. You can define similarities in hundreds of different ways, so be aware of your options as you work with your data. 

4. Visualize Pairwise Distances

With the correct variables in place and your similarities fully defined, you can now begin to visualize your cluster analysis data. You can plot individual attributes as well as the pairwise distances on a histogram chart, with your classes represented as columns on the horizontal axis. Peaks within those columns may represent potential segments.

5. Choose a Method and Number of Segments

Again, there are many different methods one may use to cluster data. You may wish to try a variety of approaches until you find one that clearly represents actionable information in a clear and robust way. Cluster analysis is iterative, so be willing to work with the data until it starts to work for you.

6. Interpret the Segments

With your chosen method and number of segments, your next step is to get a clearer idea of the data points themselves and how they relate to one another. Make note of how the segments differ based on your variables. It can be extremely helpful to visualize these clusters using graphing techniques. 

7. Perform Ongoing Analysis 

With your core data visually represented and your individual data points more fully understood, the final step is to dig down deeper with increasingly robust cluster analysis. This may include subjecting your data to different subsets, distance metrics, segmentation attributes, segmentation methods, or numbers of clusters. By exploring multiple variations, you should be able to see how well your data holds up, how much overlap you have between your clusters, and how similar your segment profiles are across different approaches.

How to Interpret and Measure Clustering

Cluster analysis is based on the assumption that the lower the numerically-represented distance between items, the higher the similarity level—provided that you have a reasonable number of clusters to work with. You can use a silhouette coefficient score to calculate how healthy your clusters are by determining the average silhouette coefficient value of each of the objects in the data set. 

Measuring your clusters also heavily depends on the questions you ask regarding your initial data. Important cluster analysis questions include:

  • How will you measure the similarity between objects?
  • How will similarity variables be weighted?
  • Once similarities are established how will classes be formed?
  • How will clusters be defined?
  • What conclusions can you draw regarding the clusters’ statistical significance?

Advantages and Disadvantages of Cluster Analysis in Sampling

A key application of cluster analysis in cluster sampling. Cluster sampling divides an entire study population into externally homogeneous but internally heterogeneous groups, with each cluster acting as a miniature representation of the whole. The groups must be divided randomly, and then individual groups are randomly selected and every individual in that group is sampled. 

For example, cluster sampling allows researchers to study certain types of communities within the country without having to acquire subjects from hundreds or thousands of different locations. Instead, these communities are divided into similar groups and a random sample of communities is assessed. In this case, the randomly-selected subset represents the whole population. Another example might be an airline that chooses to survey all of the passengers on several randomly-selected flights every day to infer conclusions about their passengers as a whole population. 

Cluster analysis as a sampling methodology offers some clear advantages over more traditional random or stratified sampling. For one, cluster sampling tends to demand fewer resources and is more cost-effective. For another, cluster analysis may be more feasible while still providing a comprehensive view of an entire population. 

That said, there are also certain disadvantages that you should be aware of. Perhaps the biggest drawback is that cluster sampling is prone to higher error rates than many other sampling techniques; the results obtained are not always fully reflective of the population as a whole. Additionally, unconscious biases may seep into this sampling methodology creating biased inferences about the entire population.

Better Analysis with InMoment

If you’re interested in getting a clear picture of the similarities and differences across a data set, then cluster analysis may be the answer. But ensuring that your cluster data accurately represents your sample group and clearly expresses valuable information can be difficult. Understanding cluster analysis and cluster sampling methodologies and how best to interpret the resultant data will provide you with the insight you need to understand the associations between your objects. 

InMoment, the leader in people-oriented text analytics, can help. Built on industry-recognized metrics and real-time intelligence, InMoment provides the tools and support you need to find hidden insights in your data. For more information on data gathering and analysis, visit our Learning Hub.

Survey Methodology

When it comes to collecting data, one of the best ways to do so is a survey. Most companies put out surveys of some kind for customers and employees at different points. But there’s more to a survey than just a series of questions. In fact, surveys typically have a method behind them to gather specific types of data and to make them as effective as possible. But what is a survey method? What is survey methodology? Read on to learn about survey methodology and why that matters.  

What Is Survey Methodology? 

