Feature · Cross-source Revenue Attribution

Cross-Source Revenue Attribution and Profitability

Cross-source Revenue Attribution combines connected ad delivery, organic search and the ecommerce order book without pretending they are one measurement system. It names what is measured, what is estimated, what is missing and what is only an association.

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Four cross-source views
Channel P&L Measured delivery beside stated attribution estimates
Blended acquisition Paid spend, new customers, revenue, CAC, ROAS
Paid–organic lift Lagged association only
Hourly alignment Spend share against realized order share
Platform tracking, estimated attribution and shop-realized commerce remain separate fields.
One row per channel
Measured Spend, clicks, impressions, CTR, position
Platform claim Tracked conversions
Estimated Orders, revenue, CM2, CM3 after spend
Trust Method, confidence, unavailable reasons
Organic has no paid spend, so its ROAS is undefined rather than zero.
Channel P&L

Channel Metrics With Attribution Provenance

Each channel row reports connection state and measured delivery first. Where attribution is available, estimated orders and revenue carry their method and confidence beside them; CM2 contribution is withheld when shop cost inputs cannot support it, and CM3 after channel spend remains an estimate rather than a realized channel ledger.

  • Delivery is not attribution — impressions, clicks, spend and platform-tracked conversions stay distinct from estimated shop outcomes.
  • Contribution has a readiness gate — missing or incomplete product and order costs produce an explicit reason instead of a revenue fallback.
  • CPO and ROAS keep their denominator rules — no denominator means unavailable, not a clean zero.
  • Useful for paid media and domain owners — compare what platforms delivered with the commercial estimate the shared model can support.
Blended acquisition

Blended CAC and ROAS Coverage

The acquisition block combines observed spend from the included paid platforms with shop-identified new customers and realized revenue across the selected window. It lists missing and unobserved platforms and marks partial coverage, because an apparently precise blended CAC is unsafe when a material channel is absent.

  • All-channel denominator — new customers come from the shop, not from an ad-platform attribution claim.
  • Partial means partial — connected, missing and unobserved platforms are separate states.
  • Meta relationship — Meta New-customer CAC narrows the numerator to filtered Meta spend but keeps the same non-causal customer boundary.
  • No individual credit assignment — this block cannot say which channel caused a particular first purchase.
Combined paid coverage
Included paid platforms
Spend
Shop-identified
New customers
Spend ÷ new customers
CAC
Realized shop revenue ÷ spend
ROAS
Included, missing and connected-but-unobserved platforms are listed before the blended result is read.
Lagged association
Ad spend Compared across candidate lags
Branded clicks Observed organic series
Non-branded clicks Observed organic series
Correlation is association only. Promotions, seasonality, ranking changes and other channels remain confounders.
Paid and organic, over time

The paid–organic lift view aligns ad spend with branded and non-branded Google Search Console clicks across several lags. It requires a minimum number of days before offering a strongest observed coefficient, lists the paired-day count for every lag, and carries an explicit association-only flag and confounders.

SEO owners can see whether branded search demand follows periods of paid pressure; paid-media owners can avoid treating that pattern as proven incrementality. A controlled holdout, geo test or other experiment is still needed to establish causal lift.

Hourly spend versus demand

Hourly Spend and Order Alignment

For each clock hour, the report places observed ad spend beside realized shop orders and revenue, then compares each hour’s share of spend with its share of orders. Missing ad observation stays missing. The largest absolute gaps are highlighted as scheduling questions, not proof that an ad shown in that hour produced an order there.

Share gap, balanced at zero
Spend share ahead Possible overscheduled hour
Balanced Shares align
Order share ahead Possible underscheduled hour
The gap is spend share minus realized order share. Exposure time and purchase time can differ.
4

cross-source views, each with its own evidence boundary

Channel estimates, blended acquisition, paid–organic association and hourly alignment are never collapsed into one magic attribution score.

Audit Meta Attribution Reality

Reconcile Channel and Shop Performance

See measured inputs, stated attribution estimates, coverage gaps and causal limits in one cross-source report.

app.amicited.com/reports/cross-source

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