Campaign measurement

Attribution window and conversion lag checklist

Published May 31, 2026. Status: evergreen source page.

Attribution windows look like reporting settings, but they decide which outcomes receive credit and which outcomes disappear from the story.

Use this checklist when a campaign report credits leads, sales, store visits, signups, pipeline, renewals, or revenue to media exposure. The goal is to separate timing rules, reporting coverage, and observed credited outcomes from stronger claims about incremental impact.

Start with the credited outcome

Before debating whether a window is too short or too long, identify the action that received credit and the touchpoint allowed to claim it.

Credited result	What it can show	What it cannot prove alone
Click-through conversion	A tracked conversion happened after a click inside the selected window.	That the click caused the conversion or that unclicked impressions had no effect.
View-through conversion	A tracked conversion happened after a recorded exposure without a required click.	That the exposure changed behavior rather than reaching a user already likely to convert.
Engaged visit or lead	A session or form action met the report's engagement and source rules.	That the person was new demand, qualified, reachable by sales, or incremental.
Offline or CRM outcome	A tracked identity, account, or household later matched to an offline event.	That the match captured the whole eligible universe or removed prior intent.
Assisted conversion	A touchpoint appeared somewhere in a tracked path before the reported outcome.	That the assist deserves causal credit or budget weight equal to the last touch.
Modeled conversion	The reporting system estimated unobserved outcomes under its model and coverage assumptions.	That the estimate is equivalent to directly observed incremental lift.

Name every clock

Most attribution disputes are really clock disputes. A usable report should show each window separately instead of compressing them into one "campaign period."

Exposure window

The dates and times when the campaign could serve impressions, clicks, sponsorship placements, video views, emails, or other eligible touches.

Lookback window

The period before the conversion during which a touchpoint is allowed to claim credit. Show separate windows for impressions, clicks, visits, and matched identifiers when they differ.

Conversion window

The period after a touchpoint during which an outcome is eligible for credit. The window should match the buying cycle, not only the easiest reporting setting.

Data-lag allowance

The delay between the real-world outcome and the moment it appears in the reporting system. Late CRM updates, returns, approvals, and offline files can change the result after the first readout.

Pre-period

The period used to detect prior intent, existing customers, earlier visits, open opportunities, sales outreach, loyalty behavior, or category purchase history before media exposure.

Reporting cutoff

The date when the report was pulled, which cohorts were mature enough to judge, and which recent cohorts are still incomplete because their conversion lag has not run out.

Conversion lag audit

A short window can undercount slower decisions. A long window can absorb demand that would have happened anyway. The right question is not whether the window is generous, but whether the window matches the decision and the evidence level.

Risk	QA question	Why it matters
Immature cohorts	Are recent exposures separated from older exposures whose conversion window has fully matured?	Fresh cohorts often look weak simply because their lag has not elapsed.
Window shopping	Were 1-day, 7-day, 14-day, 30-day, and longer windows inspected after results were visible?	Flexible windows can turn ordinary timing into a stronger story.
Sale-cycle mismatch	Does the window match the normal time from first touch to qualified lead, purchase, renewal, or pipeline stage?	Complex decisions need different lag treatment than impulse actions.
Prior intent	Were users with recent visits, searches, cart activity, open opportunities, or sales contact identified before credit was assigned?	Attribution can reward the touchpoint closest to demand already in motion.
Channel blind spots	Which touches, devices, offline interactions, privacy-constrained paths, or untagged placements are missing from the path?	The visible path can over-credit the channels that are easiest to observe.
Outcome revisions	Are cancellations, returns, duplicate leads, rejected applications, unqualified leads, and late-stage CRM changes applied after the initial conversion?	A fast count can be directionally useful while still overstating durable value.
Concurrent activity	Did promotions, sales outreach, pricing changes, email, search, affiliates, or other media run during the same lag window?	Attribution windows can collect outcomes created by other work.

Window QA checklist

Question	Good evidence	Do not accept
What was the primary window before launch?	A preselected click, view, matchback, and outcome window tied to the campaign objective.	A summary that changes windows after the strongest result is known.
How does performance change by lag day?	A lag curve or cohort table showing conversions by day since exposure or click.	Only the final credited total with no timing distribution.
Which cohorts are complete?	Separate mature and immature cohorts, with the reporting cutoff visible.	Ranking recent placements or creatives before their lag window has matured.
What happens under a shorter window?	A sensitivity table that shows how credited outcomes change under tighter windows.	One long window presented as the natural truth.
What happens under a longer window?	A sensitivity table that shows whether late conversions concentrate among high-prior-intent users.	Late outcomes credited without checking prior demand or concurrent touches.
What denominator is used?	Eligible exposed users, clicked users, matched users, sessions, leads, accounts, or households shown separately.	Rates calculated from whichever denominator makes the result look strongest.
What comparison protects causal language?	A holdout, matched control, geo baseline, model baseline, or explicit statement that no causal comparison exists.	Credited conversions described as incremental conversions.

Readout language ladder

Attribution-window work can make reporting cleaner, but clean credit rules are not the same as a counterfactual.

Evidence available	Careful wording	Overclaim to avoid
Credited outcomes only	The campaign received credit for observed outcomes inside the stated window.	The campaign created those outcomes.
Lag curve with no baseline	Observed credited outcomes matured over this timing pattern.	The lag curve proves the channel's incremental contribution.
Window sensitivity	The result is sensitive, or not sensitive, to the selected credit window.	The best-looking window is the correct window.
Prior-intent controls	The report reduces some selection risk by separating users already close to action.	Prior-intent controls remove all selection bias.
Designed holdout or geo test	The campaign supports measured lift for the eligible population, window, outcome, and uncertainty range.	The same attribution window should be treated as causal proof in every future campaign.

Questions for the vendor call

Which attribution window was selected before launch, and who approved it?
How do credited outcomes change at 1, 7, 14, 30, and 60 days?
Which cohorts are fully mature, and which are still incomplete because of conversion lag?
What share of credited outcomes came from users, accounts, or households with visible prior intent?
Which channels or touchpoints were invisible to this attribution system?
How are duplicate leads, returns, cancellations, rejected applications, and late CRM updates handled?
What comparison shows whether credited outcomes were incremental rather than only timed after exposure?

Pair with

Use this checklist with the campaign readout QA checklist for finished reports, the campaign reporting terms glossary for shared language, the campaign data-layer spec before launch, the identity matchback checklist when outcomes rely on joined records, the campaign status-window closeout checklist when conversion lag or credited outcome windows are not yet mature, the audience selection bias checklist when high-intent users may be easier to credit, and the incrementality test plan template when the decision needs causal evidence.