A D2C brand spending $200K/month on ads across Google, Meta, TikTok, and email had no unified view of what was working. Each platform reported its own metrics, attribution was inconsistent, and the marketing team made budget decisions based on platform-reported ROAS that didn't match actual revenue. We built a unified traffic analysis dashboard with AI-powered attribution and budget optimization.
Multi-touch attribution across platforms is notoriously difficult. Customers interact with multiple touchpoints before converting, and each platform claims credit. Cookie deprecation made tracking harder. The dashboard needed to work with imperfect data while providing actionable insights that marketing teams could trust.
We built a data pipeline that ingests traffic and conversion data from all platforms, the website analytics, and the e-commerce backend. An AI attribution model uses statistical analysis to determine true contribution of each touchpoint. The optimization engine simulates budget reallocation scenarios and recommends changes with predicted impact. Natural language insights explain what's happening and why.
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Request a DemoFor the first time, we actually know which ads are driving revenue. We cut $110K in wasted spend the first month.
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