CUSTOMER CHURN, ANALYTICS
Customer churn decreased by 14% in six months
Fennia Life operates in a constantly changing operating environment in the highly competitive life insurance sector. The emphasis on responsibility, increasing digitalisation, networking and changes in the work model especially affects the behaviour and needs of private customers as well as what kinds of products and services must be offered now and in the future.
Aiming at stronger retention
The cooperation with Innolink began in 2020 when Fennia Life wanted to map the factors that could be used to strengthen customer experience and commitment. With the help of research results and relationship analysis, we looked at the factors affecting customer satisfaction, service experience and the level of commitment. Based on the observations, we examined the customer segments, their motivation factors and the competitive situation in the industry more closely.
Based on the findings, we identified the need to delve deeper into customer flows. Customer flow analysis demonstrated, among other things, the accumulation of loss of income caused by annual customer churn. As a result, we ended up analysing customer churn in more detail using already existing high-quality customer information data.
3x higher probability of customer relationship termination
The customer flow analysis revealed that the churn rate of the life insurance services of Fennia Life averages approximately 11% each year for consumer customers. We set out to find answers to the following questions, for example:
- What factors do customers who terminate their customer relationship have in common?
- Which private customers are likely to terminate their customer relationship in the next year?
- What methods could be used to reduce customer churn, i.e. prevent the termination of the customer relationship?
Using a model that predicts customer churn, we identified approximately 1,000 life insurance contracts at risk of termination, their termination probability being three times higher than average.
Timely, targeted measures were effective
A concrete view of the customer group identified as having the greatest probability of churn helped Fennia Life target those customers specifically with measures that improve customer retention. With this timely response, the company was able to improve customer retention and reduce customer churn by 14% in just six months.
“We are impressed by how concrete the results were.
We quickly saw positive results after starting
to contact the presented list of customers.
All in all, we were very satisfied with the results.”
Director, Sales and Customer Accounts
Fennia Life Insurance Company is part of the Fennia Group. The Group’s services are divided into Fennia, which specialises in non-life insurance, Fennia Life, which offers voluntary life, pension and savings insurance as well as the service company Fennia-service Ltd. Fennia is the employer of just over 1,000 people and has offices in different parts of Finland.
Fennia Life is a subsidiary fully owned by Fennia. The company helps its customers succeed and offers financial security solutions for long-term savings, effective rewards and preparation for unexpected, even unpleasant events. Businesses, entrepreneurs, private individuals and households benefit from the versatile services – with the help of professionals.
Customer churn predictive model
The creation of predictive models is based on data, which is used to examine past behaviour. Fennia Life provided life insurance services for approximately 22,000 consumer customers. The amount of data was sufficiently large and diverse to create a predictive model. A data matrix was created for the material and variables from 2015 to 2021.
To create the predictive model, Innolink’s analysts tested and analysed several different machine learning models and sampling methods to achieve the most reliable results. With the resulting best possible customer churn predictive model, we identified a group of approximately 1,000 private customers who had a 30% probability of their customer relationship ending, i.e. three times higher than average. Fennia Life carefully targeted measures for this customer group and managed to reduce customer churn by 14% within just six months.
Innolink implemented the customer churn predictive model in spring 2021..
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increase the value and retention of your customer accounts!
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