We are regularly asked by clients what the difference or relationship is between Customer Experience (CX) Analytics and market/customer research. Should I invest in data solutions to monitor and improve CX or should I just ask my customers what they think? Or should I do both?
We sat down with Theo van der Steen, founder and director of sister company Underlined about his vision and experiences in this area. Underlined specializes in CX Analytics and, with its experience, frameworks and tooling, enables companies to better serve customers and design customer interaction processes effectively and efficiently from continuous analysis and monitoring. The projects Underlined does often involve collaboration with market and customer research agencies. However, the client does not always know the difference or what to hire one or the other for.
In this article, we provide our common experiences, vision and view on how you should handle these two forms of customer insight as an organization.
Traditional market research and data science?
If we look at the world of market and customer research we see, on the one hand, the more “classic” agencies as traditionally united in the MOA (the expertise center for marketing insights, research and analytics). They base their insights primarily on customer research. In addition, we see the movement from the more technical and consulting-oriented companies that, with the use of data and data science, are extracting insights from customer interactions and customer data.
Data science in light of customer behavior, has always been focused on “understanding” (customer) behavior and continues to develop at a rapid pace. Partly because of technological developments, the emphasis in this regard is increasingly on “snapping” and less on collecting and organizing such customer data.
In the future, data science will increasingly evolve into a “brain” that provides interpretation and tries to make sense of everything. This vision stems from the work of Piek Vossen, professor of Computational Lexicology at the VU Amsterdam, such as his project Newsreader and the developed History Recorder that “reads” the news every day, identifies connections and records it historically.
Market and customer research is quite a broad term….
It is somewhat dangerous to put market and customer research under the same heading. If we look at the MOA, for example, we see the growth to seven areas of expertise including also a number that were created by movement in the field from technology, but also, for example, from laws and regulations.
What we see in practice with our clients is that market and customer research is primarily used for customer sentiment measurements and floors on them. And following and understanding market and market developments, for example, when it comes to brand and image. Many of these surveys are based on the large panels the major players have rigged to provide such insights. When it comes to brand, image and market trends, data science and CX Analytics is not much of a substitute. However, when it comes to understanding customer interactions, behavior and sentiment, we see a different movement. On that front, traditional customer research has a number of drawbacks.
Pitfalls of market and customer research
Much customer interaction/customer journey research takes place at the end-point of customer journeys. This type of survey also often takes place periodically to have sufficient numbers of respondents. What you want, however, is to build insight into the entire customer journey, what goes right and wrong there, and how to address it immediately and in the right place. Research often cannot provide this detailed information and requested speed. Or at least not at a reasonable and recoverable cost. Something you can do much better and more efficiently with continuous and fine-grained measurement and monitoring based on data and data science.
In addition, a disadvantage of much customer research is that it is based on eliciting what customers think or think. After all, we know from other studies that people often say they are going to do something different than what they actually end up doing. Only when we are able to actually measure behavior and if possible link it back to research can we determine the true power of research.
With developments in the field of neuromarketing research, also known as market research in the brain, we do see the potential for this gap to be filled, by the way. Even then, we see that new technologies are making the old methods of research obsolete.
Data science applications on customer contact center data (conversational analytics), for example, are also increasingly powerful for finding out what resonates with customers and where things can be done differently and more efficiently. By applying AI to call recordings, agents no longer have to do capture and interpretations. With this, organizations are directly able to optimize customer experience and service processes without asking customers.
The question remains, however, is new technology replacing more traditional market research?
Traditional market research and data science – friend or foe?
While talking, the conclusion forms that the combination of the two worlds is the most powerful. Systematically measuring and monitoring customer data and interactions at all points in the customer journey creates a complete and up-to-date picture of what customers are experiencing and doing. Qualitative research can then be used to add depth to further optimize the customer journey.
In doing so, we see that new technology is also making more traditional ways of research more efficient, effective and reliable. And that interpretation and application of the insights, requires consulting skills that traditionally lie with the consulting firms. As a movement in the market, then, we see data science, research and consulting organizations increasingly converging.
What choices do you make as an organization
To make the right choice as an organization in building insights and continuously monitoring customer experience, the following three principles apply:
- Start by establishing purpose and objectives
- Without purpose, no direction. Concrete goals related to drivers that enhance the customer experience should align with higher-level business goals. This is necessary for targeted measurement and improvement. So as to avoid a proliferation of well-intentioned measurements and initiatives.
- Make a high over business case
- Once the goals are clear and we know what activities will have an impact, make a concise business case.
So what efforts are we going to make and then is that commensurate with what we think we’re going to accomplish with that. And does this apply to all customers or only to specific groups. - Consider not only short-term effects but also longer-term benefits. For example, keep on board a group of customers who are very valuable over time. Dare to look across several years.
- Without trying to think out a business case in depth, an initial exploration of costs and benefits is often already very useful to make sense of certain expenses around research.
- Do and learn – make short-cycle, fine-grained improvements. Effects and gains can be made if you break down the customer journey into small pieces and make improvements in them.
- If you are able to combine data science and research purposefully, with sound investment and continuous learning, you will make a difference for your organization
- Once the goals are clear and we know what activities will have an impact, make a concise business case.
If you would like to know more about this topic, please contact us. We are happy to talk further with you about which approach is best for your situation.
Kees Groenewoud
