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Implementing Personalized Known Value Items For decades retailers have driven their price-value image by focusing on KVIs. These KVIs, which may include as many as 600 product lines, are believed to disproportionately improve the shopper's value equation. Retailers assume these items, and their corresponding price points, appeal to the majority of their shopper base. While this approach does have merit, it is far from optimal. Thousands of households may not consider a particular subset of products to be relevant, or may fail to notice the retailer's aggressive prices. This dilutes KVIs as a key competitive pillar and further erodes margins by needlessly lowering prices. Conversely, PKVIs ensure shoppers are getting the best-in-market prices on the products that matter most. Using proprietary analytics and historical transaction data, PKVIs redistribute incentives by household to maximize impact – all while protecting margin. The path to personalization begins by analyzing product purchases at the household level. These products are then weighted and ranked based on household penetration and PKVI density. 1 Products with high household penetration and high PKVI density become store- wide KVIs with lower prices offered to all shoppers. This process typically reduces the number of store-wide KVIs by about 70 percent. The remaining products become candidates for PKVIs based on specific shopper behaviors. Figure 1 illustrates product classifications before and after PKVIs. 1 PKVI density reflects the likelihood of a product being in Personal Known-Value Item baskets.

Understanding Shopper Behaviors and Defining Shopper Demographics Using shopper analytics, trading partners can develop strategic initiatives to increase sales and drive category growth while improving bottom-line performance. Critical analytic outcomes include: • Defining core shoppers and understanding their purchase behavior • Understanding category-specific drivers and identify opportunities for growth, differentiation, and loyalty • Increasing ROI on promotion spending by increasing offer relevancy • Quantifying category growth by attracting new shoppers into the aisle

26%

25%

19%

15%

4% PERCENTAGE OF CUSTOMERS

11%

45–54

55–64 65+

18–24 25–34 35–44

AGE

BEFORE

AFTER

Mean age: 46 years old

STORE– WIDE KVIS

STORE– WIDE KVIS

MRS. JONES‘ PKVIS

MR. ADAMS‘ PKVIS

Figure 2

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BANANAS CHIQUITA

■ ■

BISON COTT CHSE PINEAPPLE

CAMPBELL V8 JUICE PLST 100%

70% FEMALE

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CAPRISUN FRUIT PUNCH 10PK 10%

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CARROTS PEELED 1 LB.

■ ■ ■ ■

CELESTE PEPPERONI PIZZA

30% MALE

DAISY LIGHT SOUR CREAM

88% MARRIED

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IMPERIAL MARGARINE QUARTERS

NESTLE COFFEEMATE HAZELNUT 32 OZ.

12% SINGLE

■

POLAND 24PK 16.9Z SPRING WTR

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PREGO SPAG SCE MEAT

71% KIDS

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PRIVATE LABEL BUTTER QUARTERS

■ ■

SABRA HUMMUS GREEK OLIVE

29% NO KIDS

SIMPLY OJ HIGH PULP 100%

Figure 3

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STROHMAN BRD D'TAL PLAIN

Figure 1

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