marketing mix vi price promo
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Marketing Mix Strategies VI:
Price Promotions
Professor Ofer Mintz
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Todays Class Outline
Main takeaway: Price promotions, while used veryfrequently, often harm firms long-term
Structure:
Current Events Recap
Price Promotion Overview
Price Promotion Results
Price Promotion Calculations
Case: Consumer Sales Promotions
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Class Approach to Marketing Management
1. Understand customers, markets, and own
business
2. Develop a goal based on this understanding3. Select the appropriate marketing mediums
and mix to accomplish goal
4. Measure, evaluate, and possibly reformulate
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Recap
Understanding own business and market from
customers point of view
Shape Organization to Focus on Customers POV
Value Proposition
Points-of-Differentiation and Points-of-Parity
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Recap
-1.25
-1
-0.75
-0.5
-0.25
0
0.25
0.5
0.75
1
1.25
Economy
-1 0 1 2
FACTOR 1 Performance/Quality
FACTOR 2IS1NISSAN SENTRA HONDA
ACCORD
VW RABBIT
OLDSMOBILE
THUNDERBIRD
FORD
MUSTANGBMW
PORSCHE
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Observed
Behavior- Purchase Data
- Trackers of Behavior
Quantitative- Conjoint Analysis
- Experiments- Questionnaires
Qualitative
- Focus Groups- Interviews
- Observational / Ethnographic
Recap
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Source: Mizik (2010), MIT OpenCourseWare
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Recap
Initiator
Influencer
Decider
Buyer
User
Copyright 2011 Pearson Education, Inc. Publishing as Prentice Hall
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Recap
Copyright 2011 Pearson Education, Inc. Publishing as Prentice Hall
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Price Promotion Objectives
Consumers Encourage purchase of larger units, build trial among non-
users, attract switchers from competitive brands
Retailers
Induce to carry new items, higher levels of inventory,encourage off-season buying, encourage stocking ofrelated items, offset competitive promotions, buildingbrand loyalty of retailers, gaining entry into new retailoutlets
Sales Force Encourage support of new products, encourage more
prospecting, stimulate off-season sales
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Price Promotions Tactics
Samples
Coupons
Cash refund offers
Price offs
Premiums
Prizes
Patronage rewards
Free trials
Tie-in promotions
Copyright 2009 Pearson Education, Inc. Publishing as Prentice Hall
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Price Promotion Results
Price promotion sales come near equally from other brands,
shifting purchases from other periods, and category
expansion plus harder to quantify sources like other stores
and own-branded items
The higher the frequency and the deeper the price
promotion, the lower (toward zero) the price elasticity on the
long term
Display and feature multipliers show similar average
magnitudes; in the absence of a price cut sales often doubles
with display or feature
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Price Promotion Results
Price promotions do not influence brand equity and
stock market returns
Only 1 out of 10 price promotions contributes the profit of
a firm in middle/long run
Price promotions create both lagged and lead
effects, consistent with consumers both stockpiling
and anticipating future promotions
There is a threshold effect, discounts lower than 10% do
not lead to additional sales
Source: Blattberg et al.
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Article: Who Benefits
from Price Promotions?
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Article: If Brands are Built Over Years, Why are
They Managed Over Quarters?
Known short-term bounce in revenues
Price promotions elasticity is -3.63
Abundant short-term data
Wall Street pressures on quarter to quarter
Leads to bigger category pie
Difficult to measure long-term marketing
tactics Difficulty to get data in the past
Managers may leave business
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Metrics Used by Managers to Evaluate
Marketing Mix Activities
Marketing Mix Activity MarketingMetrics
(mean)
FinancialMetrics
(mean)
TotalMetrics
(mean)
Traditional Advertising 3.81 2.98 6.79
PR / Sponsorships 2.93 1.83 4.76
Internet Advertising 4.09 3.36 7.45Direct to Consumer 3.41 3.33 6.74
Social Media 3.63 1.90 5.53
Price Promotions 2.88 3.53 6.41
Pricing 3.86 4.00 7.86
New Product
Developments4.71 4.25 8.96
Sales Force 3.10 3.75 6.85
Distribution 3.84 4.18 8.02
Overall
3.63
3.20
6.83
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Metrics to Analyze Price Promotions
Top Five Metrics Used (% used):
1. Target Volume (77%)
2. Promotional Sales / Incremental Lift (58%)
3. Total Customers (49%)
4. Market Share (47%)
5. Net Profit (46%)
Things that stood out:
1. 80% of highest performers and 77% of managers overall
used target volume
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Price Promotion Calculations
Household
id
Choice Price End of Aisle Display
(0=No; 1=Yes)
Brand Heinz Hunts Delmonte Other
(1) (2) (3) (4)
Heinz Hunts Delmonte Other
(1) (2) (3) (4)
1100001
1100001
.
.
.
1100340
1
2
.
.
.
1
5.21 4.32 4.74 3.57
5.21 3.89 4.74 3.57
. . . .
. . . .
. . . .
3.69 3.51 3. 89 2.78
0 0 0 0
0 1 0 0
. . . .
. . . .
. . . .
0 0 0 0
How to investigate impact of promotion mix on
market share from household data
Suppose you obtain data on brand choice plus marketing
mix information (price, price discount, in-store display)
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Allobservations
Price Promotion Calculations
We can calculate market share for each brand Heinz 1319/2000=65.95% Hunts 335/2000=16.75% DelMonte 210/2000=10.5%
Others 136/2000=6.8%
Q1: If Hunts price decreased by 10% and special display was used,how much increase in market share would be expected?
