Copyright © 2004 Information Resources, Inc. Confidential and proprietary. What You Don’t Know Can Hurt You Frequent Shopper Programs and Their Effects.

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Presentation transcript:

Copyright © 2004 Information Resources, Inc. Confidential and proprietary. What You Don’t Know Can Hurt You Frequent Shopper Programs and Their Effects on Pricing March 1, 2005 Michael Heberle VP Modeling Product Management

Copyright © 2004 Information Resources, Inc. Confidential and proprietary. 2 FSP and Their Effects On Pricing  What you do know about pricing…  Tremendous growth lever  Can drastically improve operating profits and overall company performance  Not managing appropriately can be disastrous  What you don’t Know…  Price elasticity of your brand is likely more elastic than you think  What we will cover today  Frequent Shopper Program Coverage  Understanding Price Elasticity  The Impact of FSP on Price Analysis  Why the Changes?  What now?  Summary

Copyright © 2004 Information Resources, Inc. Confidential and proprietary. 3 Frequent Shopper Programs Dominate Retailing  58% of Total US ACV  7 of the top 10 US retailers have programs  More than 80% of those transactions are FSP  No signs of slowing 58% 42% Percent of Total US ACV

Copyright © 2004 Information Resources, Inc. Confidential and proprietary. 4 IRI’s Frequent Shopper Solution  February IRI includes all new FSP data and restates all databases  IRI collects net pricing for major FSP retailers  Over 94% of FSP volume  “Featured” still used for non-participants  Advertised and Unadvertised FSP included  Incorporated into all data  Price, dollar, and discount measures  Better pricing info = better pricing models  Volume spikes attributed to TPRs  True base price elasticity revealed

Copyright © 2004 Information Resources, Inc. Confidential and proprietary. 5 Understanding Price Elasticity  Price elasticity models examine the impact that price changes have on volume sales  Elasticity rules of thumb: Elasticity less than -2.0 = HIGHLY ELASTIC Elasticity between -1.0 and -2.0 = ELASTIC Elasticity between -0.5 and -0.9 = NEUTRAL Elasticity greater than -0.5 = INELASTIC % Chg in Volume % Chg in Base Price

Copyright © 2004 Information Resources, Inc. Confidential and proprietary. 6 Applying Elasticity to Business  Example Case and Profitability implications  Base price elasticity is -1.7  Year 1 - sold 10MM units at $4.29 with $2 unit margin  Year 2 - raise price by 10% - increase unit margin to $2.43 Sales before price increase 10MM units Unit price before increase $4.29 Dollar sales before increase $42.9MM Sales after price increase* 8.5MM units Unit price after increase $4.72 Dollar sales after increase $40.1MM Profit before: $20MM Lost sales 1.5MM or $2.8MM Profit after: $20.6MM x x = = Result: Increasing price 10% actually cost 15% of volume but increased profits by $0.6MM * [10,000,000 x ($4.72 / $4.29)^ -1.7 = 8,500,011 units]

Copyright © 2004 Information Resources, Inc. Confidential and proprietary. 7 Example #1 – Taking Incorrect Base Price Increase  Manufacturer contemplating 10% base price increase  Elasticity understated by 40% (-1.2 instead of -1.7) Dollar SalesProfit Incorrect elasticity shows a $573k opportunity; true elasticity reveals loss of $240k Understated elasticity misled this manufacturer and cost loyal customers AND profits

Copyright © 2004 Information Resources, Inc. Confidential and proprietary. 8 Example #2 – Passing on Price Decrease Dollar SalesProfit  Manufacturer considering following competitor’s 5% lower price  -1.8 elasticity actually -2.2 (22% difference) Understated elasticity shows a loss of $43k instead of the true $1.1MM profit This manufacturer left over $1.1 million on the table losing profits and the competitive edge

Copyright © 2004 Information Resources, Inc. Confidential and proprietary. 9 How Extensive are the Changes ?  Base Price elasticity increased  10% to 40% higher  More on highly promoted brands  Promoted Price elasticity increased  Between 30% and 70% higher  Trade coefficients decreased  Feature Only down 15% to 40%  Display Only down 10% to 25%  Feature & Display down 5% to 25%  Highly promoted categories were more affected  E.g. Frozen pizza, single-serve dinners, carbonated soft drinks experienced large changes  E.g. Soup and sandwich bags experienced only small changes Magnitude of Observed Changes Lower bound of post-FSP changes Upper bound of post-FSP changes

Copyright © 2004 Information Resources, Inc. Confidential and proprietary. 10 Until Recently Limited FSP Data was Available  Two kinds of FSP exist  Advertised and unadvertised  Only featured promotions were captured  “Lowest Reported Dollar”  Reported as promotion events  20% of FSP items captured  Roughly 60% of FSP dollars  Only gross prices reported  Did not reflect unadvertised FSP  Appeared higher than shelf prices