What is survey methodology? To begin, it’s important to distinguish between a survey methodology and a survey method. A survey method is the process or tool you use to gather information via a survey. For example, you might create an online survey with multiple choice questions, and that would be your survey method. A survey method can be qualitative or quantitative. We’ll talk more about survey method options and their pros and cons later on. 

Survey methodology, on the other hand, is the study of survey methods. It’s looking at all of the survey methods available and using applied statistical information to determine what methods give certain errors and where accuracy can be improved. Essentially, survey methodology studies sampling techniques and practices and determines the accuracy, so researchers of all kinds can improve their methods and get more accurate results. 

What Is the Purpose of Survey Methodology? 

So what is the purpose of survey methodology? Why do we have an entire field of applied statistics working on surveys? It’s important to understand why survey methods matter first. Survey methods are designed to help researchers and companies get information as accurately as possible. After all, the data you gather isn’t worth much if it’s completely inaccurate or riddled with errors that make it difficult to use. Survey methods are how you get data. 

Survey methodology exists to support survey methods. Survey methodology is all about studying the ways to improve the accuracy of survey methods, so researchers and companies can get the most accurate results from their surveys. It’s a field that exists to minimize errors—any deviations from your desired outcome—and help create data that’s as accurate to a population as possible. 

Think about it this way. The common stats phrase for setting up a survey is, “Garbage in, garbage out.” That means that if your method gathers bad data, you’re going to get bad results. The bad data can come from a variety of sources, but one major source is that your tool for gathering the data isn’t very accurate. Survey methodology’s purpose is to make those tools as accurate as possible. It’s what helps researchers and companies get great tools or methods to gather reliable data and get accurate results. 

Types of Survey Methods

Now that it’s clear what the difference between survey methods and survey methodology are, we can look at common types of survey methods available. 

Quantitative and Qualitative

Methods can include both qualitative and quantitative data, but what’s the difference? Qualitative data is descriptive data and more conceptual data. For example, if your survey is gathering qualitative data, you would want to collect quotes from respondents and try to look at the emotions and sentiments of your potential customers, rather than performing a statistical analysis. Qualitative data is the heart of data. 

Quantitative data is data that’s numerical—or quantifiable. When you perform a quantitative survey, you’re gathering information you can do a statistical analysis on; you want to know numbers. While qualitative data is the heart of your data, quantitative data is the bones and muscles; it’s what gives your data structure and support. 

Both quantitative and qualitative data are incredibly important. When you’re choosing to collect data, think about what you hope to accomplish with your data and whether you’re collecting qualitative data or quantitative data. That’s an important part of your survey methods. 

Structured and Unstructured

Another important part of your methods is the structure you choose. Some surveys are very particularly structured while some or more unstructured and allow respondents more liberty with how they answer and where the conversation goes. To determine how much structure you want, think about what kind of data you want at the end. If you want very specific types of data and quantitative data, you would probably choose a structured method that has people responding to exactly what you’re exploring. 

If you’re looking more at qualitative data, you might find it beneficial to take either route. On paper, a structured survey might be easier and get you the information you need. In an interview survey, you could go either way—or even strike a balance between the two—depending on if you’re interested in seeing where the conversation ends up going or in gathering data on something specific. 

Open Ended or Closed Ended Questions

Now it’s time to think of the methods for questions. In general, you can gather information from open ended or closed ended questions. Open ended questions are ones without answer options, a yes or no response, or a true and false response. These kinds of questions are typically geared toward qualitative data (but can be flexible, of course). Closed ended questions typically have respondents choose from some kind of option or require a one-word or one-number kind of answer. These questions are common for quantitative methods. 

Ultimately, a great survey may combine both open ended and closed ended questions to get a variety of data. 