Q2: If by 20% and special display was used, ?
Q3: From which brands would this expected increase in marketshare come from?
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Price Promotion Calculations
Estimate the effects of marketing mix onbrand choice
Assume consumer chooses brand (j) on purchase
occasion (t) that maximizes his/her utility
Utility may be defined as follows: Ukt= k+ 1PRICE kt+2DISPLAYkt + t
k
kt
jt
tU
UjP
)exp(
)exp()(
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How brand(j) attractive
is to customer in time t
Price Promotion Calculations
Estimate the effects of marketing mix onbrand choice
Assume consumer chooses brand (j) on purchase
occasion (t) that maximizes his/her utility
Utility may be defined as follows: Ukt= k+ 1PRICE kt+2DISPLAYkt + t
k
kt
jt
tU
UjP
)exp(
)exp()(
Sum of brands (k=4)
Brand specific constant
(avg mkt share)
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Price Promotion Calculations
Coefficients can be estimated in a way that
the log likelihood is maximized
To estimate model, one needs to select a base
brand (b/c utility is a relative concept)
Utility of base brand is set at 0
This is equivalent to subtracting the base brands
marketing mix variables from those of all brands
h t jht jPLL )},;(ln{maxmax
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Price Promotion Calculations
Results of brand choice model estimation
Using estimated coefficients, we can predictconsumers brand choice decisions when they areexposed to different marketing activities
Household
id
Choice Brand Intercepts
(k)
Price
(1)
Display
(2)
Brand Heinz Hunts Delmonte Other(1) (2) (3) (4)
Coefficients
T-value
-2.4 -2.6 -3.4
-27.1 -26.5 -30.1
-1.3
-21.3
1.0
6.6
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Price Promotion Calculations
Household
id
Choice Price End of Aisle Display
(0=No; 1=Yes)
Brand Heinz Hunts Delmonte Other
(1) (2) (3) (4)
Heinz Hunts Delmonte Other
(1) (2) (3) (4)
11000011100001
.
.
.
1100340
12
.
.
.
1
5.21 4.32 4.74 3.575.21 3.89 4.74 3.57
. . . .
. . . .
. . . .
3.69 3.51 3. 89 2.78
0 0 0 00 1 0 0
. . . .
. . . .
. . . .
0 0 0 0
Householdid
Choice Brand Intercepts(k)
Price(1)
Display(2)
Brand Heinz Hunts Delmonte Other
(1) (2) (3) (4)
Coefficients
T-value
-2.4 -2.6 -3.4
-27.1 -26.5 -30.1
-1.3
-21.3
1.0
6.6
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Price Promotion Calculations: Q1
Consumers utility function is as follows: UHeinz, t = 0 + { -1.3*(PRICEHeinz, tPRICEHeinz, t )} +
{1.0*(DISPLAYHeinz, tDISPLAYHeinz, t )}
UHunts, t = -2.4 + { -1.3*(PRICEHunts, tPRICEHeinz, t )} +
{1.0*(DISPLAYHunts, tDISPLAYHeinz, t )}
U
DelMonte, t= -2.6 + { -1.3*(PRICE
DelMonte, tPRICE
Heinz, t)} +
{1.0*(DISPLAYDelMonte, tDISPLAYHeinz, t )}
UOther, t = -3.4 + { -1.3*(PRICEOther, tPRICEHeinz, t )} +
{1.0*(DISPLAYOther, tDISPLAYHeinz, t )}
For example, for household 1, occasion 2
Utility calculations UHeinz, t = 0 + { -1.3*(5.215.21)} + {1.0*(00)} = 0
UHunts, t = -2.4 + { -1.3*(3.895.21)} + {1.0*(10)} = 0.3186
UDelMonte, t = -2.6 + { -1.3*(4.745.21)} + {1.0*(00)} = -1.989
UOther, t = -3.4 + { -1.3*(3.575.21)} + {1.0*(00)} = -1.268
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Price Promotion Calculations: Q1
For example, for household 1, occasion 2 (continued) Take exponential
Exp(UHeinz, t )= 1 Exp(UHunts, t )= 1.3752 Exp(UDelMonte, t )= 0.1368 Exp(UOther, t ) = 0.2813
Probabilities of choosing each brand Pt(UHeinz, t )= 1 / 2.7933 = 0.358 Pt(UHunts, t )= 1.3752/ 2.7933 = 0.492 Pt(UDelMonte, t )= 0.1368/ 2.7933 = 0.049 Pt(UOther, t ) = 0.2813 / 2.7933 = 0.100
The purchase probability for entire observation = expected
market shares Heinz 1151/2000 = 58% Hunts 839/2000 = 42% DelMonte 10/2000 = 1% Other 0/2000 = 0%
The denominator (exp(Ukt)) =1+ 1.3752 + 0.1368 + 0.2813= 2.7933
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Price Promotion Calculations: Q1-3
Original 10% and
display
20% and
display
Heinz 65.9% 58% 49.9%
Hunts 16.8% 42% 50%
DelMonte 10.5% 1% .1%
Others 6.8% 0% 0%
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Next Class
TOPIC:
Marketing Mix Strategies IX: Pricing
DUE: Think of a product you have and like
READ:
1. KK: Read Chapter 142. CR: Retail Frenzy: Prices on the Web Change
Hourly
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