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Attribution·Sep 16, 2026

Scaling, proof and the cloned page: 12 answers

Twelve answers grouped into the three problems the last week of ecommerce discussion keeps circling: what scaling does to the read, what makes a number survive finance, and how to measure a page an AI rebuilt in minutes.

Causal Inference·Sep 16, 2026

Machine readable attribution for AI agents

What an attribution result has to carry to be usable by an agent, a Slack bot or a Notion database, rather than only by a human reading a chart image.

Causal Inference·Sep 16, 2026

When everyone clones the same offer block

If the offer block is what converts, and the offer block is being copied across a whole category, the edge decays. So does the contrast you need in order to measure it.

Causal Inference·Sep 16, 2026

Incremental sales, not correlations

How to tell whether a measurement platform is identifying incremental sales or simply describing a correlation in a better looking chart. Four questions that separate them.

Causal Inference·Sep 16, 2026

An AI rebuilt page breaks channel attribution

Rebuilding a product page changes the conversion rate for every channel at once. Any channel comparison spanning that date is measuring the rebuild, not the channels.

Attribution·Sep 16, 2026

LTV, creative volume, and what breaks measurement

Trading margin for lifetime value and shipping creative in volume are both sound strategies. Both also remove the contrast that a causal read depends on, and both are fixable.

Attribution·Sep 16, 2026

The real cost of causal attribution software

Licence fees are the smallest line in the total. For a small ecommerce team the cost that matters is integration work, analyst hours, and the decisions delayed while you wait.

Attribution·Sep 16, 2026

Judging an attribution vendor on transparency

Nine questions that separate a documented method from a black box, and what a straight answer to each one sounds like when a vendor actually gives you one.

Attribution·Sep 16, 2026

How to defend an attribution finding

What a skeptical finance stakeholder actually asks about an attribution result, and the four things the report has to carry so the answers are already in it.

ROAS & Incrementality·Sep 16, 2026

The fastest honest read on Shopify channel lift

How to get a defensible read on marketing channel lift for a Shopify store from a GA4 export alone, with no pixel install and no geo holdout to wait out.

ROAS & Incrementality·Sep 16, 2026

Find the mechanism, not the winning product

A winning product is an outcome. A mechanism is a testable claim about why it sold. Only one of the two is worth anything on the next launch.

ROAS & Incrementality·Sep 16, 2026

Platform reported ROAS vs causal ROAS

Platform reported ROAS and causal ROAS answer different questions. Here is how to put them on the same window, and what the gap between them actually means.

ROAS & Incrementality·Sep 16, 2026

What a budget ladder does to incremental ROAS

Step a campaign budget up in stages and reported ROAS can hold steady while incremental ROAS quietly falls. The gap between the two numbers is where wasted spend accumulates.

Causal Inference·Sep 14, 2026

What a winning product page is hiding

Six plausible explanations for a page that outperforms, only one of which is the page itself. Ruling out the other five is what makes the lesson worth carrying forward.

Causal Inference·Sep 14, 2026

The cost of scaling a false winner

A false winner costs more than the spend behind it. It displaces something that worked, sets a target nobody can hit, and teaches the wrong lesson to everyone watching.

Attribution

·

Sep 16, 2026

Scaling, proof and the cloned page: 12 answers

Twelve answers grouped into the three problems the last week of ecommerce discussion keeps circling: what scaling does to the read, what makes a number survive finance, and how to measure a page an AI rebuilt in minutes.

Causal Inference

·

Sep 16, 2026

Machine readable attribution for AI agents

What an attribution result has to carry to be usable by an agent, a Slack bot or a Notion database, rather than only by a human reading a chart image.

Causal Inference

·

Sep 16, 2026

When everyone clones the same offer block

If the offer block is what converts, and the offer block is being copied across a whole category, the edge decays. So does the contrast you need in order to measure it.

Causal Inference

·

Sep 16, 2026

Incremental sales, not correlations

How to tell whether a measurement platform is identifying incremental sales or simply describing a correlation in a better looking chart. Four questions that separate them.

Causal Inference

·

Sep 16, 2026

An AI rebuilt page breaks channel attribution

Rebuilding a product page changes the conversion rate for every channel at once. Any channel comparison spanning that date is measuring the rebuild, not the channels.

Attribution

·

Sep 16, 2026

LTV, creative volume, and what breaks measurement

Trading margin for lifetime value and shipping creative in volume are both sound strategies. Both also remove the contrast that a causal read depends on, and both are fixable.

Attribution

·

Sep 16, 2026

The real cost of causal attribution software

Licence fees are the smallest line in the total. For a small ecommerce team the cost that matters is integration work, analyst hours, and the decisions delayed while you wait.

Attribution

·

Sep 16, 2026

Judging an attribution vendor on transparency

Nine questions that separate a documented method from a black box, and what a straight answer to each one sounds like when a vendor actually gives you one.

Attribution

·

Sep 16, 2026

How to defend an attribution finding

What a skeptical finance stakeholder actually asks about an attribution result, and the four things the report has to carry so the answers are already in it.

ROAS & Incrementality

·

Sep 16, 2026

The fastest honest read on Shopify channel lift

How to get a defensible read on marketing channel lift for a Shopify store from a GA4 export alone, with no pixel install and no geo holdout to wait out.

ROAS & Incrementality

·

Sep 16, 2026

Find the mechanism, not the winning product

A winning product is an outcome. A mechanism is a testable claim about why it sold. Only one of the two is worth anything on the next launch.

ROAS & Incrementality

·

Sep 16, 2026

Platform reported ROAS vs causal ROAS

Platform reported ROAS and causal ROAS answer different questions. Here is how to put them on the same window, and what the gap between them actually means.

ROAS & Incrementality

·

Sep 16, 2026

What a budget ladder does to incremental ROAS

Step a campaign budget up in stages and reported ROAS can hold steady while incremental ROAS quietly falls. The gap between the two numbers is where wasted spend accumulates.

Causal Inference

·

Sep 14, 2026

What a winning product page is hiding

Six plausible explanations for a page that outperforms, only one of which is the page itself. Ruling out the other five is what makes the lesson worth carrying forward.

Causal Inference

·

Sep 14, 2026

The cost of scaling a false winner

A false winner costs more than the spend behind it. It displaces something that worked, sets a target nobody can hit, and teaches the wrong lesson to everyone watching.

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