con beh in retail - read after slide 30

8/8/2019 Con Beh in Retail - Read After Slide 30

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Consumer Behavior in RetailStores

Presentation 2

David R BellThe Wharton SchoolUniversity of Pennsylvania

Santiago, ChileAugust 8, 2005


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David R Bell, The Wharton School

Overview Trends / Consumer behavior framework

Sophisticated use of pricing and price promotions

Assortments and product planning

Special topics

Conclusions / Additional discussion

References


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Trends / Consumer behavior

framework


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1950 2005, SKUs: 5k 100k

Confusion, excessive focus on price

Best practices

Promote Wisely

Simplify and Minimize

Stress Convenience and Enjoyment Measure and Learn

Trends


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Focus on

Marketing activities that should increase thechance of good outcomes

Purchase acceleration

Brand switching

Volume increases

Basket effects

Store choice and store image

Background


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Background

A B

YES NO

I J K

QK

STORE CHOICE

CATEGORY CHOICE

BRAND CHOICE

QUANTITY CHOICE


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Empirical analysis

Scanner panel data Store level data

Assumptions Consumers maximize utility

Theory Economics, psychology, sociology

Background


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Promote Wisely


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Topics In-store behaviors (choice, incidence, quantity)


Promotions and consumption

Cross category effects

Consumer psychology


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In-store behaviors

85% of price effect is on brand choice [Gupta 1988]

Average effect is 75% on brand choice [Bell, Chiang

and Padmanabhan 1999]

Decomposition is explained by category characteristics

Consumer heterogeneity is important [Bucklin, Guptaand Siddarth 1998]


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In-store behaviors

Interactions with brand loyalty [Krishnamurthi and Raj1991]

Long term effects may be different[Pauwels, Hanssens

and Siddarth 2002]

Some evidence for primary demand increases


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Size of Market Basket

Total Cost

Of Shopping

Q*

Total Cost

EDLPSlope = VC

Total Cost

Hi-Lo

Slope = VC

Fixed Cost

EDLP

Fixed CostHi-Lo


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Indifference point Q* is quantity at which thestores impose equivalent costs of shopping on theconsumer [Bell, Ho, Tang 1998]

Elasticities play a role [Bell and Lattin 1998]

Stores can pursue a variety of strategies toimprove fixed and variable cost profile [Tang, Bell, Ho1998]


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Time

Quantity

purchased

QH

QL

Pure Stockpiling

Consumption Increase


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Promotions increase inventory, this increasesconsumption [Aliwadi and Neslin 1998]

Effects vary across categories[Bell, Chiang and

Padmanabhan 1999; Bell and Boztug 2004; Chandon and Wansink2002]

Food versus non-food products

Increased consumption is rational [Ho, Tang, Bell1998; Bell, Iyer, Padmanabhan 1998]


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Cross category effects

Promotions for consumption complements [Ansari,Gupta and Manchanda 2000]

Umbrella branding[Erdem 1998]

Coupon subsidies [Bell, Chiang and Knox 2004]

Consumer sensitivities [Ainslie and Rossi 1998]


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Reference effects [Bell and Bucklin 1999; Bell and Lattin2000]

Anchoring and adjustment [Hoch and Wansink 1998]

Frequency heuristic [Alba et al 1994; 1999]

Signaling [Anderson and Simester 2002]

Consumer psychology


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Prospect Theory

Return to

Regular Price

(Loss)

Utility loss

Utility gain

Provide a

discount

(Gain)

Reference

Point


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Simplify and Minimize Clutter


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Toothpaste In 1970 Colgate has 2 types, ___ today

Coffee

1990-95 new introductions / total SKUs = 40% and realcategory growth was ___

Spaghetti Sauce 1990-95 new introductions / total SKUs = 50% and real

category growth was ___

Perspective


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1. How many items?

How much variety in the assortment?

2. How to change the assortment?

How should one add / trim?

