Cost Per Action/Conversion (CPA), 65% lower than the client’s $25 CPA goal and 83% lower than the $50 CPA average across prior campaigns
A leading automotive manufacturer and carmaker, with a diverse portfolio of brands, launched a national campaign to drive high-intent consumers to its website. The company specifically wanted consumers to engage with its Build & Price shopping tool for SUVs and sedans, allowing them to customize vehicles and explore pricing before visiting a local dealership.
For this campaign, the company set an ambitious target CPA of $25, despite averaging a $50 CPA. The company’s earlier campaigns relied primarily on broad audience targeting and upper-funnel strategies, which lacked the precision necessary to consistently reach in-market vehicle shoppers.
Predactiv conducted a thorough analysis of real-time consumer engagement with SUVs and sedans. The analysis revealed which vehicle attributes—such as color, safety, reliability, performance, and total cost of ownership—generated the highest levels of interest.
Leveraging these insights, Predactiv built two highly customized audience segments: one targeting in-market SUV buyers, another targeting in-market sedan buyers. Both segments were crafted with a strong emphasis on precision to ensure maximum relevance and efficiency.
Throughout the campaign, Predactiv worked closely with the client to optimize performance, consistently reallocating budget towards the highest-performing segment.
The campaign delivered a $8.85 CPA, 65% lower than the $25 CPA goal and 83% lower than the $50 CPA average across prior campaigns.
Return on Ad Spend (ROAS), nearly 5x the benchmark
Return on Ad Spend (ROAS), nearly 5x the benchmark
Booking Rate, 75% higher than Meta’s benchmark
Cost Per Booking, 20% lower than Meta’s benchmark
Booking Rate, 75% higher than Meta’s benchmark
Cost Per Booking, 20% lower than Meta’s benchmark
Revenue-generating models, enabled by Predactiv data
Lift in models compared to a random data sample
Improvement in model performance by adding Predactiv data to the marketing consultancy’s models
Increase in model usage by the consultancy’s clients, driving significant revenue growth
Revenue-generating models, enabled by Predactiv data
Lift in models compared to a random data sample
Improvement in model performance by adding Predactiv data to the marketing consultancy’s models
Increase in model usage by the consultancy’s clients, driving significant revenue growth
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