Survey Collection Methods

The final aspect of your survey methods is the method of collection. There are many ways to collect data, but these are a few common ways with their advantages and disadvantages: 

  • Face-to-face
    • Pros: very personal, allows you to see non-verbal nuance, flexible for both structured and unstructured questions
    • Cons: can be time consuming to set up and takes resources to make happen
  • Online
    • Pros: easy to organize, can be easy to get large amounts of data at once, digital responses that are easy to analyze
    • Cons: could be subject to survey response bias, respondents may not complete the entire survey
  • Observations
    • Pros: simple to do and doesn’t require expert design, great for testing hypotheses
    • Cons: could affect the accuracy, no controlled variables
  • Focus groups
    • Pros: easy for qualitative and unstructured data gathering, get a variety of perspectives, may lead to salient ideas you haven’t considered
    • Cons: participants might not reveal their true thoughts, opinions of the respondents could be influenced by other participants

As you can see, there are so many survey methods to choose from to consider. And survey methodology is all about how to make these methods more effective. 

How to Write a Survey Methodology

When you’re going to use a survey, you can write out your methodology—or all the components of your methods and how effective they may be. Here are the steps to writing a survey methodology: 

  • Define your sample group and size (evaluate for accuracy against the population)
  • Decide on your methods and data collection method (while evaluating the effectiveness of those choices)
  • Design your survey questions and remember to keep in mind: 
    • The approach
    • Your time frame
    • Your method of collection
    • The wording of questions
    • Biases
    • (Evaluating each of these helps determine the accuracy of your methods)
  • Collect data
  • Organize and analyze your results

At the end of it, your methodology is all about thinking about and evaluating your accuracy with your chosen survey methods. 

The Bottom Line

Surveying can be a lot—especially when you not only have to consider your methods but also your methodology. There’s a lot to consider for data collection and analysis. But you don’t have to do it alone. InMoment—a leader in survey creation, collection, and analysis—is here to support you. Contact us today to see how we can help you with your survey methodology. 

5 Challenges Facing Your Customers and Brands, and What They Mean for Your CX Program

A great deal of customers and the brands that serve them are facing unprecedented uncertainties; understanding them is key to organizational success, delivering Experience Improvement (XI), and ensuring that your customer experience (CX) program is operating optimally. All of these obstacles affect both customers and brands to some extent. Because half the Experience Improvement process is knowing what these challenges are, today’s conversation addresses five of the most prominent ones that I’ve observed in my work as an experience program designer:

  1. Price Increases
  2. Efficiencies
  3. Off-Price/Discounts
  4. Shrinkflation
  5. Skimpflation

 Challenge #1: Price Increases

A plethora of international events, crises, and phenomena has produced steep inflation throughout much of the world, and no part of the supply chain has been spared these upticking costs. Brands have had to pay more to produce, transport, and store their wares, which means passing that cost burden onto their customers. I’m sure you can guess how that’s affecting customer experiences the world over.

Challenge #2: Efficiencies

This is another customer experience woe that affects both parties in CX interactions. Many companies have struggled to stay fully staffed amid the job market churn often called The Great Resignation, which translates directly to everything from longer customer wait times to reduced item availability. For brands, this has become an employee experience (EX) challenge that is formidable, but not insurmountable.

Challenge #3: Off-Price/Discounts

The events of the last few years (and their lingering effects) have resulted in a consumer demand collapse for many goods and services. This is an especially adverse problem for the brands that sell these goods, as they now have to offload them at a significant discount. For example, I discussed in a prior article how reduced demand for patio furniture left these goods gummed up in the supply chain. About a year on, a combination of sluggish demand and eventual delivery has resulted in a deluge of patio furniture that brands, frankly, have no room for. Steep discounts can benefit customers, of course, but on this scale they leave a brand’s bottom line weakened.

Challenge #4: Shrinkflation

You’ve probably seen this word plastered all over your local news recently; if not, it’s the media’s new favorite term for paying the same price for a good that is reduced in size or amount. Multiple brands have taken this approach to their customer experiences as a means of attempting to prevent cost increases, but as you can imagine, most customers aren’t thrilled that the same amount they paid yesterday yields less for them today.

Challenge #5: Skimpflation

This one is similar to both shrinkflation and the staffing woes I mentioned earlier. In essence, even when brands manage to keep employee churn low, they must still contend with the possibility that the service their retained employees provide has lost some of its quality. This results in an underwhelming customer experience much like the amount reductions discussed with shrinkflation. 

