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AI InsightsFebruary 5, 20266 min
Predictive Data Analytics to Scale Performance Marketing
Ditch the guesswork. We use machine learning algorithms to predict user Life Time Value and scale Facebook and Google Adv campaigns.
ROAS dashboards on Facebook and Google are no longer enough if you can't interpret them quickly. The competitive gap is played on data optimization speed.
- Churn Prevention: By analyzing navigation logs, AI identifies which audience segments are about to abandon a purchase before it even happens. - Dynamic Budgeting: Algorithms automatically shift budget percentages from exhausting campaigns to emerging ad-sets in the middle of the night, ensuring a stable CPA (Cost Per Acquisition).
Machine Learning Applied to Media Buying
At E-quipe we have developed cloud infrastructures that collect multi-channel signals (Website, CRM, Adv Platforms) to create predictive models.- Churn Prevention: By analyzing navigation logs, AI identifies which audience segments are about to abandon a purchase before it even happens. - Dynamic Budgeting: Algorithms automatically shift budget percentages from exhausting campaigns to emerging ad-sets in the middle of the night, ensuring a stable CPA (Cost Per Acquisition).
The Importance of Clean Data
AI is only as powerful as the data it feeds on. Before applying any automation, we ensure the tracking infrastructure (Server-Side Tracking, Conversion API) is immaculate.Data & Insights Grafici
x4
Average ROAS
Real-time budget optimization via dynamic ML budgeting algorithms.
-22%
Reduced CPA
Cost per acquisition lowered through ML predictive targeting.
100%
Server-Side Tracking
Cookie-less infrastructure with immaculate Conversion API.
E
E-quipe Performance
Digital Laboratory
