Case Studies > Insurance Carrier Identifies Leads 7x More Likely to Convert with LexisNexis® Lead Optimizer

Insurance Carrier Identifies Leads 7x More Likely to Convert with LexisNexis® Lead Optimizer

Customer Company Size

Large Corporate

Region

America

Country

United States

Product

LexisNexis Lead Optimizer
LexID
LexisNexis Marketing Risk Classifier

Tech Stack

Advanced Analytics
Predictive Models

Implementation Scale

Enterprise-wide Deployment

Impact Metrics

Cost Savings
Customer Satisfaction
Productivity Improvements

Technology Category

Analytics & Modeling - Predictive Analytics
Analytics & Modeling - Data Mining

Applicable Functions

Sales & Marketing

Use Cases

Predictive Replenishment

Services

Data Science Services
System Integration

About The Customer

The customer is a national multi-line writer of auto, home, life, and umbrella insurance. The carrier writes in excess of $1.5 billion in annual premium. As a significant player in the insurance industry, the company deals with a vast number of leads, both purchased and organically generated from its own website. Despite the volume, the company faced challenges in lead validation, which is a common pain point for insurance marketers. The carrier's agents and call center staff were burdened with the laborious task of verifying leads, which often contained false or missing information or were duplicates. This inefficiency was not only time-consuming but also costly, affecting the overall productivity and effectiveness of the marketing efforts.

The Challenge

A leading multi-line carrier was facing significant issues verifying leads, despite working hard to develop a robust lead generation program. While a plentiful supply of leads were being generated via the company’s website, the contact information was often incomplete or inaccurate. The company’s agents were spending considerable time and energy trying to prioritize and contact potential customers with sporadic success. The process was not only causing agent fatigue, it was proving to be costly and inefficient.

The Solution

Using LexID®, LexisNexis was able to identify, link, and organize lead information, including aliases, name, and address changes. This unique identifier helped in ensuring a prescribed level of identity verification. The insurer took advantage of the robust lead and insurance-specific qualifying capabilities of Lead Optimizer. By incorporating additional LexisNexis predictive models into its configuration of Lead Optimizer, the insurer gained valuable insights into predicted quoting and conversion behavior. This helped the insurer maximize its marketing ROI by focusing on higher-quality leads. The solution also included the use of LexisNexis Marketing Risk Classifier to segment marketing campaigns and prioritize incoming leads based on the risk of the identified population. This further enhanced the insurer's ability to focus on leads with the highest potential for conversion, thereby improving overall efficiency and effectiveness.

Operational Impact

10% of leads were deemed to be low quality and earmarked as a lesser priority, enabling the insurer to focus marketing efforts on the remaining higher-quality leads.
The conversion rate for higher scoring leads was seven times greater than for low scoring leads.
One in every fifteen high-scoring leads converted to a policy, whereas conversion amongst the low-scoring leads was significantly worse: one in every one hundred and four.
The carrier elected to append the leads with models that further predict quoting and converting behavior, enhancing their ability to segment and prioritize leads.
With Lead Optimizer, insurers can validate auto, home, or life leads for accuracy and prioritize marketing and communications activities, driving new revenue and better business.

Quantitative Benefit

Conversion rate for higher scoring leads was seven times greater than for low scoring leads.
One in every fifteen high-scoring leads converted to a policy.
Conversion amongst low-scoring leads was one in every one hundred and four.
Leads identified with the lowest risk had a policy conversion rate of just under ten percent.
Leads with the highest risk converted to a policy four times out of one hundred.