Using Algorithmic Audiences to Execute More Cost-Effective Ad Campaigns
The digital advertising team at a multinational electronics company uses retargeting ad campaigns to engage prospective customers and increase conversions on their website. While they were building audiences with business rules and Adobe Audience Manager (AAM) lookalike models, they were eager to expand their reach in a cost effective way. Using clickstream data from Adobe Analytics, Syntasa built audiences of visitors with high propensity to purchase, and when the company evaluated them with their rules-based and AAM models, they found Syntasa's audiences performed much better across several key KPIs.
Key Facts and Results:
- 9 custom algorithmic models launched in 3 weeks
- Conversion rates for Syntasa audiences were 2x higher than rules-based audiences
- Campaign achieved 42% spend savings vs. forecast
In this case study, discover how Syntasa's algorithmic propensity models increased reach and conversion rates while achieving a lower CPA (Cost Per Action) for the company's retargeting campaigns.
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Syntasa helps brands exploit their first-party behavioral data from websites, apps, and devices to create better analytics, make better decisions, and take better actions. Our self-service platform provides digital professionals with the capabilities they need to collect and process data, develop custom AI/ML models, and activate them in production systems. We were named a Cool Vendor for Personalization by Gartner and Dixons Carphone won IMRG’s award for ‘Best Use of AI in eCommerce’ for their personalized recommendations.