Recently, I applied for a loyalty card in one of retail outlets. I was, as part of the procedure, required to fill out a form. The most striking aspect of the process was the actual amount and the level of detail in the information that I had to part with. This included, among other details:
- Personal details – my date of birth, gender
- Household and family details – my spouse, size of my household, number of children
- Location details – residence
- Contact details – email, phone number
- Behavioral details – occupation, interests
- Financial details – who I bank with
A quick look at this information could only lead to one inference: retail outlets in Kenya are, knowingly or not, effective collectors of staggeringly useful data.
Remember, these retail brands have outlets all over the country: In every major town you would expect to find one of, some of and in some cases, all of Tuskys, Naivas, Nakumatt or Uchumi outlets just to name some of the major brand names. This means they collect this data every single day while effortlessly covering the whole country.
Taking all these information about shoppers, adding to this the fact that the loyalty card provides a system to track shopping habits like frequency of shopping, items purchased and amount spent over time all mapped to an individual; and then overlaying this against already existing demographic data would create a rich and massive data set from which no limits exist when it comes to what could be achieved from it.
Association rules and patterns between variables could easily be used to inform targeted marketing strategies, shopping basket data analysis, product clustering, catalog design, stocking, store layout plans and channel expansion among other retail-specific business decisions.
The goal here would be to turn all this information into actionable insight. First and foremost, the right business questions must be asked. From these questions, appropriate analytic techniques and tools are developed to add value to this customer data by turning it into insight.
Whether this is happening within the Kenyan retail space and at a level high enough to influence outcome is debatable but one thing is for sure: Out there, brands like Budget are firmly in the current datafication-of-life wave and have been known to use customer data as the corner stone of their strategy.
The business needs are there, the data is there, the intellectual capacity is there – so why are we not utilizing these again?