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Segmentation and Targeting

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Good Puppy! Data General advertisement in Forbes Magazine, ... Can you come up with descriptive names for each cluster (e.g., professionals, techno-savvy, etc. ... – PowerPoint PPT presentation

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Title: Segmentation and Targeting


1
Segmentation and Targeting
  • STP (Segmentation, Targeting, and Positioning) as
    the core components of marketing strategy
  • Needs-based segmentation
  • Cluster Analysis

MBA, Session 2 1
2
Segmentation Discussion
  • Present overview of method (today)
  • Discuss managerial issues/extensions (next Tue)

3
Currently, Most Segmentation Projects Provide.
Insights
4
SAMPLE SEGMENTATION STUDY FOR A HEADACHE REMEDY


Savvy Functionalists
Disciplined Bodies
Reluctantly Reliants
Super-Stressed Reactionaries
ChronicCombatants
Adults
17
10
17
14
12
Past 30 Day HeadacheSufferersVolumeMed
TreatersMed Volume
132513 25
100 100 100 100
131613 20
161816 15
191621 17
13813 10
SufferReg/OcclyRegularly
8235
5820
7523
458
6310
Severity of Headache(6 pt scale)
4.0
4.4
3.7
3.3
3.1
of All Headaches Mild / Moderate 100
Severe 100 Migraine
100
163133
12912
182018
12911
13 1013
Share of Pain Days Mild / Moderate Severe
Migraine
100 453322
100652015
100602515
100681814
10065 2015
Treat Judiciously
Concern
Reaction toHeadache
Upsetting,Distracts From Responsibilities
Sharply Limits Life
Reach forthe Cure (Med) Quickly
Move AboutOTC MedsIf Gets Worse
OTC Meds atFirst Twinge
Mostly Rx, OTC With Non-meds
Rx and OTC ...Relaxation
Put off Till Severe,Then OTC Meds
Treatment
Desired MedAspects
Fast
Powerful,Long-lasting Relief
No Side Effects
Safe
Immediacy
Targeting Opportunities
5
In the Final Analysis.
Little Measurable Value Most segmentation
projects are one-time Projects that drain
resources
6
STP is a Core Business Process
STP - (Segmentation, Targeting, Positioning) is a
Decision Process
  • To identify and select groups of potential
    buyers...
  • Organizations, Buying Centers, Individuals
  • Whose needs within-groups are similar and whose
    needs between-groups are different (S)
  • Who can be reached profitably (T)
  • With a focused marketing program (P)

7
How We Think About Segmentation
  • Instinctively, we think about target market
    segments, that are
  • Easily defined
  • Clear-cut
  • And reachable . . .

8
  • So you think you know your customers? Meet Stella
    Burns. For two years, weve been mailing her
    coupons for cosmetics, and she hasnt redeemed a
    single one! Perhaps you should take a closer look
    at your customer profiles and buying habitsRight
    Stella? Good Puppy!
  • Data General advertisement in Forbes Magazine,
    1998

9
How Many DifferentGroups Are Here?
10
On the Other HandIs this Segmentation?
  • Ad in London Newspapers, 1913
  • Men wanted for hazardous journey. Small wages,
    bitter cold, long months of complete darkness,
    constant danger, safe return doubtful. Honor and
    recognition in case of success.
  • Ernest Shackleton,
  • Did it work?

It is not entirely clear whether Ernest
Shackleton actually placed such an ad. At worst,
this makes for an interesting apocryphal story.
11
A Four-Phase Process for Successful Segmentation
Analysis Project
Phase IV Analysis and Implementation
Phase I Planning and Design
Phase II Qualitative Assessment
Phase III Quantitative Measurement
Internal Assessment Planning
Qualitative Research
Quantitative Survey
  • Objective(s) of segmentation
  • Resources
  • Constraints
  • Interview Materials Development
  • Qualitative Data Collection
  • Deep needsIdentification
  • Decision-Making Process Assessment
  • Sample Design
  • Questionnaire Development
  • Data Collection

Segmentation Analysis
  • Cluster Analysis
  • Portfolio Analysis
  • Positioning Analysis

Implementation Through Database Tools
Database Review
  • Call Center
  • Web
  • Sales call patterns
  • Promotion
  • .
  • Primary data already available
  • Secondary data

Classification Tool Development
  • Discriminant function
  • Binary (CART) tree

Prototype Implementation Exercises
  • What ifs?
  • Relevant groups involved?
  • ..

