Voice of Franchisee

Earlier this year, InMoment hosted an XI Forum with two incredible speakers—both of whom run experience programs for franchisees. Steve Grossrieder, CEO of JAX Tyres & Auto, and Jess Gill, Chief Customer Officer for Craveable Brands, know exactly what it takes to keep franchisees inspired, and make sure experience programs stick across the organization. 

Here Are Your Questions Answered by the VoF Experts:

Expert #1: Steve Grossrieder, CEO and Managing Director at  JAX Tyres & Auto

Q: ​Your NPS at the franchise level is incredible. How do you train staff in the franchises to instill customer experience in all that they do, maximizing sales?

A: ​We hold best practice and networking sessions in each region with small groups of franchisees to discuss CX best practice and to show our main pain points and how to implement simple procedures to improve these. We also develop CX action plans for all stores under 75 NPS on a monthly basis which shows their detractor feedback analyzed, how they compare to the network and potential actions based on their individual insights to improve their NPS. Additionally, our service proposition is centered around our JAX inspection report—we focus our franchisees on this proposition to deliver our consumer promise to peace of mind driving and our sales naturally translate from identifying customer vehicle issues through the inspection process which is transparent and customer centric.

Q: ​How and what do you share with franchisees from a CX scoring perspective, and how frequently?

​All franchisees have access to their stores individual CX results including their stores NPS, channel performance, monthly comparison trend (compared to the network), as well as text analytics split by promoter, passive and detractor. They also have a case management section which shows customers who have asked to be contacted showing the JAX SLA time to review and resolve with the aim to retain their customers. 

Additionally, we share the monthly CX results via a monthly report and internal newsletter showing the ten highest and ten lowest scoring stores, top complaint trends and insights for that month as well as tips and best practices to implement to ensure a consistent experience across the network. We also have multiple digital screens displaying our CX results throughout head office (updated hourly) and our monthly NPS and a selection of customer feedback is displayed on our website and intranet for consumer and franchisee transparency.

Q: Please share more on how you managed to show a clear link between CX improvement and ROI or sales improvement? It’s often a challenge in many industries.

A: Initially this was a challenge; however we have been able to establish (with historical data) the clear link between a higher than average network NPS and the gross profit that these stores make above the network average. We now have clear examples of stores increasing their NPS and their increase in gross profit follows on with a two to three month lag period. NPS has now become a key gross profit lead indicator which we have demonstrated multiple times across the business and now do it store by store to promote culture change and customer centricity.

Expert #2: : Jess Gill, Chief Customer Officer at Craveable Brands (Oporto, Chicken Treat, Red Rooster)

Q: Which channels does Craveable Brands use to capture customer feedback? 

A: We use QR codes, email to loyalty customers, Digital Intercept (an InMoment application on the XI Platform empowering brands to capture real-time data from their website visitors) and customer panels.

Q: How do you win back your customer? How do you capture it? How do you let your customer know that your company is implementing their feedback? 

A: We win back customers by training staff (in person) that it is okay to own up to errors and to make them right, running our case management program. As for any feedback for the head office, that gets directed to the right people—for example, we made changes based on feedback to bring back our old nugget recipe, and we went back to each of those customers to let them know.

Q: How do you consider feedback through third party apps such as Menulog, Deliveroo, etc? 

A: Craveable Brands’ post-transaction survey asks about delivery partner feedback to feed back to them. The feedback collected by delivery partners remains separate from our VoC program today though we look to integrate to have one view down the track.

For more ideas on launching a successful voice of franchise program that actually benefits your business, check out our new paper: https://inmoment.com/en-au/lp/launching-a-voice-of-franchisee-program/

Calling Customer Support vs Cleaning a Toilet

Shep Hyken, a well-known customer service consultant, recently shared that 42% of people would rather clean a toilet than call customer support. This statistic actually didn’t surprise me given how often support experiences leave much to be desired. 

