Are you satisfied with your gross margin and sales per square foot? If not, consider putting the customer first by adopting consumer-centric technologies for pricing. In “Putting the customer first“, Susan Boyme emphasizes how important it is to “evaluate price elasticity and tailor pricing across specific regions and individual stores.” Revionics is working with Insight-out-of-Chaos to take customer centricity to the next level by identifying the best items to promote by customer segment. Loyalty data was analyzed in terms of basket profit and trip frequency. While the revenue and profit per basket of loyalty shoppers were found to twice that of non-loyalty shoppers, it was surprising to learn that loyalty shoppers as a whole vary widely in shopping frequency and basket profitability. It was evident from the analysis that there is a large opportunity to increase increase basket profitability and shopper frequency by targeting incentives to specific customer segments. At the same time retailers can build customer loyalty in their VIP shoppers through customer-centric offers.
Our research found that basket profitability and trip frequency are largely independent, which fall in contrast to recently reported results from Mark Aguiar and Erik Hurst at NBER. Their research using AC Nielson Home Scan data suggest a “doubling of shopping frequency lowers prices paid for a given good by 7 to 10 percent. Using this elasticity and observed shopping intensity, we can impute the shopper’s opportunity cost of time. Our imputed measure tracks the life-cycle profile of wages rather closely, particularly after middle age.” Their research is presented in “Home Production, Consumption, and Labor supply” at http://www.nber.org/reporter/2009number4/2009no4.pdf.
The authors report finding “elasticity of substitution between time and market goods in home production of roughly 1.8. Food expenditures fall dramatically after the age of 45 while our estimates of actual food intakes increase slightly after middle age. We find that roughly 10 percent of the decline in food expenditures after middle age is attributable to lower prices paid because of an increase in shopping time.
Revionics’ results were from a high-end retailer, which may explain the discrepancy.
Market basket data was analyzed to identify affinity relationships. The best items by customer segment were identified to drive profitability and trip frequency. In this case, meat and seafood were strong drivers of both basket profit and frequency. Cheese, coffer, and tea were good candidates for basket builders and prepared foods helped drive trip frequency.
The analysis requires an understanding of cannibalization as well as price elasticity and affinity. When these relationships are understood, retailers can make better decisions about what item to promote at what price to specific customer segments. For more information, please email Revionics at email@example.com.