At the height of the dot-com boom in early 2000, many Internet-oriented companies offered groundbreaking ideas and solutions for an increasingly-online world. Unfortunately, many of these same visionary businesses suffered systemically from substandard process implementation. One such startup, an insurance e-commerce marketplace, promised customers an opportunity to compare and contrast policies online to find the one perfect for them, but had burned through over $100 million in invested capital without generating return and was in desperate need of new leadership. While a new CEO set to work streamlining processes and steering the enterprise towards long-sought cash positivity, Calexus Solutions set to work optimizing this client’s online customer acquisition process. Over 18 months, Calexus utilized data collected from every click in the site (and their associated time stamps), every response in its online policy-finder questionnaire, and every prospective customer that failed to convert to an active customer. Calexus used these masses of data to dramatically expand the client’s customer funnel and drive double-digit increases in revenue.

Pre-Campaign Data Creation, Cleaning, and Enhancement

  • Appended 100 unique demographic variables and associated values to client’s existing data on customers and prospective customers.

Marketing Databases

  • Compiled customer and prospective customer information into comprehensive marketing database;
  • Connected client’s website to database to foster continuous, automated updates of active customer and lead files.

AI-Centric Analytics

  • Scrutinized client’s customer acquisition funnel and prospective customer sources, including aggregators and paid search;
  • Constructed several dozen models that facilitated real-time scoring of prospective customers based on probability for profitability;
  • Fundamentally restructured client’s online policy finder questionnaire:
    • Integrated real-time models throughout questionnaire to identify stages at which prospective customers were most likely to quit acquisition process;
    • Determined through sensitivity analysis that amount, nature, and placement of questions in the policy finder process was chief driver behind attrition rate of potential customers;
  • Estimated short-term and long-term revenue generation for all customers and prospective customers.

Campaign Design and Execution

  • Reorganized policy finder questionnaire to include fewer questions and to place most important and pressing questions near process’s start to limit attrition;
  • Developed real-time framework to sell information of leads found unlikely to be profitable to other insurance agencies at a profit; generated 40% of client’s new revenue through such lead data sales;
  • Automated entire real-time data appending, modeling, scoring, and lead sale processes by project’s conclusion.

Reporting and Feedback Loops

  • Concluded that no profit was generated for customers retained by client for one year or less; 100% of client’s profit came through policy renewals; likelihood of policy renewal established as proxy determinant of customer profitability;
    • Findings integrated into further efforts that prioritized catering to customers renewing their insurance policies through client’s marketplace.