Category Management is undergoing a quiet revolution. Gone are the days when a category manager could trust in intuition and experience alone. The new generation is embracing Retail Science to make better price, promotion, merchandise and assortment decisions. Retail Science applies sophisticated data analysis to help better understand what customers want. Data sources include Point-of-Sale (POS), Transaction Log (TLOG), competitive pricing, panel, syndicated, weather, demographic, and location attributes. Data cleansing, quality assurance tests and outlier analysis are essential for measuring causal relationships. The result is a demand model that accounts for price elasticity, promotional lift, merchandising, seasonality, cannibalization, affinity, space, and assortment. Category managers use this demand model to evaluate and compare scenarios. For example, a supplier may offer a incentive to promote Cheerios. The category manager can evaluate the category profit accounting for vendor incentives, cannibalization, and affinity. This analysis shows how cannibalization of private label erodes category margin. Even the impact on loyalty customers can be evaluated in terms of basket size and trip frequency by customer segment.
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 taken 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.
By: Todd P. Michaud, President and CEO, Revionics, Inc.
As we look at the retail market, we see most retailers plagued with either inadequate Retail Demand Intelligence (RDI) and Forecasting tools or on the contrary, some retailers have too many disparate systems that contradict each other. This is even true for those retailers who have selected comprehensive solution portfolios from the largest of software vendors since so many software vendors have merely intellectual property that they have acquired through poorly architected interfaces.