Rainbow Stores – A case of MR

Rainbow Stores was a chain of 26 supermarkets located primarily in large West Coast metropolitan areas. Reputedly one of the best run chains in the country, Rainbow owed its success in large part to the creativity and resourcefulness of its president, Clark Samuels, a leader in progressive food retailing practices and more recently, a pioneer in the use of electronic scanning equipment at check out counters. Samuels had already fully equipped all 26 of his stores with the scanner devices. Samuels had been impressed with the hard savings resulting from the use of the equipment mostly in the form of labor savings and reduced inventory shrinkage and customers had generally seemed pleased with the faster check out process and the reduced incidence of error on their bills. Samuels felt, however, that the benefits of the system had just begun to surface; he was intrigued with the research possibilities presented by the scanners.

Scanners such as those used in Rainbow Stores were developed by the computer industry to accommodate the Universal Product Code (UPC) a band of parallel lines approximately one inch square, which appeared on grocery products, drug products, records and magazines. The UPC was jointly conceived by food processors, supermarket retailers and equipment manufacturers, and when decoded by an electronic scanner, the UPC would identify the manufacturer, size, flavor, color, and other features of a product. At the time, the UPC appeared on more than 170 billion packages sold in the United States.

In a scanner equipped store, the UPC of each item purchased by a shopper would be read electronically as it passed over a laser slot in the check out counter. The product information disclosed by the UPC was then matched to price information stored in the scanner’s computer, and a customer receipt that identified each item purchased by the individual product name and price was printed out. As a by-product of this system, this store management was given detailed item by item record of product movement and price; it was this latter feature that led Samuels to believe the scanner could be a valuable research tool.

Samuels realized that before the scanner system could be used in any kind of conclusive research the stores would have to be matched in some way according to the characteristics of the customers who stopped there. With that thought in mind, he retained the research firm of Robert Chapman and Associates to study age, income, family size, and other demographic characteristics of each store’s clientele. Although the study revealed some store-to-store differences, approximately 10 of the stores were so well matched on the variables studied that Samuels felt, through careful selection, it would be possible to use combinations of stores that would not cause a bias as a result of different types of customers.

Encourage by the finding of the demographic study, Samuels next turned to consider the particular areas which might possibly be researched with the scanner computer equipment. These areas seemed to be especially promising.

1. Determining of the best price to charge for store brands relative to national brands in a given product category
2. Measurement of the true effectiveness of end of aisle displays (EAD) on both current and future purchases.
3. Evaluation of the effect of different advertising practices.

In regards to the first area of research, Samuels was confident that the profitability of the Rainbow Stores’ house brand could be considerably improved. He focused on one product in particular which he felt was under priced compared to national brands. This item, frozen orange juice, was currently priced at 93 cents per package, approximately 10 cents lower than competing national brands. Historical data had shown that the store brand accounted for 30 percent of total sales volume in this product category – a figure that represented more than 600,000 packages per year. Samuels figured if he could raise the price to 95 cents a package without significant loss in sales volume, he could increase profits by $12,000 per year (600,000 x $.02); at a price of 97 cents a package, profits would increase by $24,000 per year if volume remained steady. Such figures could be significant to Rainbow Stores, which operated in an industry whose earnings were less than 1 percent of sales. Samuels felt the scanner could help him determine the most profitable price for this and many other stores branded items.

End of aisle displays (EAD) represented another potential research area of interest to Samuels. Like other food retailers, he knew that EAD increased the sales of the displayed item during the display period. Intuitively however, Samuels felt that perhaps these display induced sales increases might only borrow form future sales when the item was returned to its normal position on the shelf. The situation could be aggravated if the EAD featured a reduced price; such a practice might even result in a loss in terms of overall profits. Samuels felt the scanner might help him quantify the true effectiveness of this display technique by measuring; (1) the sales increase while the product was in EAD, (2) the sales increase or decrease for a certain number of weeks following EAD, and (3) the total profitability of the EAD effort.

A third area of interest to Samuels was the effectiveness of various forms of advertising. Advertising was essential to the food retailer, but with so many alternatives available, the retailer had only his hunches to tell him which were most effective. Samuels knew, for instance, that major items featured in bold print in Rainbow’s weekly newspaper advertisement were effective in drawing customer. Samuels was also interested in the true effectiveness of various loss leaders – specials on meat, dairy, coffee, and so on that were priced significantly below their normal retail price to draw people to the store. If customers bought only the loss leader, profitability would suffer during the course of the sale. If, however, the use of different loss leaders could be shown to be related to increase or decreases in the average amount purchased on the shopping trip, Samuels would know which loss leaders to use more frequently. He also felt that appropriate research could help him determine the most effective loss leader price and the length which should elapse before any given loss leader was featured again.

Samuels must identify certain specific products and use the scanning system as a research tool to identify volumes and net realization from these products. Thus he can repeat the exercise for another group of products. After compiling the data he can continue or eliminate the products if price adjustments cannot be done.

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