Children’s Physical Education Company Scores Big, Doubling New Customers
GrowFit Boosts Customer Acquisition Across Email, Social, and Direct Mail for Their Sports Programs and Physical Education for Kids Using Reach Analytics
GrowFit, a children’s health, wellness and fitness company, offers programs and physical education to children ages two to thirteen. Their game-based approach allows children to learn about teamwork and sportsmanship, build age-appropriate skills and gain confidence while having fun.
For this campaign, the goal was to bring in new signups for GrowFit’s sports programs. To achieve this goal and outperform their current benchmarks, GrowFit needed a clearer picture of who their members were so that they could effectively identify and target their best prospects.
GrowFit was eager to add a direct mail approach for their new campaign, since they had never used direct mail before, while continuing to use social media and email outreach which they had used for their previous campaigns.
They hoped that building predictive profiles of their top prospects would help them gain access to a large pool of more targeted prospects and enable rapid new customer acquisition across omni-channel campaigns. In order to measure the effectiveness of the predictive targeting, GrowFit measured net-new customer acquisition and ROI.
GrowFit chose Reach’s predictive technology to gain the power to analyze hundreds of variables and characteristics for a dynamic view of their current customers and their best prospects.
Reach’s automated cloud predictive platform enabled the brand to identify top prospects who look most like their current clients in order to target them with omni-channel campaigns. With Reach, GrowFit was able to build a look-alike model and pull a list which they have been using for quarterly campaigns. The self-service platform creates profiles in minutes, without needing to wrangle data or involve large teams of data scientists. To produce each profile, the Reach platform builds hundreds of predictive models behind the scenes and algorithmically scores the prospect universe with the model to identify top prospects.
“We didn’t know enough about our customers, all we knew was that they all had children in the household,” said Ashley Schildwatcher, Director of Sports Program at GrowFit. “Reach’s look-alike modeling has helped us launch our first of many direct mail campaigns.”
The new predictive-based campaign was a considerable success. GrowFit experienced a 100% increase in new customer sign ups following their initial campaign.
The targeted omni-channel campaign acquired 50% more net-new clients in the first week than GrowFit’s previous, non-targeted methods, and 40% more year-over-year in customer acquisition with a majority attributed to Reach’s predictive platform. The brand ultimately saw 130% ROI after the first month of the campaign.
Initial response rates were so high that campaign costs were covered and positive ROI was established within a month of the first campaign to this predictive-targeted audience.
“Data can make or break your marketing campaigns,” said Ben Barenholtz, VP of Marketing at Reach Analytics. “A lot of marketers still aren’t accurate enough with their targeting to make their campaigns successful and that’s a costly mistake. The best, most successful campaigns get attention because they are laser-targeted, engaging and they build brand awareness.”