We lost 3 weeks to data engineering every time we needed a 2-line audience rule. So we built the tool that didn't exist.
Segmentloom gives growth and marketing teams direct access to their behavioral event data — without filing a ticket or writing SQL.
Give growth teams direct access to the behavioral data they're already producing
The events are already there. Engineers instrument them, the warehouse stores them — but a growth team trying to build a retargeting audience from those events has to file a ticket and wait. The data team isn't the bottleneck. The process is.
Segmentloom is the layer between your event stream and your growth team's ad tools. It doesn't replace your data warehouse. It doesn't require a data engineer after setup. It gives marketing the audience access that was always there — just locked behind a queue.
The problem started in 2019 at a Denver fintech — and it never changed
From 2019 to 2022, Maya Rosenthal ran growth at a Denver-based payments fintech. The engineering team was competent — full event tracking, a well-maintained BigQuery warehouse, clean schemas. Everything a growth team could want.
What it couldn't deliver was speed. Every time the growth team needed an audience — users who viewed pricing twice and never upgraded, users stuck at onboarding step two — the request went into the data engineering backlog. Two to three weeks later, the audience was ready. By then, the campaign moment was gone. The behavioral signal that was urgent at week zero was noise by week three.
Maya left in 2022 to build Segmentloom. Not because the data engineers were doing anything wrong — the problem was structural. The tools for building audiences from behavioral events required SQL expertise and data engineering time that a growth team couldn't access on demand.
"We didn't need a bigger CDP. We needed a way to go from event to audience to synced ad platform in an afternoon — without the engineering queue in the middle."
Three people. One very specific problem.
Ran growth at a Denver fintech from 2019 to 2022. Watched behavioral event data sit in BigQuery, untouchable by the growth team without engineering support. Founded Segmentloom in 2022 to close that gap.
Previously built product at a B2B data tools company. Joined Segmentloom in 2022 to design the Audience Builder's rule interface — the core belief being that if a growth marketer needs a data dictionary to use a tool, the tool is broken.
Data infrastructure engineer with a background in real-time event pipeline systems. Architected Segmentloom's event ingestion layer, profile resolution logic, and the delta-sync engine that keeps audience lists current without full re-sends.
Three things we believe that shaped the product
Behavioral truth over profile guesses
A viewed_pricing event from this week tells you more about purchase intent than a signup survey from six months ago. Behavioral signals from the event stream reflect current intent. Profile attributes reflect historical state.
Engineers don't belong in the audience workflow
A data engineer's job is infrastructure: schemas, pipelines, reliability. Writing SQL to pull viewed_pricing >= 2 AND completed_onboarding = false for a retargeting campaign is not infrastructure work. Putting those tasks in the same queue wastes both roles.
Sync fast or sync never
A retargeting cohort that updates monthly is nearly worthless — most of those users have either converted or moved on. A suppression list that lags a week is still burning budget on current customers. The value of behavioral audience sync is precisely in its freshness. That's why hourly sync is a first-class feature, not a premium add-on.
Based in Denver, CO
Segmentloom, Inc.
3000 Lawrence Street, Suite 200Denver, CO 80205
[email protected]
+1 (720) 689-4416
Talk to us before you decide
We're three people, Denver-based, and we respond to every inbound ourselves. If you want to understand how Segmentloom maps to your specific event setup before requesting access, reach out directly.