Maximizing Property to Auto Cross-Sell Campaign Performance With Predictive Analytics to Achieve a 246% Increase in Policy Conversion
公司规模
1,000+
地区
- America
国家
- United States
产品
- LexisNexis® Market Magnifier
技术栈
- Predictive Analytics
- Advanced Linking Technology
实施规模
- Enterprise-wide Deployment
影响指标
- Cost Savings
- Customer Satisfaction
- Revenue Growth
技术
- 分析与建模 - 预测分析
- 应用基础设施与中间件 - 数据交换与集成
适用行业
- 金融与保险
适用功能
- 商业运营
- 销售与市场营销
服务
- 数据科学服务
- 系统集成
关于客户
One of the nation’s largest property and casualty insurers was struggling to garner a profitable rate of auto to property policy conversions among its current customer base. The company understood that increasing existing customer share-of-wallet by converting customers to bundled policies was an excellent way to achieve sustainable growth. However, traditional marketing campaigns were not yielding the desired results, leading to low returns and wasted resources. The insurer needed a more targeted approach to improve its marketing effectiveness and achieve better conversion rates.
挑战
The company faced three main challenges: identifying the most-likely-to-purchase customers, maximizing the value of its customer data, and optimizing marketing return on investment. Traditional marketing campaigns were casting a wide net, resulting in low returns and wasted resources. The ultimate goal was to improve revenue growth and increase retention rates among existing policyholders by leveraging existing policyholder data for new revenue opportunities and achieving the greatest benefit from cross-sell and up-sell efforts.
解决方案
LexisNexis provided detailed performance reports on existing programs, including demographic and responder profile data. Using LexisNexis® Market Magnifier, they developed analytics to predict how likely auto consumers would be to respond to an invitation to get a property quote and then purchase a policy. This predictive information was built into successive campaigns. LexisNexis helped design two cross-sell campaigns offering auto policyholders the opportunity to save money on premiums by adding a homeowner’s policy to their existing auto coverage. The combination of data and advanced analytics helped the insurer contain costs, streamline critical business processes, and improve their return on marketing spend.
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