Definition
Linear attribution spreads conversion credit evenly across all recorded touchpoints in a conversion path.
Example
If a user has four touches, each gets 25% of the credit under linear attribution.
How to use it
- Helpful for multi-touch narratives, but it can over-credit low-impact touches.
- Use it for directional insights; validate decisions with tests.
- Keep the same lookback window when comparing periods.
Common mistakes
- Comparing linear to last-click without acknowledging different intents.
- Assuming linear credit is causal for every touchpoint.
Why this matters
This term matters because it affects how you interpret performance and make budget decisions. If you use inconsistent definitions or windows, ROAS/CPA can look "better" while profit gets worse.
Practical checklist
- Write a 1-line definition for "Linear Attribution" that your team will use consistently.
- Keep the time window consistent (weekly/monthly/quarterly) when comparing trends.
- Segment results (channel/plan/cohort) before drawing big conclusions from blended averages.
- Sanity-check with a related calculator from the same category on MetricKit.
- Read the related guide (e.g., Attribution vs incrementality: what to trust, when, and how to test) for context and common pitfalls.
Where to use this on MetricKit
Calculators
- Target CPA from LTV Calculator: Translate LTV and contribution margin into a target CPA (and break-even CPA) for paid acquisition.
- MER Calculator: Calculate MER (Marketing Efficiency Ratio / blended ROAS) and estimate break-even and target MER from margin assumptions.
- Max CPC Calculator: Compute break-even and target CPC (and optional CPM) from CVR, AOV, and contribution margin assumptions.
- Break-even CPM Calculator: Compute break-even and target CPM from CTR, CVR, AOV, and contribution margin assumptions.
- Break-even CTR Calculator: Compute the CTR required to break even (and hit a target) given CPM, CVR, AOV, and contribution margin.
Guides
- Attribution vs incrementality: what to trust, when, and how to test: A practical guide to attribution vs incrementality: common attribution models, window pitfalls, how MER/marginal ROAS fit in, and how to run holdout/geo tests.