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Case Study: A Casino In Arizona Came To Orange 142 with the Goal of a $100 CPA for Each Booking

Discover how Orange 142 exceeded a casino's expectations with a $69.43 CPA, utilizing targeted strategies and optimizations to drive conversions in this case study.

A Casino In Arizona Came To Orange 142 with the Goal of a $100 CPA for Each Booking
Case Study: A Casino In Arizona Came To Orange 142 with the Goal of a $100 CPA for Each Booking
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A casino in Arizona was looking to make a splash with their 22nd anniversary celebration. They came to Orange 142 with the goal of a $100 CPA for each booking.

One week after the campaign launch, we looked at all the data we had gathered and began making optimizations and moving budget towards the strategies that were driving the most conversions, creating new strategies based upon our learnings and turning off strategies that were not working.

Our efforts far exceeded the client's expectations, the resort saw a CPA of $69.43. They awarded Orange 142 with an additional campaign that was targeting Hispanic consumers.

How Orange 142 Delivered Results

LAUNCH STRATEGIES
  • Contextual Targeting: Gambling & Casino.
  • Lookalike Modeling: Using the clients current customer database we were able to create a lookalike model of similar customers.
  • Re-marketing: We retargeted customers who visited the site but did not book a room.
  • Behavioral Targeting: Focused on location, vacation activities, entertainment, and casino big spenders.
  • Site Reporting: We white-listed sites that indexed highly for casino & gambling.
  • Historical Geofencing: We looked at device ID’s seen at competitive casino locations and targeted them cross-device.
OPTIMIZATIONS
  • Behavioral: We shifted money into the entertainment, gambling, roulette, poker and blackjack segments.
  • Report Analyzing: We added foot traffic reporting so we could track ad exposure to casino visitation.
  • Lookalike: We increased budget allocation and decreased budget on lesser performing strategies.
  • REM: Increased bid and budget as the re-targeting pool grew.
  • Segment Implementation: We added adaptive segments helping to weed out exhausted users. 
  • Budgeting: Increased spend on the well-performing contextual targeting.

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