Key questions


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1. How many items? Actual and perceived variety are different

Preferences are endogenous

Simple cues matter (space, favorite items)

Reduction in SKUs can increase assortment

perceptions and sales Substitution is prevalent

Broniarcryck, Hoyer, McAlister (1998)

Boatwright and Nunes (2001)

Dreze, Hoch and Purk (1994)

Findings / beliefs


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1. How many items?

Duplication is penalized, diminishing returns touniqueness

Perceptions are heterogeneous (organized versus

random assortments)

Variety perceptions influence satisfaction and choice

Hoch, Bradlow and Wansink (1999)

Kahn and Lehmann (1991)

Findings / beliefs


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2. How to change the assortment?

Product categories as bundles of attributes Utility as additive function of attribute levels

Learning and satiation occur

Fader and Hardie (1996)

Ho and Chong (2003)

Bell, Bonfrer and Chintagunta (2004)

Findings / beliefs


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Toothpaste product category

168 SKUS Attributes: brand (10), flavor (14), form (3), function

(7), size (3)

Observations

1. There are a lot of different products

2. Full enumeration (11,760) exceeds actual (168)3. Distribution in attribute-space is non-random

Research example


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Assuming

It can be shown

+=

J

k

jt

jt

jts

)exp(1

)exp(

Research example

=

=

T

t jt

btbj

sS

T 1log1


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Advantages No need to discard data, can work with appropriate

unit of analysis

SKU level fixed effects (preferences) can berecovered via calculation from a model estimated at a

much higher level of aggregation Insights

Marketing-mix sensitivity can be recovered forattributes

Marketing-mix sensitivity can be recovered for newitems

Research example


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Special Topics


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Loyalty programs

Other issues?

Topics


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Loyalty programs

Conditions

Large variation in customer behavior

Ability to offer rewards MB > MC

Ability to measure results, take action Objectives

Direct profits [Baby Bucks]

Indirect profits [Harrahs casino]


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Critiques

Is loyalty profitable?

Correlations are 0.45 (grocery), 0.30

(industrial service), 0.29 (brokerage), 0.20

(mail order)

It costs less to serve loyal customers

Loyal customers pay higher prices for the

same bundle Loyal customers market the company


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Critiques

Direct expenses mount up

Rebates, marketing, management of resources

They can have a life of their own

Endowment effect

They often fail to meet objectives

Customers still seek alternatives, dont necessarily

increase spending


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Free riders take advantage

Incremental sales from loyal customers have to

increase even more than projected average

Slim margins preclude good rewards

Sometimes hard to give customers benefits they value

Untracked expenses accrue

Hidden infrastructure costs

Critiques


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Change customer behavior Baby Bucks / Cross merchandizing

Learn about customers Harrahs Casino

[ Competitive preemption ]

Goals and applications


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Premise: Two types of products

Products linked to a specific store [Type 1]

Other products [Type 2]

Change customer behavior


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Store A

Store B

Store C

Store D

Random allocation

based on shopping

trips:P(A) = # of trip to A

# of trips

} }

Type 1 Type 2

Meat

Wine, Beer

Produce

Specialty food

Cereals, Laundry Detergent,Bathroom Tissue



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Two ways to improve situation

Transform Type 2 products into Type 1

Increase the probability of purchase of Type 2

products



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Customers Reward cumulative purchase of products

Limited to category or related categories

Candidate categories

High involvement, frequently purchased

High prices

Type 2 to into Type 1


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Why baby products? High annual expenditure [$1,500-$2,500]

Newborns increase the frequency of shopping trips in

most families Combining grocery shopping and baby shopping is a

high priority [one stop shopping]

Affluent customers

Baby Bucks


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Program elements One Baby Buck for each dollar spent on baby items

100 Baby Bucks can be redeemed for a $10 coupon

$10 coupon can be used on any products in the store

Implementation

70 ABCO stores (Phoenix and Tucson)

6 months (August 1, 1994 - January 31, 1995)

Baby Bucks


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CHECKOUT COUPON CHECKOUT COUPON CHECKOUT COUP

CHECKOUT COUPON CHECKOUT COUPON CHECKOUT COUP

COLLECT AND SAVE

*********************************YOU HAVE EARNED

$ 53.38 IN BABY BUCKS

*********************************

A $10 ABCO FOODSGIFT CERTIFICATE

WILL BE ISSUED FOREACH $100 OF BABY BUCKSYOU REDEEM AT YOUR LOCAL

ABCO FOODS.

