An attribution window (also called a lookback window) is the period after a candidate interacts with a job ad during which an application or hire can be credited to that ad or channel. A click-through window starts when someone clicks; a view-through window starts when someone sees an ad without clicking. Choose the shortest window that still matches how long your candidates actually take to decide, and revisit it by role type.
What Is an Attribution Window?
An attribution window defines how far back in time a touchpoint is eligible for credit. Google puts it this way for Analytics: the lookback window “determines how far back in time a touchpoint is eligible for attribution credit”.
In recruitment advertising, the conversion might be an apply start, a completed application, an interview, or a hire. If a candidate clicks a job ad on Monday and applies on Thursday, a seven-day window credits the ad. If the same candidate applies 40 days later, the ad gets nothing, even if it started the journey.
The window is a measurement rule, not a media setting. It changes which channel gets credit in reports. It does not change who actually saw or clicked your ads.
What Is the Difference Between Click-Through and View-Through Windows?
A click-through window counts conversions that follow a click on your ad. It is the stronger signal, because the candidate took a deliberate action.
A view-through window counts conversions that follow an impression with no click. It can reveal the influence of awareness formats, but it also risks crediting an ad the candidate never noticed.
Platforms treat these windows differently. Meta, for example, states that as of January 12, 2026, its 7-day view and 28-day view windows are no longer returned in the Ads Insights API, while 1-day click, 7-day click, 28-day click, 1-day engaged view and 1-day view remain available. Google Analytics 4 lets you configure lookback windows per event type, as covered below.
| Window type | Starts with | Signal strength | Main risk |
|---|---|---|---|
| Click-through | A click on the ad | Higher | Undercounts ads that influence without clicks |
| View-through | An impression only | Lower | Over-credits ads that were never noticed |
Why Are Candidate Journeys Different From Consumer Journeys?
Reason about this qualitatively, and test it against your own data rather than assuming a number.
Why journeys can run longer: a job change is a high-stakes, infrequent decision. Candidates compare employers, talk to family, update a resume, and wait for the right opening. Passive candidates may return to a job post several times across devices before applying.
Why journeys can run shorter: for hourly and high-volume roles, many candidates are actively looking, need income soon, and apply the same day they see a posting. Mobile-first, low-friction apply flows compress the timeline further.
Because both patterns exist, a single default window rarely fits every role in the same account.
How Do Attribution Windows Work With Last-Click, Multi-Touch, and Incrementality?
The window decides which touchpoints are eligible. The attribution model decides how credit is split among them. Google notes that its lookback window applies to all attribution models.
- Last-click: the final eligible touchpoint gets all credit. A short window concentrates credit on bottom-funnel channels.
- Multi-touch: credit is shared across eligible touchpoints. A longer window brings more upper-funnel touches into the split.
- Incrementality: a controlled test asks whether the conversion would have happened anyway. Windows still matter, because the test needs a defined measurement period.
For a deeper look at how these approaches fit together, see Joveo’s guide to recruitment marketing attribution and the explainer on incrementality vs attribution in job advertising. If retargeting is part of your mix, remember that it often interacts with view-through credit; see what retargeting is in recruitment advertising.
How Do You Choose an Attribution Window by Role Type?
The table below is a rule of thumb for illustration, not benchmark data. Start here, then adjust using your own time-to-apply reports.
| Role type | Starting click window | Starting view window | Reasoning |
|---|---|---|---|
| Hourly or high-volume | Short (for example 1 to 7 days) | Very short or none | Fast decisions; a long window mostly adds noise |
| Skilled or professional | Medium (for example 7 to 30 days) | Short | More research and comparison before applying |
| Executive or niche | Longer (for example 30 days or more) | Usually none | Slow, considered process with multiple touches |
A practical method: pull the time between first ad click and apply for recent hires by role family. Set the window to cover most of that distribution, then compare results with a shorter and a longer setting before committing.
What Do Major Platforms Use as Default Windows?
Defaults are a starting point, not a recommendation for your hiring.
Google Analytics 4. The default lookback window is 30 days for acquisition key events (first_open and first_visit), with 7 days as the alternative. For all other key events the default is 90 days, with 30 or 60 days also available. In the advertising conversion settings tied to Google Analytics, click-through windows can be set to any integer from 1 to 90 days.
Meta. Click windows of 1, 7 and 28 days remain available, along with 1-day view and 1-day engaged view, after the January 12, 2026 change. Which windows your account reports depends on your attribution setting.
Because each platform counts on its own rules, the same apply can show up in several reports.
What Are the Most Common Attribution Window Pitfalls?
Window too short. Channels that start the journey (video, social, display) get undercounted because the apply lands after the window closes.
Window too long. Credit drifts to ads the candidate barely remembers, and results look better than they are.
Double counting across platforms. Each platform credits itself for conversions inside its own window. Summing platform-reported applies usually overstates the total. Reconcile against a single source of truth, such as your ATS.
Cookie and pixel limits. Windows only work if the click or view can be tied to the later apply. Browser privacy controls, consent choices and cross-device behavior can break that link, so a longer window does not guarantee longer visibility.
Mixing windows in one comparison. Comparing a channel measured at 30 days with one at 1 day is not a fair test. Standardize windows before ranking channels.
Platforms such as Joveo, which manages programmatic job advertising across many publishers, can help by applying consistent conversion tracking across sources, so comparisons are like for like.
Worked Example: Same Candidate, Three Windows (Hypothetical)
All numbers below are hypothetical and for illustration only. A candidate sees a display ad on Day 0 (no click), clicks a sponsored job ad on Day 6, and applies on Day 9 after a job board search.
| Window setting | Display view credited? | Sponsored click credited? | Result under last-click |
|---|---|---|---|
| 1-day view, 7-day click | No (Day 9 is outside 1 day) | Yes (Day 6 is within 7 days) | Sponsored ad |
| 1-day view, 2-day click | No | No | Job board search |
| 14-day view, 14-day click | Yes | Yes | Job board search (last-click) or shared (multi-touch) |
The same apply is credited to three different outcomes. That is why you should document your window, and keep it the same when comparing periods.
Frequently Asked Questions
What is a lookback window?
A lookback window is another name for an attribution window. It is how far back from a conversion a system looks for ad interactions that can receive credit.
What is the default attribution window in Google Analytics 4?
For acquisition key events the default is 30 days (7 days is the alternative). For all other key events the default is 90 days, with 30 and 60 also available.
Should I use a view-through window for job ads?
Use it cautiously. View-through can show awareness effects, but it is a weaker signal than a click. Keep it short, report it separately from click conversions, and validate it with an incrementality test.
Does a longer attribution window make my results better?
No. It makes more conversions eligible for credit, which can inflate results. The right window matches how long candidates actually take from first touch to apply.
Why do my platform reports add up to more applies than my ATS?
Each platform credits conversions inside its own window and model, so one apply can be counted more than once. Treat your ATS as the source of truth and use platform numbers for relative comparison.