This got me thinking: Why is that the case when none of us would claim to enjoy cleaning a toilet!? And I decided that the reluctance to call customer support came down to three factors: 

  • Control 
  • Time to task completion 
  • And likelihood things are done right the first time

Let’s take a closer look at each of these factors—and how organizations can address them in their customer support initiatives!

3 Factors Impacting the Customer Support Experience

Factor #1: Control

Since I am the one cleaning the toilet, I have control over when and how the job is done and how well it is done. That is not often the case in the support experience. 

Yes, more companies and brands are trying to shift the customer service experience to a self-serve one, where the person needing support can find their own answers via the company’s internet site, user forums, or at worst a chat session. But let’s be honest, these moves are not being done to put the customer in control of the experience; they are being done to save the company money by shifting the experience to lower cost channels and reducing the labor costs in the call center. 

Unfortunately, because these self-serve support initiatives are motivated by a cost-savings lens and not a customer experience one, they are often not executed very well. People can’t find the answer they need online, or the answer doesn’t make sense or completely solve their problem. And chatbots are often effective at solving very simple queries, but not complex ones.

The other reality is that consumers want to interact with a live person. According to CDP.com, 64% of consumers say access to live people would significantly improve customer experience. So while shifting the support burden to the consumer or low-cost (non-human) channels may save the company money, it is not engendering customer loyalty when that is not how the consumer wants to interact with your company.

Factor #2: Time to Completion

As mentioned, no one enjoys cleaning a toilet, but if we are honest, it takes no more than a couple minutes, less than 10 for even the dirtiest of them. But how many customer-support experiences take only a few minutes? 

It often takes you at least a few minutes to get through the automated phone tree, only to be told your hold time is much longer than a few minutes! While some brands are now using automated callbacks  that adds some convenience in that you don’t have to actually wait on hold (ironically being told how important your call is over and over and over again), how likely is it that you get a call back when it is convenient for you? It’s more likely that you have moved on to other tasks only to be interrupted by that call.

Factor #3: Getting Things Done Right the First Time

Finally, we arrive at the last factor: first-call resolution (as call center leaders call it). I want you to think back to your last few call center interactions: What percentage of the time is your issue really resolved on the first call, with no transfers and no additional hold time? 

Too often the first agent you speak with is either brand new and not trained properly, or the company’s knowledge base does not provide them quick access to the answer to your issue, or they are not empowered to resolve your issue without “supervisor approval” or a transfer to a manager.

There are several problems with how most companies measure first call resolution:

  1. It is not measuring total effort to resolution. Most likely, you have already searched the website or FAQs or user forums and possibly tried the chatbot before getting to a live agent. So it is measuring the call, but not measuring customer time and effort.
  2. If it is measured based on agent data entry, it is not measuring consumer confidence that the issue was resolved and it is making that judgment likely well before the customer has experienced the solution and feels confident it is resolved.
  3. If it is measured based on survey responses, it is not representative of the total customer base, but only those customers who completed the follow-up survey, a small percentage of the customers who contacted customer support.

My colleagues at InMoment often hear me say “every call to the call center is a broken customer experience somewhere upstream.” Given that, your call center is your safety net and last chance to “save” the customer and ensure a continued relationship and extended lifetime value. 

Yet, too many companies see their call center as only a cost and something that can be managed or minimized by reducing headcount and shifting to lower cost channels. This is a financially driven, inside-out view of customer support and not an outside-in, customer-centric approach. 

If companies truly want to reduce the cost associated with customer support, learn from these calls and fix the upstream issues that are creating the need for the calls in the first place. 

Fewer issues, fewer calls, happier customers, better financial outcomes.

How to Build Customer Trust and Loyalty

Two people and a dog inside of a business showing customer loyalty.

Many companies underestimate the value of customer trust and loyalty when it comes to driving higher revenue growth. It might sound counterintuitive, but convincing existing customers to return is more important than gaining new ones. This is because the cost of finding new customers is far higher than the cost of selling to existing customers. In fact, returning customers spend 67% more than first-time buyers.

