1. Washaway Clean Debrief

2. This case is an opportunity to practice your critical thinking skills by gathering information from a variety of sources, synthesizing all the data, and creating a solution. Category Management (definition) A note about advertising and its impact on sales… just to clarify. The case also encourages you to apply concepts from EVERY chapter in your Grewal textbook: Washaway Clean – Applying every chapter to a “real-world” scenario!! Product, Price, Placement, Promotion Decisions (4P’s) Ch. 1 Sustainable competitive advantage (customer, operational, product, and locational excellence) Ch. 2 Marketing Ethics Ch. 4 Analyzing the Marketing Environment: your first exposure to demographics Ch. 5 The consumer decision process Ch. 6 Business-to-Business Marketing Ch. 7 How you structured your solutions and your presentation for Trojan Grocer. Operational excellence = full-truck discounts; locational excellence = availability of top selling products in all stores to prevent OOS. Demographic Data: who shops your category?? Consumer’s primary & secondary needs in this category; how consumers decide!! (Evaluation of alternatives; onpack sampling) Access to competitors’ data in Category Management… how to handle it ethically You were BDM’s yourselves, managing the B2B relationship between TG and WAC

3. Washaway Clean – Applying every chapter to a “real-world” scenario!! Analyzing sociocultural factors such as Uncertainty Avoidance Ch. 8 Segmentation, targeting, and positioning Ch. 9 Data Mining; Primary vs. Secondary and Internal vs. External Data Ch. 10 Product and packaging decisions Ch. 11 Diffusion of Innovation Theory: Innovators, Early Adopters, Early Majority, Late Majority, Laggards Ch. 12 Services: the Intangible Product Ch. 13 Relationship between uncertainty avoidance and willingness to try “pods” Segmentation-related data, who is your consumer (target), positioning strategies Some suggested packaging changes to better serve consumers; Pod onpacks Some teams made reference to this theory when discussing the shift to more profitable pods. Data mining = internal sales trends during ad weeks vs. non-ad weeks; POG’s; focus groups* (primary) Some teams mentioned apps as part of their promotional plans (recall Clorox app) Continued… General Case Competition

4. Washaway Clean – Applying every chapter to a “real-world” scenario!! Pricing concepts Ch. 14 Supply chain management Ch. 15 Multichannel Marketing Ch. 16 IMC planning Ch. 17 A closer look at Advertising & Sales Promotions Ch. 18 Professional Selling & Sales Management Ch. 19 Many teams included pricing changes as part of their recommendations; well supported by data; capturing value Full-truck purchases, matching ad cycles to inventory, and stocking the right items to reduce OOS by updating planograms. Cross-docking. All teams made recommendations regarding advertising and sales promotions See above!! In-depth look at traditional Food Retailer; certain categories are “staples” (traffic) Your roles were BDM roles; recall our speaker from Mondelez Continued… General Case Competition

5. Category Management, Brand Management, BDM work (overlap in this case) You may not pursue a career in this industry, but the skills you practiced are transferrable: – Complex data analysis and synthesis – Decision-making – Critical Thinking – Teamwork Case interviews – great practice! Great job by all teams!! Your thoughts – comfortable or uncomfortable? Was every piece of data relevant? Mimics real-world assignments! General Points

6. Logistics details & sales data from data warehouse – Combine ad-week sales data with logistics details, and you can see where you can generate savings and thus improve profitability, increase gross margins. Focus group data & Pater Lane’s interview – Realize that attaching pod samples or modifying packaging to encourage trial of pods is within your budget, and may be critical given the focus group comments. Combine sales data & Planogram data – Realize that top-selling items are not in enough stores; improve placement!! Demographic data – Helped you identify who your top shoppers are by demographic characteristics; helped teams craft effective plans to reach each segment. Danny Ortega interview – You cannot expect to compete on the basis of asking your distributors to discontinue your competitors’ brands. Recall how angry Danny got!! Examples of great conclusions drawn from the data…