Analysing customer data to identify opportunities to improve Customer Lifetime Value
Background and the problem
The client had a host of customer success activities, but they were not targeted based on data, and the results in general were unsatisfactory. In particular there was no understanding of which customer success activities produced results and which customers the activities should be targeted at.
Key outcomes
1.
Analysed customer behaviour and response to customer success activities
2.
Identified highest-value customer groups
3.
Focused customer success activities to highest-value customer groups to achieve churn reduction in the most valuable customers
Approach
Phase 1
Collected history data on the entire customer base, including their contracts and yearly billing, product mix and profitability
Phase 2
Analysed the data to identify cohorts of customers that could be targeted with specific customer success activities and divided customers into three value groups: high, medium and low
Pareto Graph
Phase 3
Analysed the impact of current customer success model (customer success activities targeted to all customers equally) and calculated the value potential for a new customer success model where the customer success activities are targeted to the most valuable customer groups
Phase 4
Based on the identified cohorts and value potential, defined a new customer success model where the limited customer success resources were allocated to serve the highest value customers where the value impact of the activities is also highest
Snapshots from the project
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Herkepeus
BUSINESS ADVISOR
outi@bellrock.fi
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