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See which growth deserves to count. Control what comes next.

RealBuyerGrowth is a real-buyer growth evidence service for Shopify-first ecommerce teams. It helps teams separate reported campaign activity from growth that deserves to count, then decide what to control before the next campaign.

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What the evidence review shows you

The Real Buyer Growth Evidence Review takes the numbers your campaign dashboard already reports and asks a harder commercial question: how much of this actually held up?

Reported vs Verified

Your dashboard may show new customers, redemptions, or reward claims. The evidence review shows how many still hold up when checked against device signals, contact consistency, timing patterns, and linked-participation logic. The gap between reported and verified is where budget waste hides.

Waste Exposure

Where discount codes, rewards, or incentives went to participation that did not cleanly meet the campaign claim — broken down by type: first-order leakage, repeated code use, refund-after-offer, and suspicious redemption.

Reason Factors

Each factor is a named, readable rule — not a black-box score. It explains why confidence dropped: repeated device use, linked contact details, unusual checkout speed, tight claim clustering. You can read the explanation and decide whether it matters for your business.

Next-Campaign Recommendation

What to tighten before the next campaign, with estimated recovery potential. The goal is not to rebuild the promo stack — it is to fix the part of the journey where trust weakened most.

How the product is delivered

RealBuyerGrowth is intentionally structured in stages. Most teams do not need heavier intervention on day one. They need commercial clarity first, then continuity, then tighter controls only where the evidence justifies them. The standard evidence review covers your owned campaign pages — landing pages, referral pages, reward-claim pages, and checkout pages. It does not include direct observation of off-site ad-platform behaviour before visitors land on your site.

Real Buyer Growth Evidence Review

A one-off commercial evidence review for a specific campaign, promotion period, or incentive flow. It compares reported campaign activity with what still holds up under device, timing, contact, and linked-participation review.

Reported vs verified view
Waste exposure by pattern type
Named reason factors, not black-box scoring
Next-campaign recommendation
Estimated recovery opportunity range
Commercial review walkthrough

Continuity Monitoring

For teams that want to observe the next campaign or the next cycle in motion. This is not a heavy enforcement layer first. It is a continuity view: where suspicious patterns recur, where trust weakens again, and whether the changes made after the evidence review are actually holding.

Cross-campaign pattern continuity
Repeated device and contact linkage monitoring
Claim clustering and timing drift
Leakage pattern recurrence tracking
Review snapshots across the live cycle
Recommendation updates as evidence accumulates

Later, if the evidence justifies it

Only after the signal is understood should tighter intervention be designed. That may include stricter eligibility logic, better code controls, referral-chain tightening, or review thresholds — but that comes after evidence, not before it.

Where we see this in practice

The same commercial patterns appear across promotion-heavy e-commerce campaigns. The evidence review is built to surface these specifically:

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New-customer recycling

The same buyer reappearing as "new" across campaigns or accounts.

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Referral farming

Manufactured referral chains that meet the letter of the programme but not the intent.

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Entitlement leakage

Rewards, credits, or incentives reaching participation that did not cleanly qualify.

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Code stacking abuse

Discount codes combined in ways the campaign did not intend to allow.

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Promo-code leakage

Codes shared, scraped, or guessed beyond the intended audience.

These are not rare edge cases. In the verticals we are targeting first, they are the primary sources of budget waste and dirty campaign data.

A commercial evidence review first. A protection layer second.

The evidence review shows where confidence dropped, where campaign ROI was likely over-trusted, and what should be tightened before the next campaign. That means the first job is clarity: cleaner campaign judgment, cleaner data for the next campaign, cleaner reward and incentive allocation, more proportionate protection decisions.

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The first evidence review: Diagnose and observe

Instrument the next campaign. See what the live data shows. Build confidence in the signal.

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Later: Protect with confidence

Add stronger intervention only when there is enough operational evidence to act without guessing.

What this is not

RealBuyerGrowth is a narrower, calmer tool than a generic bot platform or a full attribution system.

Not a bot-blocking tool

We diagnose promotion-integrity risk, not network-layer bot traffic.

Not an attribution platform

We do not assign credit across channels; we assess claim quality.

Not a black-box score

Every finding has a named, readable reason factor.

Not a heavy integration project

The first evidence review uses a lightweight observation tag, not an app install.

Questions buyers usually ask

RealBuyerGrowth is designed to be commercially useful before it becomes operationally heavy. These are the questions we are most often asked first.

Do we need a full replatform or app install to start?

No. The first evidence review is designed to begin with lightweight observation, not a heavy replatforming project.

Is this replacing our analytics stack?

No. RealBuyerGrowth does not replace your analytics or attribution tools. It adds a narrower commercial evidence layer around claim quality, leakage, and promotion integrity.

What do we actually receive from the evidence review?

You receive a commercial review of reported versus verified participation, waste exposure, named reason factors, and a next-campaign recommendation with estimated recovery potential.

Do you block users automatically in the first evidence review?

No. The first evidence review is about diagnosis and observation. Stronger intervention should only follow once the operational evidence is clear enough to support it.

What happens after the first evidence review?

If the signal is commercially useful, the next step is continuity monitoring: observing whether the same patterns recur and whether the changes made before the next campaign are actually holding.

The framework underneath

RealBuyerGrowth is built on AMS

The evidence review method you see here is one expression of a broader decision architecture: the Attention Monetary System. AMS governs the five questions any system must answer before releasing value — intent, trust, policy, time, risk — in a readable, rules-first way. If you want the theory, both papers are below.

★ Whitepaper · 18 min

AMS Whitepaper

Shared Trust & Allocation Infrastructure for Scarce Digital Attention. The five-layer decision spine — Intent, Trust, Policy, Time, Risk — that governs qualification before release.

Read online Download PDF

★ Companion paper

AMS Field Theory

The Benevolent Holding Field — the operating condition under which the five-layer logic produces cooperation rather than corroding into gaming. Trust substrate and container architecture for governed allocation.

Read online Download PDF

See what your campaign numbers are really saying

Start with an evidence review on your next campaign. Move into continuity only when the evidence validates that we should take the next step.

Get my growth evidence review

Applications are reviewed before payment. We reply within 24 hours.

See the specimen evidence review