Measuring the “carryover” effects of pricing

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Standard pricing models evaluate point in time consumer price sensitivity, looking at the relationship between consumption changes vis-à-vis pricing or promotional changes one week at a time. Consumer price sensitivity is a more gradual phenomenon that builds over time, with shocks on consumption reverberating several weeks following a price change. This is true for own as well as competitive pricing effects- it is easy to underestimate how much impact a competitor’s price has on a brand if one is just looking at one week at a time- the shock carries over or “persists” in later purchase cycles, regardless of price stabilizing to a new level or reverting back. We use a Dynamic Time Series model (Vector Autoregression) to capture the contemporaneous as well as lagged effect of pricing and promotions (own as well as competitive) to capture this “carryover” effect. This can help prevent marketers from underestimating the extent and duration of own as well as competitive pricing action.

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Measuring the “carryover” effects of pricing

  1. 1. Pricing Using Dynamic Demand Modeling Measuring the “Carryover” Effects of Joe Sakach Director - Consumer & Customer Insights Joy Joseph Vice President, Analytics
  2. 2. 2 Copyright © SymphonyIRI Group, 2010. Confidential and Proprietary. 2 Copyright © SymphonyIRI Group, 2011. Confidential and Proprietary. Overview • Standard pricing models evaluate point in time consumer price sensitivity, looking at the relationship between consumption changes vis-à-vis pricing or promotional changes one week at a time • Consumer price sensitivity is a more dynamic phenomenon that extends over time, with shocks on consumption reverberating several weeks following a price change • We use a Dynamic Time Series model to capture the contemporaneous as well as lagged effect of pricing and promotions to capture this “carryover” effect • This can help marketers develop more effective promotion plans that maximized effectiveness of own promotions and minimize the impact of competitive promotions
  3. 3. 3 Copyright © SymphonyIRI Group, 2010. Confidential and Proprietary. 3 Copyright © SymphonyIRI Group, 2011. Confidential and Proprietary. Marketers Perceptions on Pricing (Based on Survey Responses from SymphonyIRI Clients) • 83% of responders used some level of econometric analysis including elasticity models to drive pricing decisions • 50% managed price (promotional and everyday) gaps to key competitors • …but only 30% accounted for post-event factors influencing pricing effects and lifts 71.4% 28.6% Evaluate Pricing & Promotional Lifts within week of change Adjust lifts for Forward Buying & Repeat Purchases
  4. 4. 4 Copyright © SymphonyIRI Group, 2010. Confidential and Proprietary. 4 Copyright © SymphonyIRI Group, 2011. Confidential and Proprietary. A Primer on Contemporary Pricing Models Current pricing models capture all the major drivers that impact sales, but they correlate the impact of these drivers on volume sales within each week in the analysis time period separately Volume Sales in Week Base & Promoted Price For Week Quality Trade For Week Special Trade Programs (Multiples, Bonus Packs, Retailer Specific events) in Week Competitive Price & Trade For Week Category Trend, New Product Launches and Seasonality For Week
  5. 5. 5 Copyright © SymphonyIRI Group, 2010. Confidential and Proprietary. 5 Copyright © SymphonyIRI Group, 2011. Confidential and Proprietary. Why is this a problem? • …because promotional and pricing effects “carry over” well-beyond the week of the event itself and looking at just the event week will: – Understate or overstate impact of the event – Not reveal any insights on optimal time gaps (hiatus) between events, leading to inefficiency Initital Promotional Lift generated by TPR (Includes core buyers and incremental triers) Promotional Events are followed by a dip resulting from “forward purchase acceleration” effects (a.k.a pantry-stocking”) Short-term Post-Promotional Dip could be followed by lifts from incremental repeat buyers inlater purchase cycles
