LIVE WEBINAR Top Trends in Category Management: Accelerating Maturity & Sophistication Audio Dial In: (877) 273-4202 Passcode: 6360544#
Speaker Introductions Gordon Wade, Category Management Association Managing Partner and Director of Best Practices Vaughn Roller, Revionics Vice President of Assortment and Space 2
Implications of Change in the Marketing Ecosystem The Category Management Association 3
Agenda CatMan & The CMA Major Trends Retailer Power Growth Shopper Empowerment Big Data Impact Implications/Recommendations CatMan Commitment & Maturity Retailer/Supplier Collaboration Data & Analytics
Category Management Category Definition Category Role Category Assessment Category Scorecard Category Strategy Category Tactics Plan Implementation Category Review Demand-side Process Purpose: Optimize Shopper Experience Drives Supply-side & Replenishment Data Intensive & Increasingly Complex
Category Management Association Global Professional Community Mission: Increase CatMan ROI by Improving Shopper Experience via: Thought Leadership Sharing Best Practices Facilitating Member Interaction Professional Competence Certification
Three Major Trends Driving Change Growing Power of the Retailer Digital Empowerment of the Shopper Impact of the Big Data Big Bang
Weakened Brands Brand Equity: All Time Low TV Efficiency: Down Retailer Controls Shelf & MOT Power Shift In-store Display: Most Effective Retailer Flyers: Most Influential Retailer-owned POS & Loyalty Data Enhanced Predictive Analytic Capabilities Optimized Recommendations Target Loyal Shoppers
Threats to Conventional Food Retailers Changed Shopper Attitudes New Value Mentality Triggered by Recession Increased Shopper Individuation Increased Category Cherry Picking by Format Growth in Value Format Alternatives Dollar Stores Deep Discounters Walmart Amazon Margin Compression
Digitally Empowered Shoppers Armed with New Weapon Digital Item Level Info Ubiquitous/Immediate/Individual Data Two-way Info Flow Enables Format Leakage by Need State Explosive Growth in Digital Usage 50% using Digital 25% use Technology in 2 or more ways at Grocery Store 24% check Multiple Sources before Grocery Shopping
Digitally Empowered Access & Innovation Smartphone Shopping Lists Online Comparison: Testimonials Inventory Pricing Promotions
Digitally Empowered Shopper Data Product Data Retailer Product Details Price Inventory Product Location Store Map Targeted Offers (traditional channels) Shopper Premium Data Nutrition Eco-index Recipes Ratings & Reviews Comparisons Related Products Basket History Loyalty Card Demographic Data Shopper Data In-Store Actions & Habits Responsiveness to Offers Lists & List History In-Store Searches & Scans Shopper Location & Shopping Patterns Intent Driven Targeted Offers Digital Platform
Enables: What is the Value of Big Data? Granular Understanding of Shopper Attitudes & Behaviors Customized Merchandise & Offers at Store/SKU Level More Efficient & Effective Management of Demand & Supply
Organizing Big Data for Insights Inputs Filters Retail Loyalty Card Other Retail Behavior Social Media Media Consumption Lifestyle Behaviors Household Behavior Filter Need States Filter Analytics Outputs Need States Insights Insight Generation Category Insights Price Forecasting Optimization
Big Data Helps Manufacturers Better Understanding of Shopper Behavior Enhances Targeting Capabilities Better understanding of response efficiency by element Builds Direct Shopper Relationships Uncovers Unarticulated Needs More Effective Allocation of Retail Marketing $ s
Big Data Helps Retailers Household Level Merchandise/Offer Customization Localize/Customize Pricing Individualize Communication Target Private Brand Conversion Create Loyalty Strengthening Offers Market to Need States True Shopper Management
Big Data Enables Total Store Optimization Total Store Optimization/Customization: Dramatic >/< of Category Space Right Sizing of Categories by Cluster Assortment Customization by Cluster Shopper Segment Profit Optimization Antidote to Leakage
CMA 2013 Thought Leadership 2013 The Partnering Group, Inc. Category Management Association
CatMan Maturity Curve Data Analytics & Software Org. Skills Process & Culture
Maturity Curve Components
Analytics & Software Maturity Excelling Stage Requirements: Advanced space & assortment analytics by total store & aisle Activity based costing for category, brand & items Shopper behavior analytics by multiple shopper segments Advanced loyalty card & 3 rd party analytics by need state Individual store level supply chain analytics to reduce OOS Success models for assortment, shelf merchandising, pricing & promotion by format & banner
2013 State of the Industry Survey Manufacturer/Retailer Partnership Collaboration & Commitment = Success Collaborators get better business results!! Better Value Chain Transparency Better Shopper Understanding via Jointly Developed VOS Better Planning of What is Needed from Each Partner Better Forecasting Less Format Leakage Better ROI
23 Results: Supplier What s Working
24 Supplier Retailer Collaboration
Implications for 2018 Ecosystem Growth of Internet as Marketing Platform Shopper Individualism Drives Complexity Big Data is a Problem & Opportunity Requires Superior Data, Tools & 3 rd Party Analytics Leakage Conquered via Need State Marketing Total Store Optimization Becomes Competitive Necessity
Optimization Case Studies Leveraging Science, Data & Analytics to Right-Size Space & Localize Assortments Vaughn Roller VP Assortment & Space Revionics
What s Happening & Why? Supermarket Example: Share of food/drug/mass available dollars is shrinking 44% 28% 1995 2008 25% 2010 Pressure from All Sides: Format Encroachment Channel Blur Hyper-Competition Empowered Shopper Weak Economy Hardest Hit: Traditional Grocery!!
