Pulse Technologies
Predictive Analytics for Smarter Marketing Spend
Deployed ML-driven attribution models that optimized $50M in annual ad spend with 3.2x ROAS improvement.
The challenge
Pulse Technologies was allocating $50M in annual ad spend across 8 channels with no unified attribution model, relying on last-click reporting that systematically undervalued mid-funnel touchpoints.
Our approach
We designed and deployed a multi-touch ML attribution system using Python, TensorFlow, and Google BigQuery, ingesting real-time signals from paid search, social, programmatic, and email channels.
The results
$50M
Annual ad spend optimized
3.2x
ROAS improvement
Beyond the headline 3.2x ROAS improvement, Pulse Technologies fundamentally changed how its media organization makes decisions. Budget planning cycles shrank from six weeks to three days.
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“Astery didn't just build us a better dashboard — they rewired how we think about media investment. We now have conviction in every dollar we spend.”
Amara Osei-Bonsu
Chief Marketing Officer, Pulse Technologies
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