  6. 6. 6 Copyright © SymphonyIRI Group, 2010. Confidential and Proprietary. 6 Copyright © SymphonyIRI Group, 2011. Confidential and Proprietary. So What About Competitive Cross Pricing Effects? • Competitive pricing effects also carry over beyond the week of the competitive event driven by – Consumers taken out of normal purchase cycles due to competitive pantry- stocking – Consumers retained by competing brands through repeat purchases Carryover negative effects from proportion of switchers retained by competitor in later purchase cycles Initial negative impact from competitive promotion Hiatus period before repeat losses set in
  7. 7. 7 Copyright © SymphonyIRI Group, 2010. Confidential and Proprietary. 7 Copyright © SymphonyIRI Group, 2011. Confidential and Proprietary. Solution: Dynamic Time-Series Modeling • Dynamic Time Series modeling, especially Panel Vector- Autoregressions look at the effects of drivers over multiple time-periods • Output from these models measure the effect of consumption “shocks” due to drivers over consecutive time periods Lag in Weeks StandardizedVolumeImpact
  8. 8. 8 Copyright © SymphonyIRI Group, 2010. Confidential and Proprietary. 8 Copyright © SymphonyIRI Group, 2011. Confidential and Proprietary. So what’s a Panel VAR? • Ability to measure continuous demand over a period of time • VAR models can handle only time-series data, “Panel VAR” can leverage time periods across multiple geographies • Week 1 • Week 2 • …Week n Geo 1 • Week 1 • Week 2 • …Week n Geo 2 • Week 1 • Week 2 • …Week n Geo 3
  9. 9. 9 Copyright © SymphonyIRI Group, 2010. Confidential and Proprietary. 9 Copyright © SymphonyIRI Group, 2011. Confidential and Proprietary. Application to Trade Promotion Planning • While just looking at the promotion week, Feature & Display could be most profitable but other tactics may yield overall better cumulative incrementality • The post-promotion dip driven by forward-buying is not an ideal period to be promoting again as consumers are still working on the pantry they stocked up in the previous promotions • Ideal point to promote again is when the repeat buying and/or forward- buying starts to taper off- in below instance it would be around week 6
  10. 10. 10 Copyright © SymphonyIRI Group, 2010. Confidential and Proprietary. 10 Copyright © SymphonyIRI Group, 2011. Confidential and Proprietary. Application to Competitive Response Strategy • Successful competitive promotions should not be immediately responded to, but rather leverage modeled insights to determine the optimal hiatus during which counter-promotions will not obtain the intended benefit as consumers already have a stocked up pantry and your category is not on their shopping list
  11. 11. 11 Copyright © SymphonyIRI Group, 2010. Confidential and Proprietary. 11 Copyright © SymphonyIRI Group, 2011. Confidential and Proprietary. Case Study
  12. 12. 12 Copyright © SymphonyIRI Group, 2010. Confidential and Proprietary. 12 Copyright © SymphonyIRI Group, 2011. Confidential and Proprietary. Background • Study objectives – Understand promotional impacts beyond the week of execution – Use results to inform a more effective trade promotion strategy • Analysis framework – Market-level data – 4 years of weekly data – Competitive set of both intra- and inter- category products – Control for other major drivers (e.g. Advertising and Economic factors) that are not reported here
  13. 13. 13 Copyright © SymphonyIRI Group, 2010. Confidential and Proprietary. 13 Copyright © SymphonyIRI Group, 2011. Confidential and Proprietary. Demand Drivers Summary • Managing competitive threat is key for this segment -0.3 -0.2 -0.1 0 0.1 0.2 0.3 0.4 Category Comp X-Category Comp Non-Promoted Price Distribution Own Trade
  14. 14. 14 Copyright © SymphonyIRI Group, 2010. Confidential and Proprietary. 14 Copyright © SymphonyIRI Group, 2011. Confidential and Proprietary. Impulse Response Curves - Price • Promoted discounts show strong forward-buying behavior with minimal repeat purchases. -0.2 -0.15 -0.1 -0.05 0 0.05 0.1 0.15 0.2 0.25 0 2 4 6 8 10 12 14 16 Weeks Discount Depth Forward-Buying Dip Minimal Repeat Purchases Initial Promo Lift
  15. 15. 15 Copyright © SymphonyIRI Group, 2010. Confidential and Proprietary. 15 Copyright © SymphonyIRI Group, 2011. Confidential and Proprietary. Cumulative Trade Impact • Cumulative impact of promotional price changes are significantly lower than week zero impact would indicate 0 0.05 0.1 0.15 0.2 0.25 Cumulative Impact Week 0 Impact
