Why dialogue is important to customer centricity

Home  ❯  Opinion   ❯   Why dialogue is important to customer centricity

26th April, 2024 No Comments

An extract from the latest book by By Dr Anette Broløs and Dr Erin B. Taylor…

Digital technologies play an important role in allowing the collection and management of large amounts of data and introducing automated processes and pattern recognition for both employees and customers. It creates the possibility of designing individual solutions for customers and achieving customer-centricity.

This process is often called “data-driven innovation”. In our recent book, Customer-centric Innovation in Finance (2024, Kogan page), we argue that pure quantitative data-driven innovation carries the risk of overlooking or misunderstanding customer needs. This is where the need for qualitative data including dialogue with customer comes in.

Using qualitative data to understand people

Quantitative data can misinterpret and overlook people’s actions. In the wake of IWD24, decided to choose examples that focus on women to demonstrate some of the ways this can occur.

Customer surveys asking about behaviour and use of services may show what people think the should do rather than what they actually do.
When you ask people directly about payments, and particularly if you give them a number of survey choices, they will often stress security or perhaps a personal principle of “never carrying cash”.

However, in reality people do not always follow their own principles. We interviewed 14 Swiss women about their payment habits (Broløs and Taylor, 2022a). When talking about their shopping habits, most of these women said that they would prefer to use their phone at the checkout, but it was impractical for two reasons. First there were too many things to manage and carry and second the internet connection would often be insufficient. And so they continued to carry cash, despite considering themselves to be digital-only users.

Relying on quantitative customer data may overlook the ways people use combinations of services to manage their finances according to their needs.
In 2022, we did a short digital ethnographic study for Filene Research Institute on the development of Buy Now, Pay Later (BNPL) services (Broløs and Taylor, 2022b). We found that most BNPL services were described as win-win-win solutions that bring benefits to customers (“free credit”), providers (“more business”) and merchants (“higher sales and greater customer loyalty). When following users’ exchanges in digital user groups, we discovered first that most participants were women, and next, that contrary to the expectations, they would use a wide range of BNPLs for different purposes and would share tips and tricks to solve issues with returning shopping or understanding credit limits.

Relying on quantitative data may lead to overlooking whole customer groups like SMEs, women and young people.
When using existing customer data to create new services there is the obvious risk of overlooking customers in new or underserved customer groups. One major group of underserved customers is women, both as consumers, as business owners and as employees. Women often have different financial experiences to men: research shows that women don’t like to ask their bank for advice, that female entrepreneurs have less access to funding than males and that women CFOs feel treated poorly by their company bank. Understanding women’s experiences can be difficult to achieve via analysing their customer data or even undertaking a survey. Instead, qualitative research techniques such as interviews are most useful for capturing women’s stories.

Quantitative data analysis is likely to underestimate customer’s knowledge about money and the way people manage finances not as individuals, but as social groups, especially families.
When technology is considered the driver of innovation, there will be a tendency to consider if, when and how users can adopt new services. We often hear that lack of uptake of new financial services is due to lack of financial literacy or education. Our research, however, consistently confirms that solutions that actually solve a customer pain point will be used, while customers will ignore ‘solutions looking for a problem’. Indeed, our research suggests that unfamiliarity with a new tool is rarely a barrier to use.

People take the trouble to ask friends and family to help out when getting started with a new helpful tool. We saw this in our studies in Brazil (Taylor and Broløs, 2022) when elderly women in rural areas would learn from their grandchildren how to use digital payments (avoiding a day trip to the next city to withdraw cash and pay bills.) In some instances, understanding customer behaviour can lead to a smoother and more useful introduction of new technologies. In other instances, customers may already be running ahead of industry innovation. Gamers, virtual world enthusiasts and tech people developing ChatGPT interfaces or personal solutions may provide the industry with valuable insights into what may become mainstream tomorrow.

Quantitative data are likely to overlook the why of customer behaviour and underestimate customer values and preferences and the way customers make financial decisions.
For years it has been suggested that women invest less than men because they are risk averse, or perhaps less knowledgeable. Barbara Stewart, a former investment manager, has interviewed close to 1000 women about their investments. She finds that women are probably rather risk aware than risk averse, meaning that many women may be willing to take higher risks to establish their own business but may not want to take larger market risks for higher profit. But the most important insight is probably the much broader concept of investment spanning not only buying assets for profit but also investing in life’s big decisions like education, property, family or business.

Failing to understand customer insights that employees are aware of
Although customer service is moving from face-to-face service to digital services, some of the insights described may well be known already by company staff (front end employees or advisors). This is something to take into account (Taylor and Uy, 2021).

Looking forward
We argue that in financial markets, as well as in many other industries, the best innovative results can be achieved by combining the analysis of quantitative data with the study of customer behaviour.

*This blog post is a lightly edited extract from the book, Customer-centric Innovation in Finance:
Leveraging Human Insights to Drive Product Innovation in the Digital Age, by Erin B. Taylor and
Anette Broløs (2024, Kogan Page).

Leave a Reply

Your email address will not be published. Required fields are marked *

Our website uses cookies to provide your browsing experience and relavent informations.Before continuing to use our website, you agree & accept of our Cookie Policy