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Assessing the
Long Term Impact
of Promotions
Looking back and forward:
combining 2 different research methodologies
Today’s speakers
Maureen Arink
m.arink@skimgroup.com
Leonie Barelds-Cramer
Leonie.Barelds@pepsico.com
> Shopper Insights Manager and Business Analyst Savoury Benelux
> PhD Mansholt Graduate School
> 8 Years at Pepsico in several Consumer Insights roles
> Senior Research Director
> 20 Years at SKIM
> Focus: CPG Pricing and Promotion, Conjoint
3
In the past Request now
Conjoint Analysis Studies
for Pepsico Promotions
insights
4
Benefits But...
But...
5
Long term impact? Create a model based
on historical sales
But what about…
Proposed solution
Short term Long term
Selection of
category & country
Requirements
EDLP
Business
Questions
“Identify the immediate and long term
impact of specific existing and new
promotion types on SKU, brand and
market size”
There’s an issue…
Looking at history Looking at the futureLooking at the future
3 years of detailed sales data by
retailer (SKU volumes, prices,
distribution, etc) and promotion
executions in the same period
Modeling of impact of promotion
types in the period of promotion,
the post-promotion dip and the
long term impact on the brand
and the market
Creation of simulation tool that
predicts outcomes for different
promotion scenarios
Looking at history:
Long term model
0 3 6 9 12 15
Brand 1 (12 SKUs)
0 3 6 9 12 15
Brand 2 (9 SKUs)
0 3 6 9 12 15
Brand 4 (4 SKUs)
0 3 6 9 12 15
Brand 3 (20 SKUs)
Model
Market data
Week: Week:
Week:Week:
Weeklyvolume
WeeklyvolumeWeeklyvolume
Weeklyvolume
Validation – Overall correlation: 0.949
Respondents completed 12
virtual shopping strips
(conjoint based)
We assess sensitivities
to attributes
(brand, price, promotions)
Create a simulation tool that
predicts outcomes for different
scenarios (different promotion
types on different brands)
Looking at future:
Short term model
93%
74%
134%
108%
125%
65%
74%
70%
66%
63%
Y% discount
Y% discount on accompanying product
2 for €X
2 for €XX
Now for €Z
Revenue % growth Volume Share % growth
Immediate impact of promotion
on SKU’s volume and revenue
Also, identification of:
- Impact of promotion on 1 or several
SKUs on total brand volume and revenue
- Source of volume (i.e. where does the
increased volume come from)
Week:
Promo-week
Post-promo
‘dip’
Stabilization
Volume impact on SKU X – Promotion type “Multi-buy”
0%
56%
-2% -1% -1%
1 1.5 2 2.5 3 3.5 4 4.5 5
Key insights
•In general, the volume impact
measured in the Short term (future)
model tends to be overestimated if
compared to the (initial) volume
impact in the Long term (historical)
model.
•Deeper promotions (like “2nd for
free”) do not always have more
impact than other promotions:
initially they get a higher volume
due to higher volume per purchase
but in the long run the SKU / brand
volume may stabilize to a lower
volume level than for other
promotions
1
Promotion: “2 for X€” for SKU A
Looking at future (Short term model): volume +134%
Looking at history (Long term model) : volume +56%
Promo type Price cut (e.g. Y% off)
Multi-buy
(e.g. “2nd half price”
or “2 for X€”)
SKU initial volume impact +38% +56%
SKU LT impact +1% -1%
Brand LT impact +0% -1%
Key insights
•The best promotion type for one
channel is not necessarily also the
best promotion type in the other
channel.
•Often, the promotion that has the
highest impact is determined by the
type of channel, the type of
promotions that consumers are
used to in that channel, and the type
of consumers that go to that
channel.
2
Promotion “2 for X€” Promotion “Now Y€”
High-Low channel +171% +150%
EDLP channel +58% +246%
SKU B volume uplift, based on Short term (future)
model:
Key insights
•Different promotions have a different
impact on short term and long term
(high initial impact followed by a low
or even negative long term impact
or vice versa)
•Therefore, it is important to combine
different promotion types in order to
have a total positive result on both
short term and long term.