  16. 16. 16 Copyright © SymphonyIRI Group, 2010. Confidential and Proprietary. 16 Copyright © SymphonyIRI Group, 2011. Confidential and Proprietary. Impulse Response Curves - Trade • Lagged effects for F&D and Disp offset initial promotional lifts • Feature generates significant repeat purchasing • Optimal hiatus of 8-9 weeks between promotions -0.1 -0.05 0 0.05 0.1 0.15 0.2 0.25 0 2 4 6 8 10 12 14 16 Weeks Feat & Disp Feat Only Disp Only Forward-Buying Dip Repeat Purchases Optimal Hiatus ~ 8-9 wks
  17. 17. 17 Copyright © SymphonyIRI Group, 2010. Confidential and Proprietary. 17 Copyright © SymphonyIRI Group, 2011. Confidential and Proprietary. Cumulative Trade Impact • Cumulative impact of Features exceeds that of Feat & Disp • Initial promotion lift of Displays is almost offset by forward buying impacts 0 0.05 0.1 0.15 0.2 0.25 Disp Only Feat & Disp Feat Only Cumulative Impact Week 0 Impact
  18. 18. 18 Copyright © SymphonyIRI Group, 2010. Confidential and Proprietary. 18 Copyright © SymphonyIRI Group, 2011. Confidential and Proprietary. Impulse Response Curves - Competitors • Some competition has an immediate impact on the modeled product but for others the effect is lagged -0.03 -0.025 -0.02 -0.015 -0.01 -0.005 0 0.005 0 2 4 6 8 10 12 14 Competitor A Discount Competitor B Discount Competitor C Discount
  19. 19. 19 Copyright © SymphonyIRI Group, 2010. Confidential and Proprietary. 19 Copyright © SymphonyIRI Group, 2011. Confidential and Proprietary. Impulse Response Curves – Category Switching • Switching to products outside of the category is also likely occurring as a result of dealing -0.016 -0.014 -0.012 -0.01 -0.008 -0.006 -0.004 -0.002 0 0 2 4 6 8 10 12 14 16 Category 1 Switching Category 3 Switching Category 6 Switching
  20. 20. 20 Copyright © SymphonyIRI Group, 2010. Confidential and Proprietary. 20 Copyright © SymphonyIRI Group, 2011. Confidential and Proprietary. Sources of Volume Change The source of volume change produced by the analysis puts a slightly different light on what drove year over year change than looking at week of execution alone would have suggested, with the Dynamic approach explaining overall year-over-year change better – Lesser gain due to everyday price change & Trade/ Depth of discount – Greater loss due to Category Switching. 1.1 0.4 0.0 0.4 0.5 1.8 2.4 3.2 100.0 93.3 YearAgo OwnTrade DiscountDepth Non-PromotedPrice CategoryComp Error X-CategoryComp Distribution Other* CurrentYear *Other includes TV and Economic Factors Week 0 Effect Only 1.3 1 0.5 0.3 2 0.9 2.4 3.2
  21. 21. 21 Copyright © SymphonyIRI Group, 2010. Confidential and Proprietary. 21 Copyright © SymphonyIRI Group, 2011. Confidential and Proprietary. Summary of Findings • The cumulative impact of trade tactics are not the same…Feature promotions outperform Feat & Disp when taking into account lagged effects • Significantly higher competitive and category-switching effects than indicated by conventional models • Pricing as a standalone lever may be less attractive than previously hypothesized because of forward-buying effects • Pay attention to the timing of promotions to minimize impact of forward buying and competitive impact
  22. 22. 22 Copyright © SymphonyIRI Group, 2010. Confidential and Proprietary. 22 Copyright © SymphonyIRI Group, 2011. Confidential and Proprietary. Further Pricing & Promotional Innovation In Progress… Depth of Discount Point of Diminishing Returns Consumer-level Promotional Effects ConversionPropensityIndex Cost Index
  23. 23. 23 Copyright © SymphonyIRI Group, 2010. Confidential and Proprietary. 23 Copyright © SymphonyIRI Group, 2011. Confidential and Proprietary. Questions
  24. 24. 24 Copyright © SymphonyIRI Group, 2010. Confidential and Proprietary. 24 Copyright © SymphonyIRI Group, 2011. Confidential and Proprietary. Model Fit • R-Square: 0.89 • Average Error: 2.7% • Absolute Error: 8.3% 0 50000 100000 150000 200000 250000 300000 350000 12/31/06 03/31/07 07/01/07 10/01/07 01/01/08 04/01/08 07/01/08 10/01/08 01/01/09 04/01/09 07/01/09 10/01/09 01/01/10 04/01/10 07/01/10 10/01/10 Actual Predicted -40.0% -20.0% 0.0% 20.0% 40.0% Error

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