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Getting clear bundling insights and recommendations from a MBC study
Pilot with cable-internet-phone bundling
October 26, 2016
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Getting clear bundling insights and recommendations from a MBC study - - PowerPoint PPT Presentation
Getting clear bundling insights and recommendations from a MBC study - - PowerPoint PPT Presentation
Getting clear bundling insights and recommendations from a MBC study Pilot with cable-internet-phone bundling October 26, 2016 1 1 Introduction 2 2 What is a bundle? $ % 3 3 Why do we care about bundling? How can we make the Holiday
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What is a bundle?
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Why do we care about bundling?
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Holiday gift baskets Cell phone bundles Travel packages Phone/Internet/ TV bundles Bundles in CPG can be things like toothpaste/ toothbrush bundle
How can we make the best bundle?
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Let’s back-solve the problem. How can we calculate the utility for any given bundle?
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Existing approaches in quantitative market research
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Natural grouping, cluster analysis, Kano analysis Incorporating options, measurement of willingness to buy
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Existing approaches in quantitative market research – let’s use conjoint?
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Fixed bundles as an attribute Separate items as attributes
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Short introduction to Menu Based Conjoint (MBC)
A B C
AND AND
With MBC, respondents make from zero to multiple selections of options to build their preferred choice.
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- Price elasticity per item
- Price cross effects
- Price elasticity per segment
- Cannibalization/complementarity
- Revenue optimization
- Most chosen combinations
Key learning from traditional MBC studies
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What is MBC still missing?
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To answer the most generic bundling question, we thought of combining a CBC exercise and an MBC exercise CBC MBC
configure any bundle individual elasticities for the ‘a-la-carte’ menu
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Case Study
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For this project, the Cable- Internet-Phone bundling offers in the US were explored
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Survey Methodology
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An MBC exercise with two components was used to collect data from respondents
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Analysis
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Analysis approach
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Counts analysis to extract interaction effects Models selected perform a counts analysis
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Independent variables Dependent variables Which variables can we now use to link all the models together?
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a-la-carte choice Model Bundle Choice Model Variables Determine which models and variables we need
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Sawtooth Software’s MBC analyzing tool was used to generate utilities and the simulator
PRICE SERVICE OPTIONS DISCOUNT APPLIED TO BUNDLE?
BUNDLE 1 BUNDLE 2 RESULTS
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Resulting market simulator shows the preference for any two bundles a consumer might want
COMPOSITION PRICE DISCOUNT BUNDLE SETTINGS PREFERENCE SHARE REVENUE CALCULATION
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Content of the two optimal bundles
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Internet 100 MB/s TV 150 Channels Phone Extra Options US & Canada HBO and streaming
20% discount relative to offering items separately
Internet 150 MB/s TV 200Channels Phone Extra Options US & Canada Sports and streaming
20% discount relative to offering items separately
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Summary
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Summary
QUESTION APPROACH ≠ BUNDLE NOT PRE-DEFINED COUNTS
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VARIABLES SAWTOOTH
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Contact us
skimgroup.com @SKIMgroup SKIMgroup SKIMgroup
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Marco Hoogerbrugge Research Director m.hoogerbrugge@skimgroup.com +31 10 282 3544 Kevin Lattery VP, Methodology and Innovation k.lattery@skimgroup.com +1 646 645 7646 Wessel Roose Research Manager w.roose@skimgroup.com +31 10 282 3520
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Thank You!
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