This Presentation was presented in the 23rd Edition of MRSI, the Annual Market Research Seminar by Soumya Sarkar, This paper presents a novel approach of objective driven segmentation that incorporates strategic growth goals at the forefront of the segmentation process. A combination of CHAID and 2 Step Cluster Analysis was used to segment a largely homogeneous population of online shoppers. Inclusion of growth goals in segmentation scheme led to isolation of opportunity – ensuring high actionability and impact.. AbsolutData is a global leader in applying analytics to drive sales and increase profits for its customers. AbsolutData has built strong expertise and traction with Fortune 1000 companies across 40 countries. We specialize in big data, high end business analytics, predictive modeling, research, reporting, social media analytics and data management services. AbsolutData delivers world class analytics solutions by combining their expertise in industry domains, analytical techniques and sophisticated tools

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Chicago New York London Dubai New Delhi Bangalore SingaporeSan Francisco
www.absolutdata.com
April 28, 2014
XXIII Annual Market Research Seminar
Strategic Issues & Challenges

2. Market Dynamics – Business Goals

3. © Absolutdata 2014 Proprietary and Confidential 3
Online
The travel reservation market in India
Public Services
Source: IAMAI Report - 2012
 Fast growing market with huge potential
 But highly fragmented, cluttered and
complex…
Getting more competitive by the day
 Largely driven by flight bookings
 Commoditisized offerings with low margins….
16
18
20
23
0
5
10
15
20
25
2009 2010 2011 2012
USD(Bn)
Gross Travel Bookings – by Revenue
Offline

4. © Absolutdata 2014 Proprietary and Confidential 4
Flight booking space had become too cluttered with thin margins. It was getting increasingly difficult to sustain
growth and profitability.
Need to move beyond flight
 Client wished to explore alternate travel
booking services - one that had potential for
being transitioned to the online space.
 Client selected online bus booking as a
prospective expansion avenue…
 …a non traditional online booking area but
with high potential of growth.

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Specifically client
wished to understand :
MaximizeGrowth
Which opportunities to pursue?
Identifying growth opportunities based on actual
bus travel and booking behavior
Who to target?
What are the types of bus booking travelers?
Which ones to target?
How to target them?
What are drivers of bus usage and online bus bookings?
Special packages, loyalty schemes, etc.
Business Objectives
Client wished to develop targeted strategies of service offerings and communications…
- with the overall objective of maximizing sales growth.

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Need for a holistic approach
Ensured Actionability
Ensured Targetability
Challenge was to come up with a holistic analysis plan that took care of both targetability and actionability.

7. Ensuring Actionability
Capturing Growth

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Why?
 Growth is NOT the focus
 Emphasis is on identifying well defined segments -
Targetability, NOT Actionability
 Prioritizing segments is a hit and trial method of
secondary importance
Traditional Segmentation Analysis
Step 3: Prioritizing segments
- identifying relatively more
profitable segments
Step 2: Profiling segments
Step 1: Segmentation
(Cluster Analysis)
Evaluating methodology to capture growth
This scheme works in many cases, but it wasn’t
the most appropriate approach in our case.

9. © Absolutdata 2014 Proprietary and Confidential 9
Step 1: Goal Setting
Growth goals were identified. Growth variables were
defined which formed inputs into the segmentation
algorithm.
Step 2: Growth Driven Segmentation
Identification of segments that were differentiated in
terms of growth, thus making the results highly
actionable and impactful.
Step 3: Opportunity Mapping
‘Where to play’ analysis based on opportunity size
and winnability.
Growth
Seg 1 Seg 3
Seg 2
New Approach 180⁰
We tossed the traditional approach upside-down to have growth goals at the forefront of our
segmentation scheme.

10. © Absolutdata 2014 Proprietary and Confidential 10
Several growth opportunities were considered and evaluated. Finally, two growth goals were
identified.
Category Conversion:
Converting offline bookers to online bookers
Stealing from Competition:
Converting non client-brand users to client-brand users
Premiumization:
Encouraging premium services like Volvo coaches, Wi-Fi
Increasing Travel Frequency:
Encouraging more travels
Increasing Travel Distance:
Encouraging longer travels
Potential Opportunity Feasibility
How workable is
the opportunity?
Size
How big is the
opportunity?
High
Medium
Low
Low
Low
High
High
Medium
Low
Low
Final
Selection
Defining growth goals

