Data-Driven UX: method applied to banking and insurance

The banking and insurance sectors have long been forerunners in advanced uses of data (algorithmic trading for banks, risk evaluation for insurance), so it is assumed that they are less subject than others to the risks that arise from the arrival of digital-native players.

However, there are many recent examples that illustrate the growing power of new actors:

  • In April 2020, Alan, the French insurance start-up, announced that it was raising €50 million to continue the digitalisation of the health insurance sector.
  • On the European Insurtech scene, Swiss start-up wefox, now located in Germany, is positioning itself as a major competitor with total funding reaching just over $265 million.
  • On the B2B side, new players are also emerging as important partners for the major insurance companies. For example, Shift Technology is specialised in managing insurance fraud and has raised €88 million.

Banks and insurance companies have the advantage of a relatively captive audience and a significant volume of data that allows them to adapt the user experience at a very fine level. The main sources of economic growth are upselling and cross-selling to clients the companies already know.
However, these two sectors are not similar in every way: while banks have a near-daily relationship with their clients, needs of insurance clients (outside health insurance) are more context-driven and related to specific claims.

While the order is not totally upended, as shown by the studies from Colombus Consulting, ‘Digitalization & Customer Experience in Retail Banking in Switzerland’ and ‘Digitalization & Customer Experience in Insurance in Switzerland’, digital banks and insurance companies stand out by the experience they offer and the relevance of their websites. These players’ arrival on the market and their growth are forcing historical players to adapt.

While the use of data has largely been democratized in recent years, this process of digitalization accelerated particularly after the first wave of the COVID-19 pandemic crisis. In a context where exchanges with customers are not as easy due to the lockdown measures, data collection has proven to be a strategic issue in recent months. To talk about digital data, especially in the financial services sector, is to open Pandora’s box. There are a great deal of varied resources. To name just a few: client data, usage data, personal data, and income-based data.

In this white paper, Columbus and AT Internet want to focus on one type of data in particular: platform usage data. This data is a formidable source of improvements for the digital experience and, therefore, customer satisfaction. We believe that a pleasant user experience is an important way to stand out in a digital B2C relationship.

So, what is data-driven UX? The concept has tended to be overtaken by more trendy fields, such as Conversion Rate Optimisation.
The purpose of data-driven UX is to build the best experiences and interfaces possible by using all the user data sources available, both qualitative and quantitative.

As with any methodology, you cannot exclude obstacles to its application. It is no magic formula, and the methodology requires a certain internal maturity. In this white paper, we will detail the major steps needed to implement it.

We hope you enjoy reading it!

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