Strategic Implications for Retailers 53% of Categories Impacted 47% 24% 29% Categories Increasing Categories Decreasing No Change
Leveraging Science, Tools & Data Strategic Objectives Financial Objectives Business Rules zzzzzzzzzzzzzzzzzzz Operational Constraints Category Roles Category Strategies Market Data Loyalty Data Floor Plans Planograms P.O.S./T-Log Inventory Science Simulation Predictive Analytics Affinities Basket Drivers Loyalty Drivers Competitive Gaps Elasticity Right Sized Localized Space & Assortments 29
Sales Change Right Sizing Space Diminishing Returns Current Unproductive Space Allocation Space Diminishing Removal Improvement Loss From Current Sales 5000 0-5000 2200 2000 1800 1600 Linear Base Space
The Shrinking Center Store Increasing Sales while Shrinking Center Store Store A Results Impacted 110 Categories Increased YOY Sales +1.8% YOY Sales Space Removed 100 ft for New Store Features
Making Room for Growing Categories Reallocating Center Store Space to New or Growing Categories & Line Extensions Store B Results 45 Categories Reduced by 250 ft Performance for Reduced Categories Increased YOY Sales +1.0% YOY Sales Space Optimization Recommendations Made Room for Growing Categories Increased Sales in Reduced Categories
The Importance of Store Specificity Number of Stores Requiring Category Size Changes % of Stores Requiring Category Size Changes Category Increase Space Decrease Space No Change Cheese 75% 25% Yogurt 42% 58% Juice/Drinks 42% 17% 41% Cottage Cheese 17% 83% Localize Space to: Shopper Demand Market Conditions Store Format/Layout Butter/Margarine 25% 75% RTE Desserts 33% 67% Bread 42% 58%
Optimizing Inventory Across The Store Reducing Out-of-Stocks & Excess Inventory Store Average Days of Supply Pre Optimized Change % Change 80 74-6 -7.5% Enforcing Pack-Out Standards Decreased: Out-of-Stocks Excess Inventory Labor Costs Store Average Store Average Total Inventory (Cost) Pre Optimized Change % Change $ 1,090,000 $ 980,000 $ (110,000) -10.1% Excess Inventory (>60 Days of Supply) Pre Optimized Change % Change $ 288,000 $ 228,000 $ (60,000) -20.8% Optimization Reduced: Total Inventory Excess inventory
Evolving Category Roles Changing Market Dynamics Market Performance Optimization Cut Baby Diaper Space in Half Space Reduced by 24ft Space Performance Increased by 76% $35/foot (48ft) Increased to $62/foot (24ft) Stock Target Minimums Covered At Half Space, Baby Diaper Category outperformed Market at -2.6%
Market Data Impact Identify Competitive Gaps & Opportunities Optimization Without Considering Competitive Strategy Applying Competitive Strategy Change Annual Sales Impact $101,900 $111,500 9.4% Responsive Categories: Chips & Snacks Frozen Entrees Frozen Pizza Coffee Household Cleaners Baby Diapers Juice & Drinks Competitive Strategy Impact: 100 ft Re-Allocated Space 9.4% Sales Increase
Market Basket Impact Category Change With Sales Only Optimization Change With Sales & Basket Impact Net Difference Dinners/Side Dishes - 1 0 + 1 Natural Snacks +3 0-3 Basket Impact: On Category Space On Assortment Cat Litter - 2-1 + 1 Rice + 3 +2-1 Item Objective Score (Sales Only) Rank Objective Score (Sales & Basket) Rank Kraft Velveeta Shells & Cheese 12 oz 0.95 1 1.05 2 Kraft Mac & Cheese Dinner 7.25 oz 0.77 2 1.60 1 Kraft Deluxe Dinner 14 oz 0.69 3 0.73 3 Kraft 3 Cheese Mac & Cheese 7.25 oz 0.35 12 0.44 8
Loyalty Data Impact Category Change Without Loyalty (ft) Change With Loyalty (ft) Net Difference (ft) Condiments - 2 0 + 2 Cough & Cold - 3 0 + 3 Understanding Loyalty Impact: On Category Space On Underlying Assortment Household Cleaners - 4 0 + 4 Laundry Detergent - 4 0 + 4 Item Objective Score Without Loyalty Rank Objective Score With Loyalty Rank Best Foods Real Mayonnaise 9.96 1 11.86 1 Best Foods Mayonnaise Light 2.98 2 3.55 3 Heinz Ketchup Squeeze Bottle 2.88 3 3.64 2 Heinz Ketchup Easy Squeeze 2.58 4 3.24 4
39 What Revionics Does
Q & A Gordon Wade, Category Management Association Managing Partner and Director of Best Practices Vaughn Roller, Revionics Vice President of Assortment and Space