---
title: "What Is an Attribution Model? — SealMetrics Glossary"
description: "Attribution models determine how conversion credit is split across touchpoints. Compare first-touch, last-touch, linear, and data-driven models."
canonical_url: "https://sealmetrics.com/glossary/attribution-model/"
lang: "en"
content_type: "glossary"
owner: "content"
llm_priority: "useful"
last_verified: "2026-08-10"
source: https://sealmetrics.com/glossary/attribution-model/
publisher: SealMetrics
---

Definition

# Attribution Model

A set of rules that determines how conversion credit is distributed across the touchpoints in a customer journey. Common models include first-touch, last-touch, linear, time-decay, and data-driven attribution.

## Types of attribution models

Every conversion has a path — a sequence of interactions (ad clicks, organic searches, email opens, direct visits) that led to the final action. Attribution models define how to assign value across that path:

— **First-touch** assigns 100% of credit to the first interaction. Useful for measuring awareness channels, but ignores everything that happened after discovery. — **Last-touch** assigns 100% to the final interaction before conversion. GA4 defaults to this for most reports. It overstates bottom-funnel channels like branded search and retargeting. — **Linear** splits credit equally across all touchpoints. Simple and fair, but assumes every interaction has equal influence — which is rarely true. — **Time-decay** gives more credit to touchpoints closer to conversion. Reasonable for short sales cycles, less useful for B2B journeys spanning weeks or months. — **Data-driven** uses machine learning to calculate each touchpoint’s actual contribution based on conversion probability. Google removed all other models from GA4 in late 2023, making data-driven the default.

## Why attribution needs complete data

Every attribution model — from the simplest last-touch to the most sophisticated data-driven — depends on seeing the full journey. When [analytics data loss](https://sealmetrics.com/glossary/data-loss-in-analytics/) removes 40–87% of touchpoints, the model works on a fragment of reality.

Consider a customer who first discovers your brand through an organic search (blocked by an ad blocker), later clicks a display ad (tracked), and finally converts through a branded search (tracked). A last-touch model credits branded search. A data-driven model credits display. Neither knows the organic visit existed. The channel that actually introduced the customer gets zero credit — and zero budget in the next planning cycle.

[Multi-touch attribution](https://sealmetrics.com/glossary/multi-touch-attribution/) needs more than complete data — it needs a persistent identifier linking the same visitor’s touchpoints across sessions, which is exactly the cookie dependency that causes the data loss above. [Cookieless analytics](https://sealmetrics.com/glossary/cookieless-analytics/) closes a different gap: it captures every touchpoint within a session without that identifier, which is why models built on it — like [last-click](https://sealmetrics.com/glossary/last-click-attribution/) — run on 100% of sessions instead of a consent-biased subset.

## Attribution model comparison

| Model | Credit Distribution | Best For |
| --- | --- | --- |
| First-touch | 100% to first interaction | Awareness measurement |
| Last-touch | 100% to last interaction | Direct-response campaigns |
| Linear | Equal across all touchpoints | Long, multi-channel journeys |
| Time-decay | Weighted toward conversion | Short sales cycles |
| Data-driven | ML-calculated per touchpoint | High-volume, complete data |

Note: GA4 deprecated all models except data-driven and last-click in November 2023. Data-driven attribution requires sufficient conversion volume and — critically — complete data to produce reliable results.

SealMetrics runs one model — last-click on 100% of your traffic. See what a single, complete model tells you that blended data can't.

[Book a demo](https://sealmetrics.com/demo/)[See pricing](https://sealmetrics.com/pricing/)

### Related concepts

- [Multi-Touch Attribution An analytics model that distributes conversion credit across multiple touchpoints observed for the same identified visitor. Requires per-user tracking and is not part of SealMetrics' last-click, anonymous architecture.](https://sealmetrics.com/glossary/multi-touch-attribution/)
- [Revenue Attribution Connecting revenue events (purchases, subscriptions) to the marketing channels that drove them. SealMetrics uses last-click on 100% of observed events — no per-user journey tracking, no multi-touch models.](https://sealmetrics.com/glossary/revenue-attribution/)
- [Event Tracking The method of recording specific user interactions on a website beyond pageviews — clicks, form submissions, video plays, downloads, and eCommerce actions. GA4 uses an event-based data model where every interaction is an event.](https://sealmetrics.com/glossary/event-tracking/)
- [Data Loss in Analytics The gap between actual website traffic and what analytics tools report. Caused by consent rejection, ad blockers, browser restrictions, and data sampling. Typically 70-87% in the EU.](https://sealmetrics.com/glossary/data-loss-in-analytics/)

Learn more: [Multi-Touch Attribution with Complete Data](https://sealmetrics.com/blog/multi-touch-attribution-complete-data/) · [SealMetrics Product](https://sealmetrics.com/product/)