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Understanding the Customer

Sogeti Labs
December 14, 2016

I have always been a keen believer in interdisciplinary research and cross-over solutions. It is clear that combining the perspectives and insights of various specializations leads to better results than each discipline can achieve on its own. That’s why I am very excited about a research project that I am in the process of launching. The goal of that research is to provide customers with a better experience by increasing the quality of the customer journey.

To improve the customer journey, both insight into the progress of the actual customer journey and knowledge of the way the customer experiences the journey is required. Insight into the customer journey can nowadays be based on the registration of digital interactions, such a emails, tweets, chat sessions, app usage and website visits. Modern business intelligence techniques can derive a lot of information from these sources, but they do not regard the complete customer journey as a whole. As for the customer experience, this is usually retrieved by asking the customer directly, like with the net promoter score (NPS). However, this is not very trustworthy. Besides, customers like me are getting fed up by constantly being asked to complete a survey, however, brief it may be. Thus, both with regard to the course of the customer journey and with regard to the customer experience there is a need for better measurement instruments with more predictive power. In the past decennia, a number of research technologies and methods have been developed that offer parts of the solution. However, the full picture still eludes us.

Process mining offers insight in the course of business processes by analyzing the data registered in the supporting IT systems, such as ERP systems. Though process mining became great in the area of internal business processes, we could also regard the customer journey as a process. And apply process mining to it. There are some differences, however. The customer journey is a process that is not controlled by the organization, but by the customer. And it is not supported by a traditional ERP system, but by websites, social media and email. Which contain a lot of unstructured, textual information. How can this be translated into the structured event logs that process mining needs?

Which is where text mining comes into the picture. Text mining originates from computational linguistics and studies how to automatically extract information from texts. A recent research topic is to extract timelines from texts by taking into account references to past, current and future events. Combining this with process mining will be a huge leap forwards, enabling us to turn an unstructured heap of messages and mouse clicks into a process with a clear order of steps and experiences.

These, however, are technical disciplines. If we want to start understanding the customer, we have to include social expertise. That is why we bring in social psychology. Social psychology teaches us how to translate the motivations of customers into predictions about future behaviour. Motivations that are derived with the aid of text mining and related to the customer journey progress with the aid of process mining.

Process mining, text mining and motivation mining, as fellow researcher Philippine Waisvisz coins it, combined, help us understand the customer. However, if we sincerely want to increase the quality of the customer journey, we cannot but pay serious attention to matters of privacy and integrity. Usage of digital customer journey data must comply with privacy laws. But it goes further. If organizations really want to better serve their customers, they will have to treat customer generated data with respect and in a manner that is not contrary to the wishes and intentions of that customer. At the moment there are no clear ethical guidelines how to deal with this. That’s why we find it extremely important to add corporate integrity into the equation. We see it as our challenge to design integrity into the customer journey analysis tooling.

To really understand the customer and turn this understanding into a better customer journey, we cannot but combine the strengths of new techniques with social insights by bringing together researchers from the different fields and together start working on this thing called understanding the customer. My conviction is: if you want a good solution, take care to engage enough different perspectives. If you want a sustainable solution, ensure that you engage the integrity specialist and incorporate privacy by design, not as an afterthought.

About the author

SogetiLabs gathers distinguished technology leaders from around the Sogeti world. It is an initiative explaining not how IT works, but what IT means for business.


    4 thoughts on “Understanding the Customer

    1. Fasciniating blog, Marlies. Thanks!
      May I add another perspecive to this: Internet of Things.
      Next to text mining I think IoT can potentially give a huge amount of information on customer behaviour. Especially when physical movements are part of the customer journey. Combining that with social psychology and predictions would be very interesting.
      I am curious to know if you see the added value of IoT here.
      By the way: this only contributes to your conclusion that privacy and corporate integrity should be incorporated in the design.
      Hope you will keep us updated on the progess and results of this research.

    2. Great insights, Marlies. I also believe that only measing the NPS is definitely not enough. When it comes to collecting feedback from your users I was writing a blog post earlier related to improving mobile apps (and related services) based on collecting feedback from different sources. Of course some of the “feedback collection methods” that I have mentioned could also be applicable for other touch points in the customer journey. At the time when I was writing my blog post I didn’t mention the NPS at all ….

    3. Hi André, Thomas,
      Thanks for your comments. I totally agree that IoT also enters into the mix. The fascinating question for me is how we can mix all these different sources with the different analysis mechanisms and the different theories into a sustainable and ethically sound instrument. And I am convinced that if we set ourselves such an ambitious goal, working on it together from different disciplines, we will learn a lot on the way that will be applicable in other day-to-day decisions as well.

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