CDPs Close Data-to-Revenue Loop
Charles Chretien, co-founder of Prequel, on the modern data stack’s ROI problem
This is really a packaging and buyer problem, not a data volume problem. A horizontal warehouse, ETL, or observability tool can prove that data moved or got cleaned, but that still leaves a data team to turn it into revenue. A CDP starts closer to the money. It takes customer events, builds audiences, pushes them into Meta, Google, email, and messaging tools, then shows whether CAC, CTR, and conversion improved.
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The workflow is much tighter in a CDP. The inputs are a small set of app, web, CRM, and warehouse events. The outputs are a small set of ad and messaging destinations. That narrow path makes it possible to template common jobs like suppression, retargeting, lookalikes, and conversion syncing, so marketers can act without a large data team.
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That tighter loop makes ROI legible. Twilio highlights Adevinta using Segment to build suppression lists and audience targeting that lifted Facebook ad ROI by 12 percent and cut annual marketing costs by €190K. Hightouch frames the same value in operational terms, improving ROAS by sending warehouse audiences and conversion events directly into ad platforms.
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The category has already reorganized around this logic. Reverse ETL alone turned out to be too small and too indirect as a standalone budget line, which is why Census was acquired and Hightouch moved up into a fuller CDP motion. Customer.io describes CDP as a feeder product that lowers integration friction, then expands into higher value messaging and automation spend.
The next step is that warehouses and data infrastructure vendors keep moving into packaged business workflows. Marketing went first because it has the clearest feedback loop, but the same verticalization pattern is likely to spread into observability, support, finance, and AI products where the product can tie data work to a visible operating metric.