A two-month test cut new customer acquisition cost (CAC) by 50% and increased engagement by 200%.
The challenge
"The most famous bar on the planet" still needed digital ads to fill the room, and couldn't tell which ones did.
The first gap was digital metrics, not visits. Impressions, clicks, engagements and followers didn't show whether an ad drove anyone in.
A second challenge was inflated reporting. Chief Media Officer Leejon Killingsworth had grown to distrust print and radio reps' numbers.
The remaining issue was no ROI on creative. He wanted to choose creative based on customer visits, the way ecommerce marketers use clicks.
The solution
Create the data foundation: a database from the bar's WiFi. Coyote Ugly began with Adentro (formerly Zenreach) in 2013. Guest WiFi collected contacts, and Customer Data built a customer database from them.
Deliver the campaign: email first. Email Marketing ran on that database. Walk-Through Rate™ measured how many recipients visited after a message. That gave Leejon a visit-based benchmark before he moved to paid ads.
Prospect: ads modeled on real visitors. Adentro then built prospecting audiences modeled on the profile characteristics of on-premise visitors through the Affinity Network. Those audiences ran the digital ad campaigns.
Read the outcome: the same yardstick for ads. Walk-Through Rate™ now covered digital ads too, reporting people who responded with a visit. For the first time, Leejon knew actual ROI and CAC.
Why the combination mattered
Guest WiFi built the original audience; Email Marketing and Walk-Through Rate™ established visit-linked reporting; Affinity Network modeled later prospecting on actual visitors; and the same visit measurement was applied to paid campaigns. The acquisition-cost change has an undefined baseline.
The results
- 50% reduction in new customer acquisition cost after a two-month test
- 200% increase in engagement
- First measured view of actual ROI and CAC
Customer perspective
“This information helps us continuously craft better marketing messages and get them in front of the people who are more likely to become new customers. It's all based on real data we've collected on existing customer preferences.”