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Improving the Mobile Customer Experience by Combining User Behaviour Analysis with Customer Perceptions - Kantar & EE

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Presented by Hilary Ingleton, Head of Market Research, Everything Everywhere …

Presented by Hilary Ingleton, Head of Market Research, Everything Everywhere
Marc O’Regan, Director of Behavioural Insight, Kantar
& Ashok Kalidas, Vice President, MaPS
at Market Research in the Mobile World Europe
8 - 11 October 2013, London, Europe

This event is proudly organised by Merlien Institute
Check out our upcoming events by visiting http://www.mrmw.net

Published in: Business, Education
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  • 1. October 8 – 11 2013, London The original, premier event for the Mobile Marketing Research Industry WWW.MRMW.NET
  • 2. TITLE SPONSOR DIAMOND SPONSOR PLATINUM SPONSOR SILVER SPONSORS PREMIERE SPONSOR GOLD SPONSORS WORKSHOP SPONSORS APP SPONSOR PREMIERE SPONSOR WWW.MRMW.NET NETWORKING SPONSOR
  • 3. MEDIA & ASSOCIATION PARTNERS WWW.MRMW.NET
  • 4. Improving the Mobile Customer Experience by Combining User Behaviour Analysis with Customer Perceptions
  • 5. 2 Content Our service ambition How do overall perceptions link to customer behaviour? Understanding the impact of touchpoint experiences on perceptions INSIGHT
  • 6. WE’VE SET OURSELVES THE CHALLENGE OF BEING THE #1 FOR SERVICE ON THE HIGH STREET EE TEMPLATE FOOTER AUTHOR V.1 ON THE PHONE 11/10/2013 AND ONLINE 3
  • 7. 4 But our category is complex with a multitude of customer journeys – how do we understand what drives value in the customer experience? INSIGHT
  • 8. 5 Ultimately we want to understand all these relationships Propositions Network Customer Service Retail Digital Billing INSIGHT Relationship perceptions (CSAT, NPS) Behaviour £
  • 9. 6 We have no shortage of data….. Operational data Transactional surveys Dropped call rate Network NPS Data session failure rate Call centre NPS Average waiting time Retail NPS First call resolution Digital NPS Sales conversion Relationship Survey Outcomes Customer Focus ARPU Churn rate INSIGHT
  • 10. Customer Focus is our strategic research programme to track the overall relationship our customers have with us • Covers all touchpoints • Monitors performance in a competitive context • Used to prioritise improvement areas and drive action • Likelihood to recommend is our KPI INSIGHT 7
  • 11. Linking Survey Results to Behaviour
  • 12. The first step is to understand the relationship between customer perceptions and behaviour Propositions Network Customer Service Retail Digital Devices INSIGHT Relationship perceptions (CSAT, NPS) Behaviour £ 9
  • 13. 10 We can achieve this by linking our Customer Focus results to actual customer behaviour at an individual level We examine churn behaviour for customers that we survey in a +/-3 month window around their contract end date. For data linkage we ask customers to opt in and provide their mobile number INSIGHT
  • 14. 11 The clear relationship between likelihood to recommend and churn allows us to calculate the revenue impact of improving our recommendation scores £ INSIGHT
  • 15. Getting More Granular – Our Models to link Touchpoint Experiences with Perceptions and Behaviour
  • 16. 13 Survey and Database Variables Joint Modelling Framework From Customer Experience Survey Customer Experience For example: • Network coverage • Satisfaction with call centre • Brand • Billing • Tariff plans Headline KPIs For example: • Likelihood to Recommend • NPS INSIGHT Other Databases Operational Measures For example: • # of dropped calls • First call resolution Arrows indicate the causal relationships modeled. Behavioural and Financial Outcomes For example: • Churn/Upgrade • Spend
  • 17. 14 Examples of relationships modelled Survey – to – Survey Drop call rate Value Network Call Centre Brand Communication Recognition Survey – to – Other Databases Likelihood to Recommend Likelihood to Recommend Customer Service Metrics - First call resolution - Net promoter score - Customer satisfaction - Problem resolution Likelihood to Recommend Likelihood to Recommend Website Tariffs INSIGHT Churn/Upgrade Financial metrics
  • 18. 15 Examples of relationships modelled (cont.) Churn Dropped Calls FCR Churn estimates from the model were translated into revenue implications based on a financial model INSIGHT
  • 19. 16 Simulation Interface INSIGHT
  • 20. 17 Simulation Interface (cont.) Note: Data disguised for confidentiality INSIGHT
  • 21. 18 Modelling benefits • Putting a commercial value on Customer Experience improvements, by linking perceptions with churn behaviour, raises it up the corporate agenda • Use of our models drives Customer Experience prioritisation by quantifying the revenue impact of different potential actions, and therefore informs resource allocation decisions • Bringing in the operational metrics allows us to pinpoint the specific activity required to drive improvements – eg focusing on reducing the number of customers experiencing >x% dropped calls INSIGHT
  • 22. THANKS
  • 23. TITLE SPONSOR DIAMOND SPONSOR PLATINUM SPONSOR SILVER SPONSORS PREMIERE SPONSOR GOLD SPONSORS WORKSHOP SPONSORS APP SPONSOR PREMIERE SPONSOR WWW.MRMW.NET NETWORKING SPONSOR
  • 24. MEDIA & ASSOCIATION PARTNERS WWW.MRMW.NET
  • 25. October 8 – 11 2013, London The original, premier event for the Mobile Marketing Research Industry WWW.MRMW.NET

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