Retail technology provides novel ways to investigate the effects of marketing actions (MAs) on consumers’ behaviors. To evaluate effects of MAs on conversion, we propose an approach that combines sensor-collected records of store entries with register-receipts within pre-determined time-bands. Studies of effects of MAs on conversion in brick-and-mortar settings, however, are surprisingly scarce. The approach has three stages: (a) build a model for the conversion probabilities with data outside the MA interval, (b) build a counterfactual baseline for the conversion probabilities during the MA, under the hypothesis that this action has not occurred, (c) compare the observed conversions to the corresponding counterfactual conversions to determine the effects of the MA. An analysis of a two-day promotion illustrates the method. It provides evidence that the promotion associates with increased counts of both visits and purchases, but the association with conversion remains unclear.
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- Counterfactual prediction
- Promotional effectiveness
- Retail technology