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 gift Cell phone Travel Phone/Internet/ Bundles in CPG best bundle? baskets bundles packages TV bundles can be things like toothpaste/ toothbrush bundle 4 4

Let’s back-solve the problem. How can we calculate the utility for any given bundle? 5 5

Existing approaches in quantitative market research Natural grouping, cluster Incorporating options, analysis, Kano analysis measurement of willingness to buy 6 6

Existing approaches in quantitative market research – let’s use conjoint? Fixed bundles as an Separate items as attribute attributes 7 7

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. 8

Key learning from traditional MBC studies • Price elasticity per item • Price cross effects • Price elasticity per segment • Cannibalization/complementarity • Revenue optimization • Most chosen combinations 9

What is MBC still missing? % ! 10

To answer the most generic bundling question, we thought of configure combining a CBC any bundle exercise and an CBC MBC individual MBC exercise elasticities for the ‘a-la-carte’ menu 11

Case Study 12 12

For this project, the Cable- Internet-Phone bundling offers in the US were explored 13 13

Survey Methodology 14 14

An MBC exercise with two components was used to collect data from respondents 15

Analysis 16 16

Analysis approach 1 2 3 Which variables can Determine perform we now use to link all which models and a counts analysis the models together? variables we need # a-la-carte choice Model Counts analysis to extract Independent variables interaction effects Bundle Choice Model Dependent variables Models selected Variables 17 17

Sawtooth Software’s MBC analyzing tool was used to generate utilities and the simulator SERVICE OPTIONS DISCOUNT APPLIED TO BUNDLE? BUNDLE 1 PRICE RESULTS BUNDLE 2 18

Resulting market simulator shows the preference for any two bundles a consumer might want BUNDLE SETTINGS COMPOSITION PRICE $ DISCOUNT % PREFERENCE SHARE REVENUE CALCULATION 19

Content of the two optimal bundles Internet 100 MB/s Internet 150 MB/s TV 150 Channels TV 200Channels Phone US & Canada Phone US & Canada Extra Options HBO and streaming Extra Options Sports and streaming 20% discount relative to offering items separately 20% discount relative to offering items separately 20 20

Summary 21 21

Summary # QUESTION APPROACH ≠ BUNDLE NOT COUNTS SAWTOOTH VARIABLES PRE-DEFINED 22 22

Contact us Marco Hoogerbrugge @SKIMgroup Research Director m.hoogerbrugge@skimgroup.com +31 10 282 3544 SKIMgroup Kevin Lattery VP, Methodology and Innovation SKIMgroup k.lattery@skimgroup.com +1 646 645 7646 Wessel Roose Research Manager w.roose@skimgroup.com skimgroup.com +31 10 282 3520 23 23

Thank You! 24 24