Basic Idea Do segmentation analysis on a small
(random) sample of customers, but leverage the
insights across the entire customer base.
12
Needs-Based Segmentation Distinguish Between
Bases and Descriptors
  • Basescharacteristics that tell us why segments
    differ (e.g., needs, preferences, decision
    processes).
  • Descriptorscharacteristics that help us find and
    reach segments.
  • (Business markets) (Consumer markets)
  • Industry Age/Income Size Education Locati
    on Profession Organizational Life styles
    structure Media habits

13
Variables to Segmentand Describe Markets
14
Segmentation (for Carpet Fibers)
Perceptions/Ratings for one respondent Customer
Values
..
..
.
.
.
.
.
.
.
.
.
.
.
.
D
.
.
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.
A
.
.
.
.
.
.
Strength (Importance)
..
..
Distance between segments C and D
.
.
.
.
.
.
.
.
.
.
B
.
.
.
C
.
.
.
.
.
.
.
A,B,C,D Location of segment
centers. Typical members A schools B light
commercial C indoor/outdoorcarpeting
D health clubs
.
.
.
.
Water Resistance (Importance)
15
Targeting
Segment(s) to serve
.
.
.
.
.
.
.
.
.
.
.
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.
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.
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.
Strength(Importance)
.
.
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Water Resistance (Importance)
16
Which Segments to Serve?Segment Attractiveness
Criteria
17
Selecting Segments to Serve
E
Strong
Firms Competitive Position
B
Medium
D
A
C
Weak
Low
Average
High
Segment Attractiveness
18
Segment Economics forDriving Segment Selection
Source McKinsey Co. Report, October 2001
19
Positioning
Product Positioning
.
.
Us
.
Comp 1
Comp 2
Strength(Importance)
Water Resistance (Importance)
20
Segmentation Process Summary
  • Articulate a strategic rationale for segmentation
    (i.e., why are we segmenting this market?).
  • Select a set of needs-based segmentation
    variables most useful for achieving the strategic
    goals.
  • Select a cluster analysis procedure for
    aggregating (or disaggregating customers) into
    segments.
  • Group customers into a defined number of
    different segments.
  • Choose the segments that will best serve the
    firms strategy, given its capabilities and the
    likely reactions of competitors.

21
Segmentation Methods Overview
  • Factor analysis (to reduce data before cluster
    analysis).
  • Cluster analysis to form segments.
  • Discriminant analysis to describe segments.

22
Cluster Analysis forSegmenting Markets
  • Select variables for analysis these should be
    based on them providing meaningful ways to define
    the needs of customers.
  • Define an overall measure to assess the
    similarity of customers on the basis of the needs
    variables.
  • Group customers with similar needs. The software
    uses the Wards minimum variance criterion and,
    as an option, the K-Means algorithm for doing
    this.
  • Select the number of segments using numeric and
    strategic criteria, and your judgment.
  • Profile the needs of the selected segments (e.g.,
    using cluster means).

23
Doing Cluster Analysis
a distance from member to cluster
center b distance from I to III
24
Single Linkage Cluster Example
  • Distance Matrix
  • Co1 Co2 Co3 Co4 Co5
  • Company 1 0.00Company 2 1.49 0.00Company
    3 3.42 2.29 0.00Company 4 1.81 1.99 1.48 0.00C
    ompany 5 5.05 4.82 4.94 4.83 0.00

ResultingDendogram
1
2
3
Company
4
5
1
2
3
4
5
Distance
25
Wards Minimum Variance Agglomerative Clustering
Procedure
  • First Stage A 2 B 5 C 9 D 10 E 15
  • Second Stage AB 4.5 BD 12.5
  • AC 24.5 BE 50.0
  • AD 32.0 CD 0.5
  • AE 84.5 CE 18.0
  • BC 8.0 DE 12.5
  • Third Stage CDA 38.0 CDB 14.0 CDE 20.66 AB
    5.0
  • AE 85.0 BE 50.5
  • Fourth Stage ABCD 41.0 ABE 93.17 CDE
    25.18
  • Fifth Stage ABCDE 98.8

26
Wards Minimum Variance Agglomerative Clustering
Procedure
98.80
25.18
5.00
0.50
A
B
C
D
E
27
Interpreting Cluster Analysis Results
  • Select the appropriate number of clusters
  • Are the bases variables highly correlated?
    (Should we reduce the data through factor
    analysis before clustering?)
  • Are the clusters separated well from each other?
  • Should we combine or separate the clusters?
  • Can you come up with descriptive names for each
    cluster (e.g., professionals, techno-savvy,
    etc.)?
  • Typically, the market is segmented first, and
    then you independently evaluate your ability to
    reach the segments (i.e., separately evaluate
    segmentation and discriminant analysis results).
    However, such an approach may not necessarily
    result in segments that can be targeted.

28
Profiling Clusters (PDA Example)
29
Discriminant Analysis forDescribing Market
Segments
  • Identify a set of observable variables that
    helps you to understand how to reach and serve
    the needs of selected clusters.
  • Use discriminant analysis to identify underlying
    dimensions (axes) that maximally differentiate
    between the selected clusters.

30
Two-Group Discriminant Analysis
XXOXOOO XXXOXXOOOO
XXXXOOOXOOO XXOXXOXOOOO XXOXOOOOOOO
Price Sensitivity
X-segment
Need for Data Storage
O-segment
x high propensity to buy o low propensity
to buy
31
Interpreting Discriminant Analysis Results
  • What proportion of the total variance in the
    descriptor data is explained by the statistically
    significant discriminant axes?
  • Does the model have good predictability (hit
    rate) in each cluster?
  • Can you identify good descriptors to find
    differences between clusters? (Examine
    correlations between discriminant axes and each
    descriptor variable).
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