The report, by software firm SAP, also found that more than half of retailers have more data than they can actually act on.
These are worrying stats considering the impact that data can have on all aspects of a business, particularly since 75% of retailers have seen demand for more personalised services increase in the past two years.
The company’s opening gambit on the website of FuelData, an agency I recently met, is: “Data. It’s a lot more exciting than it sounds.”
This couldn’t be more true, but the sheer scale of data that some organizations now have at their fingertips is overwhelming.
What is obvious, even to those of us not so well versed in the intricacies of data collection, is that just collecting data isn’t enough.
Data has to be utilised to make it worthwhile collecting, and it has to be used in the right way to help grow a business.
Supermarkets such as Tesco were frontrunners in data capture and data use through loyalty schemes such as ClubCard. And although loyalty schemes are often front of mind in terms of data – that’s not the only way that it can be useful.
There are innumerable ways that retailers can use data to help improve business performance and that does not necessarily mean a reward scheme that hands out vouchers and coupons in return for information.
Data can be used to personalise services, prove return, to shape a marketing campaign, identify where to invest marketing spend, to deal with a crisis, better segment or find out the optimum product range for a store in a certain location, and many more beyond.
If data isn’t being used in the right way, retailers could find that instead of using a loyalty scheme to grow business, they are eroding it by rewarding behaviours that shoppers would exhibit anyway. The data should instead be used to shift consumers into other areas and encourage new behaviours.
The key to efficient data use is knowing what you want to achieve, and using data to solve that problem and make better business decisions. Having too much data is as worthless as having none at all.