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Term · Marketing & analytics

Attribution model

An attribution model is a rule for assigning credit for a conversion — an enquiry or a sale — to the marketing touchpoints that preceded it. A customer might see an Instagram ad, later search on Google, then return directly and buy. Which channel "caused" the sale depends on the model.

Updated · 2 min read · DealPro

[ 01 ]

Explained

Common models

  • Last click: all credit to the final touchpoint before conversion. Simple; undervalues channels that create demand.
  • First click: all credit to the first touchpoint. Highlights discovery; ignores what closed the sale.
  • Linear: equal credit to every touchpoint.
  • Time decay: more credit to touchpoints closer to conversion.
  • Position-based: most credit to first and last touchpoints, the rest shared.
  • Data-driven: algorithmic credit based on observed paths — the default in GA4 and Google Ads, where data volume allows.

Why it matters

The model changes reported ROAS and cost per acquisition by channel, and therefore budget decisions. Last-click models tend to favour search and remarketing; awareness channels such as social video appear weaker than they are.

Limitations

  • Only tracked touchpoints count — offline conversations, word of mouth and untracked messenger contacts are invisible.
  • Cross-device journeys and privacy restrictions reduce visibility.
  • Platforms each claim credit using their own view, so totals across platforms exceed actual sales.

Using attribution wisely

  • Choose a primary model and report consistently.
  • Compare models to understand each channel's role.
  • Use incrementality tests (holdouts, geo tests) for big budget decisions.
  • Reconcile with actual sales in the CRM. See end-to-end analytics.

[ 02 ]

FAQ

Frequently asked questions

Which model is best?

None is perfect. Data-driven models are a sensible default where available; supplement with tests and business judgement.

Why do Google and Meta both claim the same sale?

Each platform attributes conversions using its own data and rules. Use an independent source — analytics or CRM — as the reference.

Related reading

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