This document summarizes a presentation on improving the mobile customer experience. It discusses combining analysis of user behavior data with customer perception survey data. Models are used to link experiences across different touchpoints like network, retail, billing etc. to perceptions of value and loyalty. Behavioral outcomes like churn are also linked. This allows understanding the revenue impact of improving customer experience and prioritizing improvement actions. Simulation tools demonstrate potential impact of different experience improvements on key metrics like likelihood to recommend.

1. October 8 – 11 2013, London
The original, premier event
for the Mobile Marketing
Research Industry
WWW.MRMW.NET

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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

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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