It’s clear that executives need to put customer loyalty at the center of their company’s values, but how do you actually go about doing building customer trust and loyalty? Let’s jump right in!

3 Ways to Build Customer Trust and Customer Loyalty

  1. Create Personalized Experiences to Build Trust
  2. Go the Extra Mile to Listen and Understand
  3. Quality, Quality, Quality

Action #1: Create Personalized Experiences to Build Trust

Throughout the customer journey, your brand should meet customers where they are. The more personal you make the customer experience, the more trust you’ll cultivate. 

For instance, in the pre-purchase stage, in-store employees should have substantial knowledge about products and understand what customers need. Employees should be trained to create positive interactions from the beginning all the way up to the final moment of purchase. Asking small questions like if a customer found everything they needed—and stepping in if they didn’t—can make a huge impact. Little actions like that help add a nice personal touch to a customer’s experience—and lead to a stronger level of trust!

Action #2: Go the Extra Mile to Listen and Understand 

Trust often leads to loyalty, but your brand has to make the first move. To cement a longstanding relationship of trust, your business needs to show loyalty to customers first. 

An effective approach here would be to engage with and respond to customers, because engaged customers are more likely to promote your company than unengaged customers. Actively responding to customer questions, comments, and complaints can grow loyalty by putting a human voice to a brand. 

One best practice for engaging with customers in this way is to design an open communication and feedback channel. Of course, we recommend utilizing not just a help center as a method to reach out, but any adequate resource, from employees on the front line to digital surveys. Additionally, you should look to other indirect forms of feedback to understand your customers such as review site data and social media mentions.

Action #3:  Quality, Quality, Quality

At the end of the day, even if their customer experience was amazing, if the product doesn’t meet a customer’s expectations, all that work you did to build trust and loyalty is in vain. Customers expect value for what they pay for and no amount of sales gimmicks can hide the truth of your product, so it’s key to know customers’ expectations and develop your product/service to meet or exceed that. After all, loyal customers are coming back for a quality purchase; the positive customer experience is an additional element encouraging that return. 

Your customer experience platform is essential to identifying friction points and remedying them to improve customer trust and customer loyalty. We discussed in the section above how it’s important to keep tabs on what your customers are saying about their experience. Once you’ve collected all this feedback data across every channel, you can leverage your customer experience (CX) platform to analyze all that customer feedback and identify the areas in your business that need some attention. Check out this video below to learn how global banking giant, Virgin Money, worked with InMoment to understand the most impactful moments in the customer journey.

Now that you’ve learned how to build customer trust and loyalty, read our eBook to learn about how that trust and loyalty can drive cross-sell and upsell opportunities!

Simple Random Sampling

If you are an organization with thousands of customers, surveying your entire customer base can seem like a daunting task. The likelihood of all of your customers (whether they number in the thousands or in the hundreds) answering a survey is slim to none. But, customer feedback is critical to driving Experience Improvement and growing your CX program. So, with such slim odds, how are you supposed to trust the customer feedback you do get? 

Simple random sampling is the perfect solution to this problem. Sampling methods such as simple random sampling allow businesses to get the data they need to make decisions without having to go through any unnecessary work. The goal of using simple random sampling is to get a small group that is unbiased representative of a larger population.

What is Simple Random Sampling and Why Is It Important?

A simple random sample is a selection of participants from a population. What makes this sampling method different is that each participant has an equal probability of being selected.   

Simple random sampling is important for many reasons. First, the subgroups from your population will be unbiased. Since they were chosen at random, they do not have any predisposed bias as participants, and they do not suffer from researcher bias. 

It is also important because these unbiased groups allow businesses to get data that is reflective of the entire population, without actually having to survey the entire population. 

What Are the Advantages and Disadvantages of Simple Random Sampling?

