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Optimising in-store data is more than just a numbers game

Data. Everyone involved in retail decision-making seemingly wants more of it. In fact, there isn’t a day that goes by without yet another report proclaiming big data as an absolute necessity for business success. Loyalty cards, EPOS systems and online analytics – big data is everywhere. But does it really do anyone any good?
You only have to look at the current plight of grocery retailing, and you’d be forgiven for answering ‘no’. Arguably the ‘Kings’ of big data, supermarket loyalty programmes have been collecting data on us for years now and have, until recently, been the engine of success. By understanding how many times something was picked up, the time we spent in aisles and what we were buying, it would be possible to forecast purchasing trends, secure greater loyalty and remove the margin for error – essentially: predict the future. Or so the theory went.
According to a report by shopper research agency Shoppercentricr, 17 per cent of self-defined “Tesco shoppers” actually claim to spend more in other stores. Worse still, many shoppers are now abandoning the big four grocers altogether – changing habitual shopping behaviour that has been ingrained in them for 30 years. As a result, supermarket profits are dropping off a cliff. But why did big data not predict this tide of change?

Put simply, because information is not insight – analysing customer data does not mean you understand shoppers. What modern retailers need now more than anything else is not information on what people buy; but insight into why they buy what, and where they do. What they need is knowledge.

We live in a world of information overload. As a result, more does not necessarily mean good if data required for critical answers is missing. For example, retailers won’t be able to maximise the impact of POP if they only have data about how much of it they need, while remaining blind about the biggest challenge: ensuring they have POP that is suited to different store formats within retailer estates. Indeed, data capture should be about providing information that helps marketers make better decisions or learn something new.

Many promotions and sales are lost through ‘poor retail implementation’ practices in-store. This is sometimes down to not being aware of potential issues, being too slow to react, or reacting to the wrong things. So it does little good to have a mountain of information that tells you what’s happening within your retail estate sitting around in a format that won’t be seen until after the fact, or have the relevant facts and events lost in a sea of too much of information. No, retail marketers don’t need any more data. What they need is knowledge – and in real time.
In truth, the challenge for retailers and brands isn’t big data, but how to manage lots of little data. A lack of cohesion will make anything resembling real knowledge impossible: You will be left with a thousand pieces from a thousand different puzzles. All that information must be monitored, sorted and managed in a way that’s thoroughly integrated into your retail operations, and in a way that delivers real business improvement.
In an age where retail data is everywhere, the issue of quantity versus quality remains a real challenge. These days, business intelligence is recognised and invaluable business tools. Yet when it comes to data analysis of POP across retail estates brands often neglect to use the same kind of principles that they apply to making other, more broadly scoped business decisions.
By treating information from thousands of store visits as the rich data sources that they are, it is now possible to turn too much information into the valuable knowledge you need to keep your in-store POP better maintained in more effective ways, at a lower cost and with less work. Ultimately, their benefit will be your benefit.