Innovation

What data can’t tell you about customers

Harvard Business Review /

Across industries, companies are using vast amounts of user-generated data to guide innovation of new products and services. But data mining does not automatically create authentic ”customer intelligence”.

Human behaviour is nuanced and complex, and no matter how robust your data is, it can provide you with only part of the story. Desire and motivation are influenced by psychological, social and cultural factors that require context and conversation to decode.

Data can reveal new patterns that point a firm in the right direction, but it can’t indicate what to do once it gets there. Data reveals what people do – not why they do it. And understanding the why is critical to innovation.

A wink or a twitch?

Think of the last time someone winked at you. With just a simple gesture that person was able to communicate. Yet, how did you know what that gesture meant? Anthropologist Clifford Geertz posits that all of our behaviours are imbued with sociocultural significance. Interpreting their meaning and the motivation behind them requires what he calls a ”thick’’ understanding that comes from detailed observations of people’s interactions and their environment. In the wink/twitch example, traditional customer intelligence would only tell us that there was eye movement – not what kind or what it meant. It misses the ”thick’’ understanding that is critical to meaningful innovation.

Several years ago, a client hired our design firm, Continuum, to create new products for poor families in urban Brazil. So we set out to understand these people’s needs, values and motivating desires. In conducting our field research, we observed that virtually every family owned a television. This was not a huge surprise – any report can tell you the rising percentage of technology ownership among families in emerging markets. But when we dug deeper, we learned that the TVs weren’t status symbols or signs of increasing wealth; they were safeguards. Because of the violence prevalent in the favelas where these families lived, parents feared their children going out at night. What these parents really wanted was to make their living rooms more entertaining for their kids than the streets.

Customer intelligence might have told us the percentages of poor Brazilian families that owned televisions, but it never could have explained exactly why they had them. Building on this insight, we leveraged our client’s capabilities to transform a staple product geared toward parents into an engaging experience designed for kids. In prioritising parents’ deeper needs, our client regained market leadership.

When the data trail goes cold

Increased computing power, ubiquitous consumer tracking and ever-more-effective data mining techniques offer significant advantages for businesses. Trends can be identified more quickly and precisely than ever before. But the fact remains that any trend, however early it’s identified or robustly defined, can’t tell you how to succeed.

When Clorox entered the ”green” cleaning market in America, routine trend analysis had revealed that while the overall cleaning products market was stagnant, the ”green” niche was growing. Basic consumer intelligence indicated that consumers were becoming more environmentally conscious, but that people often didn’t know how to act upon their changing values toward green. The company’s own intelligence suggested the emergence of a new and underserved segment of ”chemical avoiding naturalists” who had not been attracted by existing offerings from more green-friendly brands like Seventh Generation and Method. But that’s where the data trail ended.

Abandoning quantitative data analysis, Clorox conducted in-depth interviews and in-home ethnography to better understand the psychology, unmet needs and underlying values of these ”naturalists” – and what it would take for them to switch to green home-cleaning products. These insights allowed Clorox to stake out a product position focused on sustainability that resonated with this segment.

Advertisement

We Recommend

FROM AROUND THE WEB