NOT REDEEMABLE FOR CASH

EARN BABY BUCKSFOR EVERY BABY ITEM PURCHASED

AT ABCO FOODSBETWEEN NOW AND FEB. 1, 1995

COLLECT AND SAVE $100 INBABY BUCKSAND RECEIVE A $10 ABCO FOODS

GIFT CERTIFICATE

SALES TAX NOT APPLICABLE.

A

B

C

ABCOB

ABYC

LUB

Coupon


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Hypotheses (and metrics) Total baby sales will increase

Number of baby related transactions will increase

Amount of money spend each trip on baby product willincrease

Store traffic will be unaffected

No significant spillover

Baby Bucks


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H y p o t h e s e s E x p e c t e d A c t u a l

B a b y S a l e s + +

# o f T r a n s a c t i o n + +

T r a n s a c t i o n S i z e + +

S t o r e T r a f f i c 0 +

S p i l l - O v e r 0 +

Results


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Formula Baby

Food

Diapers Baby

GM

05

10

15

20

25

30

35

Formula Baby

Food

Diapers Baby

GM

% Changein Sales

Results


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Total Baby Category Sales $6,372,501

Actual Baby Bucks Redeemed for $10Gift Certificate(29% redemption of BB coupons)

$182,650

Gift Certificates Redeemed(80% redemption)

$146,120

Cost of Goods Sold on Certificate(25% Gross Margin)

$109,590

Results


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Increase in Baby Sales $1,274,500

Gross Profits

(25% Gross Margin)

$318,625

Cost of Promotion $109,590

Net Gain on Baby Categories $209,035

Results


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Financial recap

Promotion cost per dollar sales

$109,590 / $6,372,501 = 1.72%

Return on investment

$209,035 / $109,590 = 190%

Results


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All categories are not High involvement, frequently purchased

High priced

Can we still improve the sales of these

categories?

Type 2 improvement


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H

BC

G

M

Cross merchandizing


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H

BC

G

M

Cross merchandizing


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Objective

Encourage consumers to shop a greater part of

the store by linking a low traffic category with

a high traffic category Example

Charmin 4PK @ 99 cents and get 10% off Pert

Plus

Cross merchandizing


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Cross merchandizing

Test Draw Target

Control Toothbrush

Traditional Toothpaste Toothbrush

In-Aisle Shampoo Toothbrush

Traffic Building Bath Tissue Toothbrush


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Implementation

7 retailers (geographically dispersed)

From 7 to 150 stores per retailer

29 different tests 40 stores per test (when possible)

1 week promotions, 6 months baseline

Cross merchandizing


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SAVE30ON JERGENS SOAPBATH OR PERSONAL SIZE

when you purchase Close-Up toothpasteregular, tartar or gel, 100 ml.

Limit one pkg. per coupon. Limit one coupon per customer.Coupon valid until Monday, May 9, 1994 at Loblaws & SuperCenters

Coupon


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Target Category

Traditional In-Aisle Traffic

Building

01

2

3

4

56

7

8

9

10


Building

% Increasein Sales

Results


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Target Aisle


Building

0

1

2

3

4

5

6


Building

% Increasein Sales

Results


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Baby Bucks

Category sales increase 25%

Store traffic increase 5%

Spill over 4%

Cross merchandizing

Target item increase 15%

Target category 10%

Target aisle 6%

Summary


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Customer knowledge

Premise: Knowledge helps because

Individual behavior can be predicted, pooling is

useful

Key metrics helpful for targeting


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Example Harrahs took note of how many different machines I

played (nine), how many separate wagers I placed

(637), my average bet (25 cents), and of course totalamount spent coin in

Philosophy

This is the replacement of intuition and hunch withscience COO Gary Loveman

Harrahs


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Intuition: Who is the best customer?

