Abstract:
We describe a methodology by which a retailer can identifyaction steps that are likely to increase sales and customer satisfaction anddemonstrate the methodology using proprietary data from a large retailer withover 500 stores. We use monthly store-level data on a number of operationalvariables including in-stock rate, store staffing level as measured by payrolland store employee turnover, together with customer responses to satisfactionsurveys. We develop a nested three-stage econometric model to analyze themarginal effects of various execution levers on sales, customer satisfactionand the percentage of customers who answer yes to the question Did you findeverything you were looking for?, which we term customer perceived in-stock. Ourmodel explains approximately 75%, 97% and 71%, respectively, of the residualvariation in sales, customer satisfaction, and customer perceived in-stock. Wefind that customer perceived in-stock is primarily driven by actual in-stockand customer rating of employee knowledge; overall customer satisfaction is primarily driven by customer perceived in-stock, payroll level, customer rating of employeeknowledge and check-out efficiency; and sales is primarily driven by actualin-stock, overall satisfaction and payroll level. Finally, we estimate relativemagnitudes of these effects, propose specific actions to improve sales and estimate the likely sales increase from those actions. Our results suggest thata modest reallocation of the payroll budget among stores could be expected toyield a 2-3% increase in sales with no increase in cost.
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