Download - Measuring the “carryover” effects of pricing

Pricing Using Dynamic Demand

Modeling

Measuring the “Carryover” Effects of

Joe SakachDirector - Consumer & Customer Insights

Joy JosephVice President, Analytics

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


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


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

separatelyVolume 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


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


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


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

Sta

nd

ard

ize

d V

olu

me

Im

pa

ct


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 nGeo 1

• Week 1

• Week 2

• …Week nGeo 2

• Week 1

• Week 2

• …Week nGeo 3


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


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


Case Study


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


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


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


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


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


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 ImpactWeek 0 Impact


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


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




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 3.2100.0

93.3

Ye

ar

Ag

o

Ow

n T

rade

Dis

co

un

t D

epth

Non-P

rom

ote

d P

rice

Ca

teg

ory

Co

mp

Err

or

X-C

ate

go

ry C

om

p

Dis

trib

ution

Oth

er*

Cu

rre

nt Y

ear

*Other includes TV and Economic Factors

Week 0 Effect Only 1.3 1 0.5 0.3 2 0.9 2.4 3.2


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


Further Pricing & Promotional

Innovation In Progress…

Depth of Discount Point of

Diminishing Returns

Consumer-level Promotional

Effects

Co

nve

rsio

n P

rop

en

sity In

de

x

Cost Index


Questions


Model Fit • R-Square: 0.89

• Average Error: 2.7%

• Absolute Error: 8.3%

0

50000

100000

150000

200000

250000

300000

35000012/3

1/0

6

03/3

1/0

7

07/0

1/0

7

10/0

1/0

7

01/0

1/0

8

04/0

1/0

8

07/0

1/0

8

10/0

1/0

8

01/0

1/0

9

04/0

1/0

9

07/0

1/0

9

10/0

1/0

9

01/0

1/1

0

04/0

1/1

0

07/0

1/1

0

10/0

1/1

0

Actual Predicted

-40.0%

-20.0%

0.0%

20.0%

40.0%

Error