Customer journey analytics versus customer research

We are regularly asked by clients what is the difference or relationship 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 serve customers better and set up customer interaction processes effectively and efficiently from continuous analysis and monitoring. The projects Underlined undertakes often involve collaboration with market and customer research agencies. However, clients don't always know the difference or what to engage one or the other for.

In this article, we provide our common experiences, vision and image 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 consultancy-oriented companies that, with the use of data and data science, extract insights from customer interactions and customer data.

Data science in the light of customer behavior, has always been aimed at "understanding" (customer) behavior and is still developing rapidly. Partly due to technological developments, the emphasis is increasingly on "getting it" and less on collecting and organizing such customer data.

In the future, data science will increasingly develop 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 place market and customer research under the same denominator. If we look at the MOA, for example, we see the growth to seven areas of expertise, including a number that have arisen due to 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 mainly used for customer sentiment measurements and subsequent investigations. And to follow and understand market and market developments, for example when it comes to brand and image. Many of these surveys are based on the large panels that 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. In that area, 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 research also often takes place periodically to have sufficient numbers of respondents. However, what you want is to build insight into the entire customer journey, what goes right and wrong there and how to address it immediately and at 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 asking what customers think or think. After all, we know from other research that people often say they are going to do things differently than what they actually end up doing. Only when we are able to measure actual behavior and if possible feed it back into 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 closing this gap, by the way. Then, too, we see new technologies making 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 arranged differently and more efficiently. By applying AI to call recordings, agents no longer need 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 both worlds is the most powerful. The systematic measurement and monitoring of customer data and interactions provides a complete and up-to-date picture of what customers experience and do at all points in the customer journey. Qualitative research can then be used 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 consulting firms. As a movement in the market, therefore, 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 the purpose and objectives
  • Without purpose, there is 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. In order 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 achieve. And does that apply to all customers or just specific groups.
  • Consider not only short-term effects but also longer-term benefits. For example, keep on board a group of customers who will be very valuable over time. Dare to look over 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 improvements in a short-cycle, fine-grained way. 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.

If you would like to know more about this topic, please contact us. We would be happy to talk further with you about which approach is best for your situation.