Copyright © 2004 Information Resources, Inc. Confidential and proprietary. 11  We now get smooth baseline  Creating clearer picture of true base sales  Volume spikes and price reductions match  True base volume more clear  More accurate price/volume relationship = more accurate elasticity BPE: -1.50BPE: Better Data Drives Better Models

Copyright © 2004 Information Resources, Inc. Confidential and proprietary. 12 Reasons Behind Higher Elasticity - Correlation  Many parts of model highly correlated with FSP discounts  Base and promoted elasticity  Feature & display lifts  Base Volume and Price  FSP discounts previously excluded are now incorporated  Without FSP discounts, models act significantly different Modeling Fact Omitting variables from a model causes coefficient errors in other highly correlated variables

Copyright © 2004 Information Resources, Inc. Confidential and proprietary. 13 Why Price Data Impacts Base Price Elasticity  Adding variable impacts on all other correlated variables  Why estimates changed for promoted price, features and displays  Base price correlation also causes changes Correlation with FSP Discounts * Correlation figures taken from evaluation of roughly 500,000 elasticity estimates

Copyright © 2004 Information Resources, Inc. Confidential and proprietary. 14 “Due to” Evaluation Revealed Reasons  98% of changes in elasticity due to improved price data  Small effects from base price and merchandising Changes in Base Price Elasticity by Cause

Copyright © 2004 Information Resources, Inc. Confidential and proprietary. 15 What You Should Know About Pricing  Know how price sensitive your brand is  All price increases can be expected to reduce sales, the real question is ‘by how much.’ Knowing your price sensitivity let’s you know the exact trade off  Focus on value and your own price  Determine whether absolute price thresholds exist, creating a “step increase” in price elasticity  Base price impacts are largest. If your brand has a unique offering that’s accepted by consumers, then price point impacts, competitive impacts, etc., matter much less  Know the importance of your competitor’s price  Cross elasticity-less important if your brand is well differentiated from the competition  Price Gaps-Maintaining gaps and exploiting ‘niches’ means not competing where you don’t have to!

Copyright © 2004 Information Resources, Inc. Confidential and proprietary. 16 DifferentiationLowHigh Brand EquityLowHigh LoyaltyLowHigh Level of InvolvementLowHigh Advertising Investment Low High CompetitorsManyFew Trade PromotionHighLow “The Role of Marketing is to Reduce Price Sensitivity” Elasticity Brand/Product Attribute More elasticLess elastic Volume “sensitivity”

Copyright © 2004 Information Resources, Inc. Confidential and proprietary. 17 Build Equity To Reduce Price Elasticity  Build Equity through Advertising or other Support Vehicles  Advertising reduces a brand’s total price sensitivity. Other vehicles may be more appropriate for smaller brands, but building equity means differentiation and lower price sensitivity  Use price elasticity as a supplementary measure of ad effectiveness  Expect to see elasticity decrease as spending goes up (assuming reasonable copy/strategy)  Expect to see elasticity decrease as copy or strategy is improved  For high spending categories, elasticities can reflect diminishing returns from increased ad spending

Copyright © 2004 Information Resources, Inc. Confidential and proprietary. 18 Innovate To Reduce Price Elasticities  Innovate and Support New Items  Successful new items can lower a brand’s total price sensitivity and improve its ability to maintain its margins. The best new products essentially avoid price competition through differentiation  In the absence of high ad spending, price elasticity reflects a brand’s success at differentiation and innovation  Must communicate product benefits through the product, packaging or category price structure, in order to command price  Changes in elasticity over time may signal fundamental changes in a brand’s well being

Copyright © 2004 Information Resources, Inc. Confidential and proprietary. 19 New FSP Data and the Effects on Price Analysis  Increased data accuracy  More robust promotional measures  More accurate net price and TPR only weeks  Proper alignment of promotion and movement data  Changes in pricing and merchandising effectiveness  Price elasticity increased significantly; both base and promoted  Lower quality merchandising lifts  Higher trade ROI  Models based on IRI data yield the most accurate price elasticity and promotion lifts in the industry  Wall Street and academic world agree

Copyright © 2004 Information Resources, Inc. Confidential and proprietary. 20 Industry Agrees with IRI Price Elasticities  “Our research indicates that IRI’s enhanced FSP information can improve the accuracy of price elasticity estimates by 40% or more for heavily promoted items” – Ross Link, CEO of Marketing Analytics, Inc.  “We analyzed price elasticity of a variety of non-alcoholic beverage categories using IRI’s new data methodology and concluded that pricing is an even more important growth lever than we previously believed. IRI’s updated methodology now captures frequent shopper discounts which provides a much more accurate view of what consumers are actually paying at the register ” – Robert van Brugge, Vice President and Research Analysts, Sanford C. Bernstein & Co., LLC.