Gender: ____

Age: ____

Game: ____ Location: ____

Why?

Harrahs


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Details

25 million Total Rewards card holders

Customers earn meals, rooms, etc.

Results Highest three year return in industry (second largest

operator)

Wallet share is 42 percent (up from 36 percent)

Since 1998 each 1% increase contributes $125 million

in shareholder value

Harrahs


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Targeting

Identify high value segments (pooling)

Time sensitive offers to encourage

Purchase acceleration (primary demand)

Switching (secondary demand)

Differentiate offer based on location anddemographics

Harrahs


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Other issues


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Takeaways

1. Measure consumer behavior

2. Make use of theory (and experience)

3. Develop models, run experiments

4. Retailing practice can benefit from marketingscience !


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Partial References


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General

Ainslie, Andrew A. and Peter E. Rossi (1998) Similarities in Choice BehaviorAcross Product Categories, Marketing Science

Aliwadi, Kusum and Scott A. Neslin (1998) The Effect of Promotions onConsumption: Buying More and Consuming it Faster, Journal ofMarketing Research

Bell, David R, Teck-Hua Ho and Christopher S. Tang (1998) Determining Where

to Shop: Fixed and Variable Costs of Shopping, Journal of MarketingResearch

Bell, David R. and James M. Lattin (1998) Store Choice and ConsumerPreference for Retail Price Format: Why `Large Basket Shoppers PreferEDLP, Marketing Science

Burke, Raymond R. (2005) Retail Shoppability: A Measure of the Worlds BestStores Retail Industry Leaders Association

Partial References


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General

Bell, David R, Jeongwen Chiang and V. Padmanabhan, The Decomposition ofPromotional Response: An Empirical Generalization, Marketing Science

Bell, David R. and Randolph E. Bucklin (1999) The Role of Internal ReferenceEffects in the Category Purchase Decision Journal of Consumer Research

Bell, David R. and James M. Lattin (2000) Looking for Loss Aversion in ScannerPanel Data: The Confounding Effect of Price-Response Heterogeneity,

Marketing ScienceBell, David R., Jeongwen Chiang and George Knox (2005) Coupons and Budget

Constraints: Empirical Analysis of Coupon Redemption Across MultipleProduct Categories, Working Paper, The Wharton School.

Bell, David R. and Yasemin Boztug (2005) The Effect of Inventory on Category

Purchase Incidence Working Paper, The Wharton School

Partial References


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Store Image

Ho, Teck-Hua, Christopher S. Tang and David R. Bell (1998) Rational ShoppingBehavior and the Option Value of Variable Pricing, Management Science,44 (12)

Tang, Christopher S., David R. Bell and Teck-Hua Ho (2001) Store Choice andConsumer Shopping Behavior, California Management Review

Partial References


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Assortments and Product Planning

Bell, David R, Andre Bonfrer and Pradeep K. Chintagunta (2005) RecoveringSKU-level Response Sensitivities from Market Share Models Estimated onItem Aggregates, Journal of Marketing Research.

Fader, Peter S. and Bruce G.S. Hardie (1996) A Parsimonious Model ofConsumer Choice Among SKUs Journal of Marketing Research

Special Topics

Bell, David R. and Sangyoung Song (2005) Neighborhood Effects and Trial onthe Internet: Evidence from Online Grocery Retailing Working Paper, TheWharton School.

Dreze, Xavier and David R. Bell (2003) Creating Win-Win Trade Promotions:Theory and Empirical Analysis of Scanback Trade Deals, MarketingScience

Partial References

con beh in retail - read after slide 30

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