The perfect accompaniment. Steak and Chips. Christmas and Snow.
Big Data and Qual.

 

Creeping digitisation of our world means life can be recorded and quantified in ways that would have been scarcely imaginable a decade ago. From purchase patterns to media consumption to dating preferences, our online behaviour leaves a footprint at every turn.

Practically every business, intentionally or otherwise, captures large volumes of customer data. When effectively harnessed, this data can present a goldmine of information, uncovering patterns in consumer behaviour which help businesses operate more efficiently and boost revenue streams.

In reality, however, the challenge of digesting and making sense of so much data can prove overwhelming. Even when businesses possess the correct skillsets to generate insight from customer data, they can rarely go beyond explaining the ‘what’ (identifying a trend in the data); falling short of explaining the ‘why’ (why a certain trend is evident).

While quantitative data of this type can provide valuable insight on customer behaviour, it often fails to explain the motivations behind the behaviour – and by extension, has no chance of developing strategies to change the phenomena that have been identified. For this reason, many companies continue to appreciate the value that primary research delivers in terms of small quantities of high quality information.

Kadence recently undertook a programme of self-funded research in collaboration with ESOMAR, titled “Who Owns The Data?”, which explored views on the collection, management and use of data within commercial organisations around the world. A key finding that emerged from the research was that quality of data matters far more than quantity when unlocking meaningful insight. This sentiment certainly rang true for a client we recently partnered in the FinTech space.

Our client, with over 6 million UK customers, possessed huge quantities of personal and behavioural information. While this data helped identify patterns in behaviour, it failed to explain why this behaviour occurred. Our client was keen to understand why their most affluent segment of users did not follow patterns of profitable behaviour commonplace amongst other segments. They recognised that only once they’d discovered the barriers to this behaviour could they start to dilute and remove these same barriers – and ultimately drive greater profitability.

Having carefully considered our client’s challenge, Kadence proposed an online community led approach designed to uncover key motivations and needs for this group. Over a ten day period, Kadence elicited fascinating and enlightening opinions, observations, experiences, needs and personal stories from participants. Community-based tasks and activities were specifically designed to provoke engagement, yielding insights which helped Kadence to genuinely understand the why behind the what. Working collaboratively with our client and building on insights from existing customer data, we were able to uncover insights which reached far beyond initial client expectations and the initial scope of the study. Our client is currently in the process of implementing a programme of changes built around Kadence’s recommendations, monetising this hitherto non-monetised segment.

The challenge our FinTech client faced is far from unique.  Many organisations struggle to make sense of the huge volumes of data they collect, particularly when it comes to understanding why behaviour occurs. In this context, an expertly curated qualitative exercise is the perfect accompaniment to big data, uncovering the why behind the what, and enabling our clients to drive profitable change.