GA4 says $47K. Google Ads says $62K. Shopify says $51K. Three platforms, three numbers, none match. The Attribution & Measurement Recovery Framework takes your stack from "zero trust" to 95-98% accuracy across tracking, attribution, reporting, and incrementality — built from 400+ account audits and $120M+ in managed spend.
Level up with these complementary products.
The average search account leaks 15-30% of spend on irrelevant clicks while targeting only 15-20% of its addressable market. The Six-Phase Campaign Architecture fixes both — built from 90+ search accounts and 160+ total accounts managed. One DTC brand used this exact system to scale from $21K to $336K/month at 3.8x true ROAS on non-brand search alone.
Shopping feeds, search ads, landing pages, demand gen creative, competitive intelligence, and unified reporting — all from a single terminal. Built from a production system running live campaigns every day. Three tiers, one decision: how much do you want already built?
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Every budget decision built on data nobody trusts. We audited a supplements brand spending $50K/month. Platform ROAS: 4.2x. After reconciling against Shopify: 2.6x. They'd been scaling on numbers 62% higher than reality for six months — $50,400 in misallocated spend — and were about to cut Google Ads because Meta "looked better" on the dashboard. Google was actually the more incremental channel.
The pattern across 400+ audits: 70% have structurally broken tracking. 72% run the wrong attribution model. Median misattribution: $4,200/month. Platform ROAS overstates true impact by ~33%. Fixing one layer without the others just moves the problem. This is why the system fixes all four — tracking, attribution, reporting, and incrementality — in sequence.
— Run the 78-point diagnostic across 5 layers. Rebuild your GTM container. Configure GA4 events and Google Ads conversions correctly. Layer server-side tracking to recover the 15-35% of data client-side misses.
— Fix the GA4 configuration errors that cause 70% of data problems. Cross-check all sources using the reconciliation template. Build a single source of truth where platforms agree within 3-5%. Set up conversion delay analysis so you stop killing profitable campaigns too early.
— Classify every metric into vanity, diagnostic, or decision tier. Channel-specific frameworks for Shopping, Search, PMax, Demand Gen. 30-minute weekly diagnostic plus monthly deep dive. 6 recovery playbooks for common crises.
— Geo-split tests with proper market matching. Brand search 7-day quick test (answers the $25K/month question). PMax 3-cell methodology. Calibrate your daily dashboard with incrementality factors that reflect reality.
One product. Two ways to implement. Choose the depth that matches your timeline.
Full curriculum and architecture — build the system yourself
What you get
Not included
Everything in Blueprint + downloadable agent codebase
What you get
Lifetime access. Free updates. Upgrade to a higher tier anytime — pay only the difference.
You invest
$997 once.
One Enhanced Conversions fix recovers an average of 8.3% of invisible conversions. One premature campaign kill costs $2,000-5,000 in wasted learning phase. One incrementality finding saves $2,000-16,500/month in non-incremental spend.
At $10K/month spend with ~$4,200 median misattribution: the system pays for itself in the first month.
Agencies charge $2,000-5,000 per engagement for tracking, attribution, reporting, or incrementality — each sold separately. This consolidates all four for $997 once. Break-even: $33.23/day. Module 1's diagnostic typically surfaces more than that in the first 2 hours.
Blueprint — 30-Day Fix Guarantee. Run the Module 1 diagnostic. When the 78-point check finds at least $997/month in trackable waste, misattributed spend, or invisible conversions — and in 400+ audits, it always has — you'll know it paid for itself. If it doesn't, email the completed diagnostic and I refund every cent.
You've seen what broken tracking costs. The only question is when you fix it — and whether you stop at fixing, or build an experimentation platform on top of clean data.
| Metric | Before (median) | After | Improvement |
|---|---|---|---|
| Orders matched | 74% | 97% | +31% |
| Conversion visibility gap | 26% invisible | 3% invisible | -88% |
| Duplicate conversion rate | 18% | 0% | eliminated |
| Cross-platform discrepancy | 22% | within 4% | -82% |
| Metric | Before (median) | After 60 days |
|---|---|---|
| Platform vs actual ROAS gap | 38% inflation | 5% |
| Monthly misattributed spend | $4,200 | $380 |
| Premature campaign kills / quarter | 4.1 | 0.6 |
| Metric | Before (median) | After 90 days |
|---|---|---|
| Time to detect performance issues | 11 days | 2.5 days |
| Weekly diagnostic time | 2.5 hrs (unfocused) | 30 min (structured) |
| Budget trapped in underperformers | 28% | 11% |
| Effective ROAS (after reallocation) | 2.4x | 3.2x |
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