Definition
A click ID is a unique identifier added to a landing page URL to link a click to an ad interaction (used for attribution and conversion uploads).
How to use it
- Capture it at landing, persist it (cookie/local storage), and attach it to conversions when allowed.
- Click IDs help with attribution, but incrementality still requires holdouts or experiments.
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 "Click ID" 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., UTM + GA4 attribution: practical tracking for paid ads (without lying to yourself)) for context and common pitfalls.
Where to use this on MetricKit
Calculators
- ROAS Calculator: Calculate Return on Ad Spend (ROAS) and estimate contribution profit after ad spend.
- Break-even ROAS Calculator: Estimate the break-even ROAS based on contribution margin assumptions.
- Target ROAS Calculator: Estimate a target ROAS to cover variable costs plus a desired margin buffer.
- Paid Ads Funnel Calculator: Model CPM -> CTR -> CVR to estimate CPC, CPA, ROAS, and profit per 1,000 impressions (with margin and variable costs).
- ROI Calculator: Calculate Return on Investment (ROI) for a campaign or project.
Guides
- UTM + GA4 attribution: practical tracking for paid ads (without lying to yourself): A practical guide to UTMs and GA4: consistent source/medium/campaign tagging, conversion deduplication, and common attribution traps.
- 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.