Marketing Mix VI Price Promo

8/13/2019 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



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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



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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 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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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


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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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


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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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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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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Household

id

Choice Price End of Aisle Display

(0=No; 1=Yes)


(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)


(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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Marketing Mix VI Price Promo