The Path Forward for Customers and Brands

It’s helpful to understand the territory your brand operates in, and these challenges constitute just that for many organizations in these strange times. However, there is more to the story: what are customers doing to cope with these and other challenges, and just as pertinently, what can brands do to respond in a meaningful way? How can they ensure that they’re displaying that empathy mentioned at the beginning of this discussion?

Click here to read my full-length point of view article on customer coping strategies and what your organization can do to address them. I’ve spent a great deal of time researching both of these CX elements over the last few years and am confident that those learnings can help you on your own Experience Improvement journey.

What Is the Difference Between Voice of Customer and Market Research?

A lot of folks believe that voice of customer (VoC) programs and market research mean the same thing—but they’re actually quite different! In fact, each discipline differs in purpose, design, analysis and outcomes.

However, even though they’re different, it’s important to point out that one isn’t necessarily better than the other—and brands need both if they want their customer experience (CX) programs to reach their potential.

So, with that in mind, let’s get into a quick primer!

Breaking Down the Difference Between Voice of Customer & Market Research

What Is the Definition of Voice of Customer (VoC)?

Voice of the Customer (VoC) is the process of gathering vital information regarding what customers think and feel about their experiences with a business.

How Does VoC Fit into Your CX Strategy

VoC programs are an essential part of any CX toolkit. They’re designed to fulfill many critical functions for your overall customer experience program, including, as their name implies, understanding customer needs. They’re also useful for understanding customer expectations, as well as what those individuals may want from you before even they know. This information can then be used to adjust operations, inform marketing efforts, and help your organization create both short- and long-term Experience Improvement (XI).

Not all VoC feedback comes from typical listening methods like surveys and focus groups, either. A lot of it comes from unsolicited feedback (website reviews, social media comments, etc). Unsolicited feedback is helpful because it gives customers a chance to express themselves entirely in their own terms, which may alert brands to problems and journey breakages that they weren’t aware of.

All of this boils down to the ability to not just capture individual and collective customer feedback, but act upon it. Taking action is crucial to Experience Improvement and building connective relationships.

What Is the Definition of Market Research?

Market research explores hidden relationships within industry data, collected by a market research firm, in order to predict and forecast future events and behavior within the market.

What Is the Role of Market Research in Your Business?

While Voice of Customer is all about feedback, market research takes a slightly wider lens by focusing on understanding the trends around your business.

Primary research is useful for testing new communications and services that your company wants to put out there, while secondary research looks at the dynamics and sizing of the marketplace around you. Conducting these types of research can help your company identify your target market, segment your customers, and identify growth opportunities.

Your company can supercharge its market research efforts by defining the population you want to target with a survey, then creating samples that ensure you’ll have a match. We’ve found that surveys like these are most effective when they’re blind, meaning that the customer or individual stays anonymous while taking them, and challenge you to do the same! This method is great for reducing response bias.

The Difference between Voice of Customer (VoC) and Market Research
This handy chart breaks down the differences between these two methods

So, Why Do You Need Both?

VoC and market research aren’t the same, but your CX program and your organization need both in order to truly understand your customers as people. That fundamental, holistic understanding fuels unforgettable experiences that build loyalty while also creating additional revenue! So be bold in your strategy and use both VoC and market research. Your customers will feel heard, your C-suite will be impressed, and the experiences you provide will be meaningfully transformed.

Click here to read our full-length white paper on why your brand needs both VoC and market research. Our very own Eric Smuda has spent decades in both fields and provides an in-depth look not just at why these disciplines are important, but how your organization can wield them effectively.

How & Why You Should Customize the NPS Follow-up Question

Net Promoter Score (NPS) is a simple and highly effective way to determine the happiness of your customers. This one rating — how likely are you to recommend <company> — gives you valuable business insights from the need to fix specific issues quickly, to long-term trends. But what about the NPS follow-up question?

That’s where the more actionable insight comes from, because the customer is able to explain the “why” behind their rating with an open-text answer that gives you the good, bad, and the ugly of their experience. 

By customizing your NPS follow-up question, you’re better able to gain the insight you need to improve your customer experience (CX) and increase Customer Lifetime Value (CLV). We have four simple ways you can approach creating the optimal follow-up question for your specific needs.

Read More…

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!

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