Customer Insights

Client Situation

Life insurers sells risk based products which requires superior analytical capability in understanding data on customer behaviours.

Challenge

The volume of membership data (more than 4 million rows) required to understand the customer behaviours when pricing the insurance product was becoming unmanageable when using Excel.

Solution

The membership data file processing was automated by programming it in R (statistical programming language for data analysis and visualisation) which overcame limitations in Excel.

Results

After implementing a customer insights engine using R:

• The pricing process was transformed into an agile process which cut data processing time by more than 80%.
• The use of R for analysis allowed the deeper insights to be extracted from the data resulting in deeper customer insights and sharper pricing decisions.
• Using R as a data analysis tool allowed compelling data visualisations to be created to influence clients and stakeholders.