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(MRSI- 1/3) Optimizing growth with multilayered occasion based segmentation

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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..

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(MRSI- 1/3) Optimizing growth with multilayered occasion based segmentation

  1. 1. © Absolutdata 2014 Proprietary and Confidential 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. 2. Market Dynamics – Business Goals
  3. 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. 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.
  5. 5. © Absolutdata 2014 Proprietary and Confidential 5 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.
  6. 6. © Absolutdata 2014 Proprietary and Confidential 6 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. 7. Ensuring Actionability Capturing Growth
  8. 8. © Absolutdata 2014 Proprietary and Confidential 8 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. 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. 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. 11. Ensuring Targetability Focus Correction
  12. 12. © Absolutdata 2014 Proprietary and Confidential 12  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. 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. 14. Execution Marrying Actionability with Targetability
  15. 15. © Absolutdata 2014 Proprietary and Confidential 15 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. 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. 17. Key Insights
  18. 18. © Absolutdata 2014 Proprietary and Confidential 18  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.
  19. 19. © Absolutdata 2014 Proprietary and Confidential 19 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. 20. Implications for MR Industry
  21. 21. © Absolutdata 2014 Proprietary and Confidential 21 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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