Deploy log
DPL-003Marketingdeployed · live

Bloom — Growth Engine

AI content + paid loop driving compounding demand.

client
Bloomstack
sector
DTC e-commerce
timeline
Ongoing
shipped
2025
4.1×
return on ad spend
+180%
organic traffic
-38%
cost per acquisition
case_file
  1. stage_01 · diagnose

    The challenge

    Paid spend had plateaued and content couldn't keep pace with the channels that needed feeding. Attribution was murky, so nobody could say with confidence which spend was actually working.

  2. stage_02 · build

    The approach

    We stood up an AI content pipeline feeding a continuously optimized paid loop, wired to clean attribution. Experiments run automatically against pipeline metrics, and winners get more budget while losers get cut — no manual guesswork.

  3. stage_03 · ship

    The outcome

    4.1× return on ad spend and a compounding organic base, with a content engine that produces on-brand material at a cadence the old process couldn't approach.

    4.1xreturn on ad spend
scope_of_work

What we owned on this engagement, end to end.

  • 01Brand & creative
  • 02Performance marketing
  • 03Content engine
  • 04Attribution
build_manifest

The runtime this system ships and runs on in production.

dependencies05 loaded
Next.jsPythonOpenAIPostgresVercel
The only team I've worked with that's equally lethal in engineering and growth. Our pipeline tripled in two quarters.
Marcus Reyes · Founder & CEO, Bloomstack

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