Baby Boomer Segmentation:

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Cracking the C.O.D.E. A Case Study Step 1: Consumer profiling Joe’s Cookies utilized a hybrid of ACNielsen Homescan Panel data and POS-based profiles to identify its preferred consumer. Since Joe’s Cookies had low penetration in the marketplace, the company used panel data to profile the total category, and then used Spectra Opportunity Finder Solutions to profile individual SKUs. The result of this analysis: Joe’s Cookies gained an understanding of how its brand consumers differed from the overall cookie category and competitors. The typical Joe’s Cookies buyer skewed to African-American and Hispanic ethnic makeup, earned $50,000–$100,000 per year and lived in a household with children. ■ See chart 1. Chart 1: Cookie consumer profiles Joe’s Jane’s Cookie Cookies Cookies Category 16 oz. 16 oz. White Med. High Low High African Am. Low High Very Low Hispanic Low High Very Low < $50K Low Low Low $50K+ High Very High Medium $100K+ High Low Very High No Kids in HH Low Very Low Very High Kids in HH High Very High Very Low Source: ACNielsen Homescan & Spectra Step 2: Opportunity gapping Joe’s Cookies then ranked retailer stores based on the “fit” between the store consumer profile and the Joe’s Cookies consumer profile, quantifying the consumer opportunity gap. The analysis determined that store opportunity varied greatly once the consumer was inserted into the equation. For example, Joe’s Cookies found Store A and Store B identical in every transactional way. Joe’s Cookies had two facings in each store, and the store shelf set and total sizes were virtually identical. However, sales results for Joe’s Cookies were anything but identical. Store A sold approximately $90 per week of cookies, while Store B sold closer to $230 per week. A consumer trade area analysis for each store uncovered very different shopper bases. Store A was located in an urban setting with many households without kids in its consumer trade area. Store B, on the other hand, was in a rural setting with many households with kids in its consumer trade area. As a result, Store A was not the underperforming store it initially appeared to be, but in fact, had captured most, if not all, of its opportunity. Store B, initially thought to be over-performing in its trade area, was actually under-performing and should have sold an incremental $130 more per week. ■ See chart 2. Instead of allotting resources against a store that appeared to be an under-performer, Joe’s Cookies targeted the real underperforming store. Joe’s Cookies followed the C.O.D.E. method and assessed the different demand drivers and demand inhibitors affecting the store in order to chart a path for Store B growth. This exercise was repeated for other chains to diagnose the amount of unconverted opportunity by account and develop tactical plan for realizing untapped potential. Chart 2: Opportunity gapping Store A: $90 in Sales Store B: $230 in Sales Consumer Trade Area Consumer Trade Area Few Kids—Urban Many Kids—Rural Consumer Opportunity Gapping Gap Upside: $8 Gap Upside: +$130! Source: ACNielsen Homescan & Spectra 48 Fall/Winter 2006
Step 3: Dynamic clustering The next step for Joe’s Cookies was to make similar recommendations to its retailer that could be executed in a scalable manner. Joe’s Cookies clustered similar stores based on consumer, store, and performance attributes including consumer fit, opportunity gaps, competitive interaction and existing store sales. In doing so, Joe’s Cookies focused its efforts against several types of consumers and enabled action that was scaled yet appeared customized on the shelf. Dynamic Clustering also identified which clusters were not only a strong fit, but quantified the upside opportunity. This approach allowed Joe’s Cookies to take action where it was needed and to minimize where it was meeting demand. Demonstrating the power of Dynamic Clustering in action, when applied from the category down to the SKU level, Joe’s Cookies executed against the opportunity for its brand and the category. ■ See chart 3. Chart 3: Dynamic consumer profiling—allows you to take action where there is potential Category/Brand Consumer Fit Gapping Opportunity Clusters 20 Stores $2.7 Million Gap 35 Stores $0.8 Million Gap 68 Stores $0.0 Million Gap Step 4: Executing for the consumer Turning to tactical considerations, Joe’s first cluster (Blue Collar Suburban) represented $2.7 million in sales, spread across 20 stores. It appears to be under-performing with respect to many product types and within certain cookie sub-segments. Joe’s Cookies implemented a dynamic clustering framework and pursued tactics that included: • identifying cluster potential to assist with assortment decisions; • determining the competitive forces affecting each dynamic cluster to assist with tactics; • assigning key merchandising roles to SKU-level items by dynamic clusters to determine the turf and image enhancers; • allocating shelf size based on dynamic clusters; • performing SKU-level rationalization based on consumer demand and potential sales by cluster to put the right product in the right store. The Retail C.O.D.E framework has helped many manufacturers and retailers unlock hidden sales opportunity previously masked by results aggregated at the account, region or trade area level. C.O.D.E. proponents integrate a variety of consumer and retail information to de-code available opportunities and implement comprehensive action plans designed to improve product and category performance. Are you ready to crack the Retail C.O.D.E.? Your sales depend on it. Your consumers demand it. Competitive Interactions Sales Influencers 46 Stores $0.0 Million Gap 22 Stores $2.7 Million Gap 10 Stores $1.1 Million Gap Source: ACNielsen Homescan & Spectra 49
Page 1 and 2: CONSUMER Insights today for tomorro
Page 3 and 4: 4 On the Cover: Baby Boomer Segment
Page 5 and 6: 1. Consumer Profiling—accurately
Page 8 and 9: Simply put, there is no shared cult
Page 10 and 11: Chart 4: Segmenting Baby Boomer hou
Page 12 and 13: Chart 5: New family configurations
Page 14: Global Household Product Sales: Inn
Page 17 and 18: Stepping Outside Your Own Borders?
Page 19 and 20: garbage bag sales (40%), almost env
Page 21 and 22: Identify and Target High Opportunit
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Page 26 and 27: Aligning the cross hairs For market
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Page 30: Employee Empowerment: The Key to Ca
Page 33 and 34: The Answer for Busy Professionals S
Page 35 and 36: Open your window to collaborative b
Page 38 and 39: Gas Price Hikes continued from page
Page 40 and 41: Concurrently, the competing warehou
Page 42: Chart 5: Rising gas prices will imp
Page 46 and 47: the potential demand. The result is
Page 48 and 49: 3. Store Attributes. These may rang
Page 52: Trendwatch Walk-In Retail Clinics:
Page 55 and 56: Track the New Health & Wellness Tre

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