Project Summaries

Optimizing Direct Mail with Data Analytics

Optimizing Direct Mail with Data Analytics

Project Details

Client:

Quility Insurance

Opportunity:

A growing insurance sales organization needed to improve direct mail return rates

Approach:

Applied Lean Six Sigma data analytics

  • Identified multiple demographic factors that drive variation in return rates
  • Created a binary logistic regression model to predict the return rate of each piece of direct mail sent out
  • Tested the model in a known market by comparing a “top group” and “bottom group” to validate performance
  • Applied the model to planned outbound campaigns to prioritize top potential prospects and exclude mailing to low-probability prospects

Results:

  • Top group in pilot return rate was over 2x compared to the bottom group!
  • Revised mailing rules for all campaigns based on drivers of low probabilities
  • Improved lead margin by over 20% in 5 months (July to November, 2021)

“For a company that spends millions of dollars per year on leads, a 20% improvement in lead margin is nothing short of miraculous. And even better, our leadership team has learned to trust our investments in data analytics to improve real-world performance.”

~ Doug Zeh, Chief Operating Officer

Most Recent Projects