Table 7: Category Gross Profit Changes under various Pricing Strategies
Currently Dominick's follows a limited micro-marketing strategy, in which they segment their stores into several price zones: high, medium, and low. In the high price zone, the everyday prices of all products are raised proportionately by 10% over the medium price zone. Conversely, Dominick's lowers prices proportionately by 10% in the low price zone from the medium price zone. (In practice these percentages change but we use a single percentage since it captures the essence of the strategy and simplifies the calculations.) This segmentation is largely decided by competitive characteristics of the store's trading area. For example, if a store is close to a warehouse competitor then the store will be assigned to the low price zone. The profits from various category pricing strategies are given in Table 8. Under the current zone pricing strategy expected profits would increase by .86% over those of a uniform strategy under a moderate prior.
Table 7: Category Gross Profit Changes under various Pricing Strategies
To simplify our discussion about a store's price response, we develop an overall measure of the store's response to proportional price movements (i.e., the category elasticity). (See also Hoch et al. 1995.) The motivation of the category elasticity is to measure the effect on movement of a 1% increase (or decrease) of all the prices in the category. Our primary purpose is to construct a summary measure for labeling each store as price sensitive or insensitive. Formally the category elasticity is:
Where 
is the total category movement,
is the vector of movement market shares, 
is the cross
elasticity matrix evaluated at the average price for store s, and
is a vector of ones.
To illustrate the dispersion of the category price elasticities using a moderate prior we plot each as a thermometer against its location in Figure 9. The thermometer's box shows the total range of the category elasticities (all boxes have the same height). The most price sensitive store is located on the South Side of Chicago with a category price elasticity of -1.87 (s.e.=.23). The least price sensitive store is in the northwest suburb of Arlington Heights, it has a category elasticity of .15 (s.e.=.12). (This is the only store that shows a positive category elasticity.) The shaded area within the box represents the posterior mean of the store's category elasticity. The average category elasticity across the stores is -.85 with a standard deviation of .31, three quarters of the stores have inelastic category price responses.
Figure 9: Category Price Elasticity
To ease the identification of stores we shade the thermometers. The most and least price sensitive third of the stores have the lightest and darkest shading respectively. The map allows us to observe that the largest geographic concentration of the price sensitive stores are located on the south side of Chicago, and the least price sensitive stores in the northwest suburbs. Notice that price sensitivities can change very quickly with price sensitive stores being located very closely to insensitive ones.
A natural question is whether the retailer's current assignment of stores to each pricing zone can be improved upon. To set up a better store-segmentation strategy the retailer could assign stores based upon their category-level elasticities. To keep the current zone strategy comparable with this new strategy we allocate the same number of stores to each price zone. The most inelastic stores are assigned to the high price zone, and the most elastic ones are assigned to the low price zone. These zones would increase expected profits to 2.35% over a uniform strategy. This improved zone scheme would result in a three-fold increase in profits that are now attributable to micro-marketing policies using Dominick's current zone strategy.
If we were to look at these results on a store by store basis we would see that stores with price increases have increased profits, and stores with price decreases have lower profits. This is the result of the low category price sensitivity of even our most price sensitive stores. Our improved zone classification scheme has increased the profitability of the high price zone, while the stores in the low price zone have been chosen to lessen the profit loss. Compared to this improved zone classification scheme, a better strategy is to simply discontinue the low price zone segment, or even better to simply increase the prices in all stores. If we combine the low and medium price zones under our category elasticity zones we would see a 7.29% increase in expected profits. Whereas if we simply raise the prices in all stores, we would realize a 22.21% increase. Notice that less than a quarter of the stores are in this high price zone, but total profits increase by more than a quarter. This disproportionate increase is the result of carefully selecting stores with the least price response.