Other parts of this series:
In previous posts in this series, we discussed the three types of advanced analytics: descriptive, predictive and prescriptive. This week, we would like to provide some real-world examples that outline how insurance companies are using data within their organizations.
Marketing & Distribution
Several insurers are using advanced analytics to determine the characteristics of their best customers. They then use this information to identify several key segments:
- Those who will buy anyway
- Those who need persuasion
- Those who will never buy
- Those who don’t want to be contacted.
With this information, marketing dollars can be directed towards those who need information and persuasion to make a purchasing decision and away from the other three groups. The outcome results in a significantly better ROI on marketing spend.
One insurer added 200,000 new customers in 18 months using this technique.
An Italian insurer, facing ever-increasing customer acquisition costs used advanced analytics to look inward at their existing customers to determine the characteristics of those who have left the company for a competitor.
Using this information, the analytics platform then scoured the book of business and identified those most likely to leave the organization. These customers were then targeted for special treatment, which ranged from offering them new premium credits, a stronger CRM outreach and invitations to special events and sporting matches.
The result was a significant reduction in the organization’s churn rate.
Next week, we will explore how insurers are using advanced analytics to reduce fraud and hire better, more productive employees.