Case Study - Gerber

Can predictive modeling help to reach the right people with the right message?

Fact: Only 4% of moms give birth on their expected due date.

This is a well-known moving target to new parents everywhere, but it also posed a significant messaging challenge to Gerber. Gerber came to Three Deep with a request to drive targeted messages to their database within the fast-changing and highly variable 2-week window of newborn development stages. That means we needed to hit their database with appropriate messaging relevant for a newborn baby without knowing exactly when their baby was born.

OUR SOLUTION

To try to attribute birth dates to their database, we were given a list of the projected birth dates and put together a model actual birth dates with more accuracy. We performed time-based audience modeling to determine the most effective date to send their audience of new moms messages about their newborn baby while the message was still relevant.

  • Used cohort modeling to more accurately predict birth date
  • Sent messages to database during appropriate newborn phases

Results

471%

INCREASE IN ‘AVAILABLE’ CONSUMERS PER 100k

54%

YEAR-OVER-YEAR INCREASE IN CONVERSION OF REDEEMED CHECKS

482k

ESTIMATED INCREASE IN RETAIL REVENUE PER 100,000 CONSUMERS

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