Always on
The standard
The catalog pauses when the agency pauses, when the tool sleeps, when the operator logs off.
Dynamic Commerce OS
Catalog, cohort, and lifecycle flows run between sprints, between reviews, between holidays.
The operating system for DTC catalog growth.
Cohort signal, tailored variants, algorithm-led reallocation, run as one continuous operation.
InsideLive targeting · Tailored experiences · Algorithm-led
Three fundamentals. One compounding operation.
The same three beats the algorithm rewards, engineered as one continuous DTC operation.
OUTCOME · 01STEP 01–02
First-party cohort signal at the source, fed to the catalog the algorithm optimizes against.
Live targeting.
OWNED BY HEAD OF GROWTH · CONTRIBUTION-MARGIN READ
Volume seeds tailoring. Every cohort by catalog cluster gets its own variant set against its own hypothesis. The audit trail carries the count.
QUARTERLY BATCH · WEEKLY COHORT × SKU
OUTCOME · 02STEP 02–03
A different creative and a different page per cohort, shipped at algorithm pace.
Tailored experiences.
OWNED BY FOUNDER-OPERATOR · LTV READ
Feed-driven creative knows the cohort. The page surfaces the cluster. Server-side measurement holds the identity across all three.
STATIC PDP · PER-COHORT FEED
OUTCOME · 03STEP 03–04
Kill rate fires inside the cycle. Spend reallocates to the cohort that pays back.
Algorithm-led.
OWNED BY CFO · LTV:CAC READ
Testing closes into contribution margin. Signal becomes cohort reallocation. The cycle closes against the baseline the CFO co-signed.
WIDE BAND · AUDITED CM CURVE
Six layers, on your account.
The same six layers that run on every Commerce OS account, adapted to DTC realities. Catalog-aware, cohort-aware, lifecycle-aware.
Layer 01Infrastructure
Clean catalog signal at the source
Server-side GA4 · Meta CAPI · TikTok Events API · Pinterest Conversions API · Shopify or WooCommerce integration · feed management · consent layer.
Layer 02Intelligence
Live read of your cohort
Catalog and category demand reads · prospect/retention split research · creative competitor mapping · audience reads validated against your cohort data.
Layer 03Strategy
A plan the algorithm executes
Channel mix across Meta · TikTok · Google PMax · Google Shopping · YouTube · Pinterest. Prospect/retention budget split, AOV banding, lifecycle architecture.
Layer 04Ad Engineering
Variants at algorithm pace
Catalog-aware creative · static · video · UGC · feed-driven dynamic creative · landing pages tied to angle and SKU. UGC sourcing and brief packs included.
Layer 05Optimization
Spend follows the cohort, continuously
Bid · budget · placement · variant reallocation across every active channel. Plus lifecycle: Klaviyo flow architecture, send-time and cadence optimization, segmentation by cohort.
Layer 06Analytics
Every dollar mapped to LTV
Cohort + LTV modeling · contribution-margin tracking · attribution audit with documented confidence ranges · MMM with geo-holdouts when scale supports.
Each cycle compounds the last.
Last week's cohort signal becomes this week's budget split. This quarter's retention curve shapes next quarter's acquisition. Continuous, not episodic. Always on, never starting from zero.
Site read
Tracking, conversion, and offer surface read end to end.
In
- Your site, today
- Buyer + funnel context
Out
- ICP / offer profile
- Funnel-state snapshot
Market read
Category, ICP, and competitor creative mapped for credible openings.
In
- Live competitor field
- Category demand
Out
- Category gap map
- Competitor-creative atlas
Bets placed
A ranked set of angles, audiences, and offers built to win.
In
- Market + funnel read
- Channel economics
Out
- Ranked bet list
- Budget allocation
Variants shipped
Production-grade ads against every bet: copy, image, video, landing.
In
- Bet brief
- Brand system
Out
- Hundreds of variants
- Matched landing pages
Signals captured
Real spend, real audiences. Every click and conversion attributed cleanly.
In
- Real spend, real audiences
- Cross-channel conversions
Out
- Unified signal stream
- Variant-level performance
Decisions executed
Winners scaled, losers killed, budget reallocated. Every cycle, your sign-off.
