Data Science, Analytics & Solutions
This DIY retailer was trialing a series of new store experiences at a single test store. They wanted to understand what impact this had had on the shopping behaviours in-store and the impact on local market share.
What we did
Using our extensive experience with payments data we facilitated a representative sample of credit and debit card transaction for the test store and surrounding area from a major payments network. Using this data in conjunction with the in-store transactions we were able to develop the correlation of sales performance and footfall data against the competition in local markets. This identified regular under performance in conversion rates within the store. This was historically being attributed to poor weather as no other data points were available. Evidence based tracking of consumer spend across the category proved the local market was trading well in spite of poor weather and this should not be attributed to the performance.
This new evidence triggered a closer investigation of the internal operations. Store management were able to re-assess staffing mix and ultimately addressed weekend shift training at those stores and re-balanced the ratio of experienced staff on key trading days.