Many businesses prefer simple random sampling for its simplicity and lack of bias. It is also the easiest form of sampling. You don’t need to be a data analyst in order to perform this sampling method; and the data you receive can be applied to the whole population. 

The biggest disadvantage to be aware of is researcher bias. Researcher bias occurs when the researcher conducting the sampling selects participants to be in a subgroup based on their personal biases. This can be easily avoided by including multiple forms of random selection in your sampling. 

How Do You Perform Simple Random Sampling?

Simple random sampling is the perfect tool for a company looking to get an idea of how its entire customer base feels about a certain subject. Let’s say that you work for a nationwide retailer, and are interested in finding out how your loyalty members feel about a new selection of loyalty perks that you are considering to develop. 

You could go into the database that has a list of all of your loyalty members or, in this case, the list of your population. After assigning each member a number, you could use a random number generator to randomly select the number of participants you have chosen for your sample size. 

This subgroup of members, chosen at random, can now be surveyed. Their responses can be analyzed and can also be viewed as being representative of your entire member base. 

Sampling With InMoment

If you’re interested in understanding your customer base without having to survey each and every customer, then simple random sampling may be your answer. But understanding that data, what it means, and what to do with it moving forward can be difficult. 

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 and look at how our data studios can be beneficial to your business. 

Your Top 3 ROI Questions, Answered

ROI Questions

Imagine if you were still operating your business in the same way you were in 2019. Total nightmare, right? Your customer experience (CX) program, like your business, needs to be able to grow and evolve to prove a return on investment. If you’re like the majority of CX practitioners (CX Network’s “Global State of CX” report shows that it is the second highest concern for CX practitioners), you likely have quite a few ROI questions.

In our over two decades of experience helping the world’s best brands positively impact their bottom line with Experience Improvement, we’ve heard quite a few of these ROI questions, and have determined the strategies at the heart of a profitable program. In order to achieve true ROI, you need to take an integrated approach to experience by breaking down data silos and creating one ecosystem of data. 

All of your customer data needs to exist in one place, where it can be accessed from anywhere in the organization, meaning that the game changing insights you need to acquire new customers, keep the old ones, expand customer lifetime value, and cut inefficient or costly processes are all in one place.

InMoment recently held a webinar with representatives from Forrester, an independent market research firm, to give you the answers you need about your top CX ROI questions. InMoment’s Principal CX Strategist Jim Katzman and Forrester’s Senior Analyst Judy Weader discuss showing the value of your CX program, designing digital experiences that make your business stand out, and setting your brand up for success. Let’s dive in! 

Your Top 3 ROI Questions

ROI Question #1: Why Is Showing the Value of Customer Experience So Difficult?

Showing the value of your CX program can be a daunting task. How are you supposed to link improving experiences back to financial gain? Well, the truth is, most CX professionals don’t know the right mechanics they need to perform in order to show ROI through their CX program. 

In order to showcase the ROI of your CX program, there are going to be calculations involved. But, don’t be intimidated by that. It isn’t as complicated as it may seem. 

Let’s take a look at a call center for an example. At every call center, there is an average cost per call. For the sake of simplicity, let’s say our call center has an average cost per call of $5. If this call center receives 100 calls per day about an identified pain point (let’s say it’s a confusing process), you would be able to take that customer feedback and turn it into an actionable insight which would clarify the process, thus relieving the pain point. 

By taking action, you may be able to turn 100 calls per day into 80 calls per day. 20 less calls per day at $5 average cost per call is a $100 of daily savings. Just like that, we have proved that having a CX program that creates actionable insights provides a return on investment to the organization. 

Showing the value of your CX program is easiest when you are able to turn actions into numbers. By making decisions based on customer data, are you increasing revenue? Decreasing costs?

ROI Question #2: How Are Business Designing Digital Experiences That Make a Difference?

