Case Study: How We Drove Visitation at the Naples Zoo

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The Naples Zoo was looking to find a new agency partner who could help them drive ticket sales and increase their overall marketing ROI (Return on Investment). The agency they were working with had only been running brand awareness campaigns and had not been tracking anything beyond clicks. In addition, they also were looking for a partner who had experience running multicultural campaigns.

Our team created pixels and assisted the client with placing them on their website. We also completed test purchases to ensure everything was tracking properly
prior to launch. One week after the campaign launch, we reviewed all the data we had gathered and began making optimizations. We moved the budget towards the strategies that were driving the most conversions, created new strategies based on our learnings, and turned off strategies that were not working.

Launch Tactics

Behavioral Targeting: We used In-Market for Leisure Activities, Family Fun and Hispanic Families.
Contextual Targeting: We targeted content related to parenting and families.
Lookalike Modeling: Our proprietary algorithm created a seed audience from conversion data and targeted consumers who were similar to those converting.
Re-marketing: We re-targeted people who visited the site but did not purchase a ticket.
Cart Abandonment: We created a unique re-marketing strategy for users who had added tickets to their cart, but did not complete the checkout.
A/B Testing: We used Spanish and English versions of the of the creative when targeting Hispanic audiences and tested to see what drove more sales.

Optimizations

Behavioral: We removed the “In-Market Leisure Activities” segment and shifted more budget to “Hispanic Families” because it was performing better. We added “language browser targeting” and ran the Spanish creative on browsers set to “Spanish.”
Top Scoring Users: Once we started seeing conversions come in, we were able to use our audience scoring to create a custom strategy targeting the best users.
Lookalike Targeting: This was the best-performing strategy, so we increased budget allocation and decreased the budget on lesser-performing strategies.
REM: We increased bid and budget as the re-targeting pool grew.
Added Adaptive Segments: We added adaptive segments to weed out exhausted users from the re-targeting pool and adapted to users expressing interest by serving them more ads.
Dayparting and Site Targeting: We added a top converting website strategy and layered top performing day-parts for maximum efficiency.