In
- Variant performance
- Spend-to-outcome ledger
Out
- Scale / kill calls
- Reallocated budget
Phase 01 · Site readPhase 02 · Market readPhase 03 · Bets placedPhase 04 · Variants shippedPhase 05 · Signals capturedPhase 06 · Decisions executed
Dynamic Ad runs six measurement surfaces on one continuous mesh: 01 Site read, 02 Market read, 03 Bets placed, 04 Variants shipped, 05 Signals captured, 06 Decisions executed. Every surface reads every other in the same 7-second tick, with human-operator approval on every action that reaches an ad platform. Fragmented stacks pass signal in batches between vendors; this loop runs full-mesh in lockstep.
The number is ordinary. The operation isn't.
Three rows on the canon axes. Same metric, three different operations behind it. The page hands you the language for the internal CFO conversation.
Algorithm-led
The standard
An agency's iteration count is bounded by its hour bank.
Dynamic Commerce OS
Commerce OS's iteration count is bounded by cohort signal, not by staff hours.
Human-approved
The standard
Most AI tools auto-pilot inside a slice you cannot audit.
Dynamic Commerce OS
Commerce OS routes every cohort reweight and budget shift to a named operator.
Read against your pre-engagement baseline. The operating record reads below.
One hospitality account. Six layers. The operating record.
Apollo Palm Hotel
Boutique hospitality · 48-key design hotel · multi-market inbound · direct-booking acquisition
Apollo Palm Hotel is a 48-key boutique design property in Psyrri, Athens. Commerce OS runs the full six-layer operating model on the direct-booking funnel: editorial creative across Meta, Google Search, and Google Hotel Ads, geo-segmented prospecting across six source markets, lifecycle flows stitched to cohort identity. The read is direct-revenue contribution net of OTA cannibalization, against a pre-engagement baseline the operator signed.
Six layers · One data flow
Pre-arrival and post-stay flow behavior feeds Analytics, naming which source markets compound repeat booking and which churn after first stay. Intelligence carries that read into the next market-cluster definition. Strategy reweights spend across markets and the prospect-to-retention boundary. Ad Engineering ships the next editorial variant against the market that compounds, Optimization reallocates on signal, the cycle closes against the direct-contribution baseline.
Google SearchGoogle Hotel AdsGeo-segmented prospectingLifecycle flows
Monthly source-market cohort refresh · monthly direct-contribution snapshot · 90-day operating record
Cycle in progress · operating record publishes at cycle close
Run the read on your operation.
Looking for B2B pipeline instead of DTC catalog?
See Dynamic Lead OSThe questions buyers ask before engaging Commerce OS.
Is Commerce OS live yet?
Yes. Commerce OS runs today on Apollo Palm Hotel, a 48-key boutique design hotel in Psyrri, Athens. The same six-layer operating model that runs Lead OS on Medistat (B2B) runs on Apollo in hospitality mode, against Commerce OS economics: editorial-grade creative, geo-segmented prospecting across six site-language markets, pre-arrival and post-stay lifecycle flows, source-market cohort and LTV measurement net of OTA cannibalization, with direct-revenue contribution as the reporting truth. The cycle is in progress; the operating record publishes at cycle close.
How does Commerce OS handle iOS, privacy, and signal loss?
Server-side measurement deployed at engagement start: Meta CAPI, TikTok Events API, Google Enhanced Conversions, GA4 server-side via GTM SS. Event match quality target of 7.0 or above. Post-purchase survey (Fairing or Elevar) runs continuously as ground-truth attribution. The operating record reads against survey-validated revenue, not platform-attributed ROAS.
Do you replace our agency, tool, or team?
No. Triple Whale stays. Klaviyo stays. Your in-house growth lead stays. The agency may stay or wind down depending on overlap. Commerce OS is the operating layer above your existing stack: we run the operation that acts on what your tools already show you, continuously, with a named operator and an audit trail. The wedge is operational, not procurement.
How is Commerce OS priced?
Engagement-scoped from the audit. Hybrid model: retainer for the operating layer, ad-spend management on the platforms you authorize, optional setup or wedge engagements that fold into a flagship retainer. The audit names scope; price follows scope.
What size brand is Commerce OS for?
$5M to $200M annual revenue. Below $5M, paid acquisition is rarely the bottleneck. Above $200M, the engagement runs inside an institutional procurement cycle that the audit-led entry does not match. The cleanest fit sits between $20M and $80M, where the prospect/retention split is the operating decision the founder reads weekly.
Which DTC categories does Commerce OS work in?
Strongest fit: Beauty / skincare (replenishment, retention compounds the LTV math), Health / supplements (subscription-led), Pet (subscription). Multi-SKU apparel as opportunistic close. We do not run flash-fashion, low-margin commodity DTC, or one-and-done categories where lifecycle does not compound.