Dunnhumby founder Clive Humby: customer insights should be based on passions as well as purchases

Using transactional data to guess customers’ motivations gives a limited backward-looking view. Brands must use social data to add personality to their insights, according to dunnhumby founder and Starcount chief data scientist Clive Humby.

The Alan Turing Institute’s research activity in data sciences finally began this autumn. With it has come a renewed conversation about the role of ‘big data’ in Britain – and £42 million worth of confidence from the chancellor George Osborne. Industry and academia are meeting at an exciting intersection, which is welcoming in a new era of insights using the mass of data now available.

Indeed, data is the new oil. This vast, untapped reservoir represents limitless potential value. Yet, in its crude state it poses real challenges for business. Companies have an excess of data but a shortage of insight. The next generation of insight needs to refine this crude data to achieve the ultimate goal: understanding customers.

Data needs to tell a story. Like a kind of ‘digital play’, it must paint a full and nuanced picture of individual customers. Achieving this will mean drawing on multiple data sources, creating a rich blend of insight that cuts to the heart of the customer’s needs and wants.

Customer insights have progressed in leaps and bounds in the age of new media. Back in the 1950s, audiences were roughly divided into social classes: AB, C1, C2, DE. Back then, you were defined by the job you did or the area you lived in.

Towards the turn of the century, demographic data was overtaken by insights gleaned from actual behavioural data. In 1989, Edwina Dunn and I started the customer data company dunnhumby. The trend of the loyalty clubcard was spawned, and with it a host of new, actionable insights.

Customer data exchange, enabled by a loyalty card, began painting the picture of why customers made their purchase choices. Retailers were able to offer ‘personalised’ offers, and in return could expect ‘loyal’ customers.

And yet, a piece of the puzzle was missing. Customers were being judged on what they bought, but an understanding of their implicit motivations and aspirations was missing.

“There is more to understanding your customers than an in-depth knowledge of their past behaviours.”

For data-rich organisations, we developed the ability to understand ‘motivations’ derived from the items you choose to pick off the shelf. This method works well when transactions are frequent and varied, such as in supermarkets or with credit cards. In many ways we were able to imitate the instantaneous opinion you form when you observe another customer’s choices of groceries on the till-belt.

Grocery and credit cards apart, for most other customer organisations the richness of transaction just is not there; from fashion to utilities, sports to club memberships, transaction data is a sparse landscape that tells us little other the recency, frequency and value of a customer. To truly engage with them we need to understand them much more fully. This is the ‘long tail’ conundrum: how to understand that long tail of customers with few interactions or little engagement.

Jump forward to the present day and we’ve been introduced to a growing expanse of personal data, now known to us as big data. Brands can look beyond their own customer data to complementary external data sources that enrich customer understanding to unprecedented levels.

Furthermore, the consumer landscape has changed. The emergence of social media has meant that nowadays everyone leaves a trace – a trace that has become the lifeblood of business. Customer control of the content generated and consumed on digital channels is constantly increasing, so understanding their behaviour is essential.

The social media trail can be read to discover passions, media consumed, influencers, and brands engaged with. Until cultural understanding of customer motivations and aspirations is reached, a brand cannot make itself relevant. Gain this understanding, and you can see your brand through the eyes of your customers.

There is more to understanding your customers than an in-depth knowledge of their past behaviours. But this is what most customer insight teams will do: they are glorified management information teams, manipulating historic data to determine some proxy personalisation.

Without storytelling, data offers just a rear-view mirror. Next-generation customer insight will bring personality to big data; it will go beyond backward-looking internal customer information, using social and market data simultaneously to identify communities based on shared passions, interests and behaviour. This precise segmentation will be invaluable in developing a customer engagement strategy; it will inform board-level decisions and impact the customer experience.

And yet big data has come to be associated, for many, with Big Brother. Questions are asked as to whether these new insightful possibilities are cool or creepy.

First things first, it is crucial that brands operate to the highest standard of data privacy. New flows of information have been enabled by new media, and demand ever-increasing accountability from corporations. Transparency is key; if customers can see the value they gain from sharing their information, they will relish the prospect of targeted, personalised messages and deals. Allowing customers to opt in puts them in control of their own data.

Indeed, the landscape of customer interactions is turning from push to pull: instead of businesses pushing a service onto the customer, the public are now pulling in the products that they want. This shift of power means that business must appreciate the importance of the customer as an individual.

Whether we like it or not, data is now inescapable. Commercial models are changing and customer value is improving. Now is the time to embrace the information available, to refine this raw asset into insight that will benefit businesses and customers alike.

The launch of the Alan Turing Institute shows clearly that the immense potential of big data is coming to the fore of the public agenda, so now is the time to sit up and pay attention. The winners will be those who bring to life the story behind the information, and from it reap the benefits of personalised customer journeys.

Clive Humby is chief data scientist at Starcount, and was co-founder of dunnhumby, now owned by Tesco.