•In any case, promotions with
negative long term impact should be
avoided at all times
3
Promotion “2 for X€” Promotion “Now Y€”
High-Low channel +1% +6%
EDLP channel -1% +1%
SKU B Long term volume impact, based on Long term
(historical) model:
Promotion “2 for X€” Promotion “Now Y€”
High-Low channel +171% +150%
EDLP channel +58% +246%
SKU B volume uplift, based on Short term (future)
model:
BOY Constraints
ApplicabilityFrequency
Next Steps
Thank you
Maureen Arink
Senior Research Director at SKIM Group
m.arink@skimgroup.com
Leonie Barelds-Cramer
Shopper Insights Manager at Pepsico
Leonie.Barelds@pepsico.comSKIMgroup.com

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Co-presenting a webinar on “Long term impact of promotions” with PepsiCo

  • 1. Assessing the Long Term Impact of Promotions Looking back and forward: combining 2 different research methodologies
  • 2. Today’s speakers Maureen Arink m.arink@skimgroup.com Leonie Barelds-Cramer Leonie.Barelds@pepsico.com > Shopper Insights Manager and Business Analyst Savoury Benelux > PhD Mansholt Graduate School > 8 Years at Pepsico in several Consumer Insights roles > Senior Research Director > 20 Years at SKIM > Focus: CPG Pricing and Promotion, Conjoint
  • 3. 3 In the past Request now Conjoint Analysis Studies for Pepsico Promotions insights
  • 5. 5 Long term impact? Create a model based on historical sales But what about…
  • 7. Selection of category & country Requirements EDLP
  • 8. Business Questions “Identify the immediate and long term impact of specific existing and new promotion types on SKU, brand and market size” There’s an issue…
  • 9. Looking at history Looking at the futureLooking at the future
  • 10. 3 years of detailed sales data by retailer (SKU volumes, prices, distribution, etc) and promotion executions in the same period Modeling of impact of promotion types in the period of promotion, the post-promotion dip and the long term impact on the brand and the market Creation of simulation tool that predicts outcomes for different promotion scenarios Looking at history: Long term model
  • 11. 0 3 6 9 12 15 Brand 1 (12 SKUs) 0 3 6 9 12 15 Brand 2 (9 SKUs) 0 3 6 9 12 15 Brand 4 (4 SKUs) 0 3 6 9 12 15 Brand 3 (20 SKUs) Model Market data Week: Week: Week:Week: Weeklyvolume WeeklyvolumeWeeklyvolume Weeklyvolume Validation – Overall correlation: 0.949
  • 12. Respondents completed 12 virtual shopping strips (conjoint based) We assess sensitivities to attributes (brand, price, promotions) Create a simulation tool that predicts outcomes for different scenarios (different promotion types on different brands) Looking at future: Short term model
  • 13. 93% 74% 134% 108% 125% 65% 74% 70% 66% 63% Y% discount Y% discount on accompanying product 2 for €X 2 for €XX Now for €Z Revenue % growth Volume Share % growth Immediate impact of promotion on SKU’s volume and revenue Also, identification of: - Impact of promotion on 1 or several SKUs on total brand volume and revenue - Source of volume (i.e. where does the increased volume come from)
  • 14. Week: Promo-week Post-promo ‘dip’ Stabilization Volume impact on SKU X – Promotion type “Multi-buy” 0% 56% -2% -1% -1% 1 1.5 2 2.5 3 3.5 4 4.5 5
  • 15. Key insights •In general, the volume impact measured in the Short term (future) model tends to be overestimated if compared to the (initial) volume impact in the Long term (historical) model. •Deeper promotions (like “2nd for free”) do not always have more impact than other promotions: initially they get a higher volume due to higher volume per purchase but in the long run the SKU / brand volume may stabilize to a lower volume level than for other promotions 1 Promotion: “2 for X€” for SKU A Looking at future (Short term model): volume +134% Looking at history (Long term model) : volume +56% Promo type Price cut (e.g. Y% off) Multi-buy (e.g. “2nd half price” or “2 for X€”) SKU initial volume impact +38% +56% SKU LT impact +1% -1% Brand LT impact +0% -1%
  • 16. Key insights •The best promotion type for one channel is not necessarily also the best promotion type in the other channel. •Often, the promotion that has the highest impact is determined by the type of channel, the type of promotions that consumers are used to in that channel, and the type of consumers that go to that channel. 2 Promotion “2 for X€” Promotion “Now Y€” High-Low channel +171% +150% EDLP channel +58% +246% SKU B volume uplift, based on Short term (future) model:
  • 17. Key insights •Different promotions have a different impact on short term and long term (high initial impact followed by a low or even negative long term impact or vice versa) •Therefore, it is important to combine different promotion types in order to have a total positive result on both short term and long term. •In any case, promotions with negative long term impact should be avoided at all times 3 Promotion “2 for X€” Promotion “Now Y€” High-Low channel +1% +6% EDLP channel -1% +1% SKU B Long term volume impact, based on Long term (historical) model: Promotion “2 for X€” Promotion “Now Y€” High-Low channel +171% +150% EDLP channel +58% +246% SKU B volume uplift, based on Short term (future) model:
  • 20. Thank you Maureen Arink Senior Research Director at SKIM Group m.arink@skimgroup.com Leonie Barelds-Cramer Shopper Insights Manager at Pepsico Leonie.Barelds@pepsico.comSKIMgroup.com