Customer Lifetime Value
The Customer Lifetime Value (CLV) forecast is an essential part of the Top Defend solution from Onesurance. This module is designed to predict which customers potentially represent the highest value - provided they are retained in the coming year. By focusing on customers with both high termination risk and high expected value, CLV enables insurance professionals to take targeted, impactful actions.
Application of CLV
The CLV module is primarily integrated into the Top Defend, where it helps prioritize customers based on both risk and value. In addition, CLV is an important building block within Onesurance's broader customer segmentation. In this segmentation, relationships are classified based on a combined assessment of their churn probability (termination risk) and their expected lifetime value. This results in targeted customer strategies, such as retaining valuable customers (feeders) or reconsidering customers who are structurally loss-making (bleeders).
Definition of CLV
Customer Lifetime Value is composed of a combination of expected revenues and expected costs, calculated over the remaining lifetime of the customer relationship. The CLV is defined as:
CLV = (Annual revenue - annual cost) × expected customer lifetime
Annual revenues and expenses are composed of the following components:
Commission or commission income
Based on the client's existing policies and premium volumes.
Cost of contact moments
Includes service desk interactions, advisory calls and administrative handling.
Claims expense/claims handling costs
Average annual cost based on client's claims history and similar profiles.
Expected customer lifetime is an estimate of how long a customer will continue to need insurance products. This includes consideration of demographic characteristics; a young adult will generally represent a longer potential relationship than an older customer.
Data sources
To make an accurate CLV prediction, both internal and external data sources are used. These are divided into the following categories:
Policy Information
Information on the nature, duration and premium of current insurance policies.
Relationship Data
Age, family status, place of residence, occupation and other profile characteristics.
Claim data
Claims history, handling speed and claims frequency.
Contact History
Information about the number and type of customer interactions, such as emails, phone calls or advice calls.
External data
Including demographic data, market information and, when available, risk profiles at the zip code level.
Added value for insurance organizations
Making CLV central to customer management allows insurers, brokers and proxies to make informed choices about where to focus their commercial efforts. The combination of churn opportunity as well as expected customer value ensures that retention actions are focused not only on customers at risk, but on customers who are actually of strategic value to the portfolio.