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Tagged: market research

Customer Segmentation Pitfalls and Potholes

March 9, 2017

Customer segmentation can be an immensely useful tool in getting actionable insights from your customer research. From those insights, you can devise strategies to improve the customer experience, because you have a more specific understanding of what customers want. But segmentation is far from simple.

To get the most out of it, you need to understand a few things about the art and science of conducting customer research. That’s just what CSP has been doing for more than thirty years, so we thought we’d share some of our pointers.

What Can Go Wrong with Customer Segmentation

customer segmentation

Methodology Mishaps

What does your business have in common with the Large Hadron Collider – the massive facility in Switzerland that smashes atoms together to better understand physics? You both rely on the Scientific Method. Or at least, you should (and they certainly should).

Any good research, whether studying customers or plants or animals or atoms, is based on these standards, which have been the guiding principles of science since the mid-1700s. To get good results out of your research, your methods must be scientifically sound, unbiased, and verifiable.

Research is not just conducted, but designed. That means knowing how to create a sound and testable hypothesis, conducting the right kind of ‘experiment’ to test it, and verifying your results with the proper vigor. Get any of these parts wrong, and the rest unravels from there.

Contaminated Sample

Sometimes research starts from scratch, but often, it relies on parsing data you already have on hand. That might include one or more customer databases or Customer Relationship Management (CRM) tools. These databases must be meticulously maintained so as to avoid contaminating the results. Examples of database disruptors include duplicate entries, incomplete entries, “dead” entries (meaning, invalid or out-of-date information, such as dead email addresses), and false categorization.

A slip-up here or there may seem like not a big deal, but it can lead to disasters in customer communication. For example, in 2011, the New York Times erroneously sent out a special discount offer to a small list of 300 recent ex-subscribers to entice them back – except that it was delivered to 8 million contacts, including many current subscribers who suddenly became aware of a discount they were not being offered. Things like this can happen when database entries are not correctly or clearly identified and grouped.

You Know What They Say About Assumptions…

Everyone has conscious and unconscious biases and makes assumptions based on those biases – it’s only human, and it’s rarely malicious. But such assumptions, no matter how logical or benign, can still affect the viability of research results and the value you get out of them.

A good example of where you see this happening is in discussions of the different generations – Boomers, Gen X, Millennials, and so forth. Many sweeping generalizations have been made about each group, some supported by sound research, and others just created by socialization. Eye-grabbing headlines and op-eds easily filter through to form your beliefs about these potential customer segments.

When that happens, you are more prone to leaping to the wrong conclusion. Don’t assume that seniors don’t use mobile banking because they’re technologically illiterate, or that lower-income customers don’t have smartphones. Any conclusions derived from research must be supported by that research.

It Pays to Have an Expert on Your Side

Done well, customer segmentation can lead you to valuable insights and an improved customer experience. Done poorly, it can just as easily lead you astray, or not lead you anywhere at all. If it were easy, businesses like CSP wouldn’t need to exist – but luckily, we do. To learn more about how we guide businesses in using their data to provide stellar customer service, contact us


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SOURCES

New York Times email mishap
Unsupported assumptions

What is Customer Experience Research?

March 6, 2015

Traditionally, Customer Experience Research falls into two main categories.

In the first category, there are market research firms that take an academic or scientific approach to collecting data and presenting the findings. These providers emphasize the purity of their data and the rigor of their methods and processes for collecting that information.

In the second category, there are data collection firms that specialize in gathering, storing, and organizing vast amounts of data from a variety of sources. Through their proprietary systems and tools, they make their findings accessible and digestible to the end user.

What does customer experience research capture?

The two metrics most important to customer experience management are customer satisfaction and customer engagement, which exist on a continuum and influence each other in both directions.

Customer satisfaction is an immediate measurement of an experience, from something as small as an interaction with a customer service representative to the overall feeling a customer has that his or her expectations and needs are being met. This is arguably the starting point for all customer research.

Customer engagement is what keeps customers coming back. It captures the long-term equity that is built on satisfying experiences by measuring things like loyalty and how likely a customer is to refer others to their preferred brands and businesses. In this way, it’s a more useful measurement than simple satisfaction: customers who are strongly engaged over time are more willing to overlook or tolerate the occasional less-than-satisfying experience.

A great example of this comes from the consumer technology industry. Brands like Apple and Google each have dedicated, loyal audiences that will continue to buy their products and tout their benefits to friends and family, even when the products themselves fall short of 100% satisfaction (think: buggy software releases or smartphones so thin they bend in your back pocket). This is the kind of engagement every brand dreams of.

The Journey From Data to Information to Knowledge

data information and knowledge

Both the academic and data-collection approaches to customer experience research have value. Market research can reveal trends, insights, and patterns across large populations and broader spans of time. Data collection, meanwhile, has grown so sophisticated as to merit its own industry, aimed at helping the everyday business manager access intelligence about their customer – because it’s unlikely they have the expertise or time to sift through it all themselves.

Both methods also have their limits. Statistical research may be useful in an ideal world where all customers have the same expectations and needs, and all businesses face the same challenges in meeting those expectations. But in a real-world setting, the insights garnered from this research often ends up “watered down” and are unlikely to apply to each unique business or brand the same way.

It’s not unlike the idea of the self-help book, which can be a useful way to talk about people in general, but won’t always apply on an individual level. You can do everything “by the book” and still fall short of your goals if the book you’re going by doesn’t account for the nuances of your business or your customers.

In turn, data collection is exactly what it sounds like: collecting data and presenting it as information. But turning that into knowledge that you can act on? That part is up to you. These firms often step out of the picture at that point, leaving you to figure out how that information factors into your strategies and tactics, what merits your attention and what doesn’t, and what steps come next.

Bridging the Gap Between Research and Reality

The shortfalls of traditional customer experience research are how businesses end up thinking they know their customers, without actually knowing them. There’s a break in the process that prevents them from getting to that next level of knowledge and using that knowledge to improve their customer experience.

In our 20+ years of customer experience research, CSP’s guiding principle has been to not only gather and present the information, but to then guide our clients in creating the roadmap to a better customer experience based on a thorough understanding of their unique customers.

Why should anyone have to figure this out from scratch? CSP has seen it all before, and we know what works and what doesn’t. Our experts are flexible enough to adapt to any given brand or business with a methodology that’s personalized every step of the way. Your specific questions about your customers, your market, and your competition are built right into the program, along with ongoing support, tools, and coaching to help you define and achieve your goals.

This level of customization and personal attention is hard to come by with traditional research models, but we believe it’s the key ingredient to successful customer experience management. We’re not passionate about data – we’re passionate about improving the customer experience, full stop.

For more information about CSP’s customer experience research methodologies and the programs we build to support them, contact us today by phone at (402) 399-8790 ext:101, via our website, or on Twitter @csprofiles