When developing a digital product or service, it’s important to think about the context that your offering will be used in. Think of your favorite airline, or an airline that has developed a “good” mobile application. The reason these apps succeed are because they were designed with the knowledge that when you check-in for a flight, you aren’t going to haul out your computer. These airlines knew it would be easier and more convenient for their customers to be able to check-in for a flight when they were on the go. 

When you develop your products and services around your end customer, you’ll be able to create digital experiences that enrich peoples’ lives and generate more adoption, engagement, and advocacy.  

When designing and developing your products, you also need to remember to design for accessibility. If you aren’t thinking about accessibility in your products, you are missing out on a huge opportunity. There are over a billion people in the world that are disabled. Whether it be different font sizes, text-to-speech options, or modified touchscreen shortcuts, designing for accessibility is something that needs to be done throughout the design process. It is not something that can be bolted on after the launch date. 

ROI Question #3: What Three Things I Can Do to Set My CX Program Up for Success?

  • Have a Good CX Vision

The optimal CX vision for your organization should be derived from your brand vision. Your brand vision should answer the question “What do I want my brand to be for the market?” Consequently, your CX vision should answer the question “What do I want my CX program to be for my customers in order to support my brand vision?” 

  • Build Out a CX Strategy

Developing a CX strategy can seem like a long, intimidating process. But, it is important to remember that the goal of your CX strategy is to bring your CX vision to life. If we take one more step back, your CX vision should reflect your brand vision. So, at its core, your CX strategy should align with your business goals in order to bring that brand vision to life. Using your business goals as a base, you will be able to develop an effective, focused CX strategy. Your motto should be to “design with the end in mind.

  • Align Your Priorities

You want to make decisions that are grounded in customer understanding and current business initiatives. When thinking about which initiatives to go after first, take a moment to think. What matters most to the business? What are the goals that your business is trying to achieve now versus what they hope to achieve later? By prioritizing your CX initiatives with your business goals, you will create an effective CX program. 

Moving Forward

As you look forward and adopt these principles into your own ROI strategy, don’t stress about being perfect. CX programs are ongoing, ever-changing, and constantly evolving assets to your business. There is no set “right” way to utilize your CX program. 

Our recommendation? Start with a quick win—a straightforward project you can measure the success of. 

An ROI Example from an InMoment Client

A few years ago, one of our clients, a national chain restaurant, was looking for a new way to get in touch with their customers. They already had an internal assessment system that was used as a comprehensive assessment of performance in front- and back-of-house operations and policies related to Food Safety, company standards, and guest experience (e.g., quality, order accuracy, speed of service, staff friendliness, cleanliness, and team engagement). 

With more than 13,000 of these assessments completed each year, the results helped drive continuous improvement in quality, operations, and brand standards—but they lacked a view into the guest perspective. 

This company chose InMoment as its CX optimization partner based on its ability to interface audit data with CX data. By bringing audit and guest feedback data together, InMoment’s prescriptive analytics automatically generated two improvement priorities for each location. The integration model takes into consideration both guest experience and audit score, and creates priorities tied to the greatest return on investment: where this organization should put more time, energy, and effort. 

After implementing these data-driven improvements using the InMoment and internal audit correlated system, the organization’s restaurants saw a significant increase in all key metrics in just eight months:

  • 34% in OSAT
  • 33% in Friendliness
  • 22% in Product Quality
  • 22% in Cleanliness and Facility 
  • 19% in Speed of Service
  • 12% in “Make it Right” (if an order had a mistake, was it corrected?)
  • 3% in Order Accuracy 

By focusing on just two improvement priorities at each location, this organization was able to completely transform its relationship with its customers. Starting with small, measurable initiatives is a great way to kickstart your CX program. These small initiatives might even have results that expand further across the organization than you would expect. 

If you want to learn more about extracting ROI from your CX program, watch the full webinar here! 

What is CX design?

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? 

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

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. 

Price Increases

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.

Retail Banks

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!

Human Expertise

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.

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