11. Ensuring Targetability
Focus Correction

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 Convenience and comfort (AC)
 Safety
 Ample luggage space
 Sleeper/ semi-sleeper coach
 Entertainment facilities
Mr. Shiv and family
Over-night holiday trip in summer break
Incidently, Mr. Shiv and Mr. Sundar is the same person –
Mr. Shiv Sundaram !
What is different is the
Travel Occasion
‘Occasion’ to think different
 Punctuality
 Online booking facility
 Easy cancellation/ refund policy
 Wi-Fi/ Charging points
Mr. Sundar
Short business trip in December

13. © Absolutdata 2014 Proprietary and Confidential 13
 Hence to derive meaningful and holistic
segmentation solution, we decided in favor of
segmenting occasions (trips) rather than the
respondents.
 Occasion level segmentation was a more
realistic approach enabling us to identify
sharp, well defined and distinguishing
segments rather than fuzzy overlapping
respondent groups.
Travel for a respondent is multifaceted, and needs/ attitudes/ behavior are dependent on the travel occasion.
 Initial ideations had suggested that individual preferences vary by travel occasion
 This hypothesis was further validated through pilot tests
‘Occasion’ to think different

14. Execution
Marrying Actionability with Targetability

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Our approach: Combining the best of both worlds
CHAID 2 Step Cluster Analysis
Multilevel Hybrid
Mapping dependence relationship:
Growth goals as dependent
variable
Identifying key differentiators:
Selecting variables which
differentiated growth.
Accommodating mixed scales:
Includes both numeric and categorical
segmenting variables.
Developing well defined segments: 2
step algorithm of Preclustering feeding
into Final Clustering produces well
defined segments for effective targeting.
The key operational challenge was to devise a methodology that would address the growth goals and
simultaneously produce well defined targetable segments.

16. © Absolutdata 2014 Proprietary and Confidential 16
Growth Opportunity
Business Religious
Holiday
Level 1:
Level 2:
Level 3:
KD1* KD2 KD3 KD4 KD5
Final Segments
MultilevelApproach
* Key differentiators (e.g. price sensitivity, travel frequency etc.)
CHAID with pre-defined growth objective as the
dependent variable. Purpose of visit came out to
be the 1st key differentiator of growth goal.
Second level CHAID analysis within each purpose to
identify the key differentiating variables. These served
as final segmenting variables in the next step.
Final 2 Step Cluster Analysis with key
differentiating variables as identified in Level
2.
Using key differentiators as segmenting
variables produced clean segments
differentiated by growth potential.

17. Key Insights

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 Segmentation solution yielded a comprehensive set of 15 occasion segments – across the 4
purposes of visit.
For e.g. we had 4 business segments – these were business trips in routes like Mumbai-Pune, Chennai-Hyderabad
etc. Similarly, we had 4 segments for holiday and religious trips, and 3 for visiting family/ friends.
 Key differentiators across segments were identified which included (but not limited to) frequency
of travel, spend, price elasticity, mode of booking etc.
 Need/ attitude mapping of segments provided key inputs in establishing target strategies and
customizing offerings.
For e.g. A business segment was largely comprised of trips booked by office, with little/ no say of the individual
traveler. This insight helped client design packages focused on key corporate needs like last minute availability,
booking assistance, quick confirmation etc.

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Winnability Analysis helped
evaluate actionability across
segments.
This enabled informed decisions of
‘where to play’.
For e.g. Segment 2.4 though high in
growth potential had low fitment. These
were largely offline trips made by SEC B
who preferred booking at the bus stop.
Winnability Analysis - Sample
Winnability
(Feasibility of targeting and converting)
OpportunitySize
High
High
Low
Segment 2.4 Segment 1.2Segment 1.1
Segment 4.1
Segment 2.3
Segment 4.2 Segment 4.3
(Howbigistheopportunity?)

20. Implications for MR Industry

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Occasion based
segmentation is
effective in identifying
distinguishing patterns
among online
shoppers, who
otherwise have a
predominantly
homogenous socio-
economic footprint.
This segmentation
approach can be
suitably implemented
across industries like
Hospitality, Food &
Beverage etc. which
are fundamentally
occasion oriented
Given the
segmentation scheme
works at the occasion/
trip level, it’s easier to
integrate/ validate
results from
transactional CRM
databases. This
enables extrapolating
study findings to
realistic market
estimates.
The segmentation
scheme is driven by
growth objectives. This
makes it a highly
actionable
segmentation solution
when client has a pre-
defined growth
strategies.

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