Key Takeaways
- Meta's default is 7-day click, 1-day view (restricted from pre-iOS 14 28-day windows)
- Google allows 1-90 day attribution windows with various models
- Meta is removing 7-day and 28-day view-through windows in January 2026
- Incremental Attribution from Meta shows 20%+ boost in incremental conversions
- Window misalignment guarantees reporting disagreement between platforms
Starting January 12, 2026, Meta will remove 7-day and 28-day view-through attribution windows. Plan your measurement strategy accordingly.
Understanding Attribution Windows
Attribution windows define how long after an ad interaction a conversion can be credited to that ad. Get this wrong, and you'll make decisions based on inaccurate data.
The Basic Concept
User sees ad → [Window opens] → User converts → [Credit assigned?]
↑ ↑
Impression/Click Only if within window
Window Types
| Click-through | Conversion after clicking | Direct response |
| View-through | Conversion after seeing (no click) | Awareness, brand |
| Engaged-view | Video watch of 10+ seconds | Video campaigns |
Available Options (2026)
| Window | Description | Use Case |
| 1-day click | 24 hours after click | Impulse purchases |
| 7-day click | 7 days after click | Most e-commerce |
| 1-day view | 24 hours after impression | Brand influence |
| 7-day click + 1-day view | Default setting | Balanced approach |
The iOS 14 Impact
> "Before Apple's iOS 14.5 update, Meta offered advertisers detailed attribution insights, with windows extending up to 28 days post-click and 7 days post-view."
What Changed:
- 28-day click window removed
- 7-day view window being removed (Jan 2026)
- More limited data granularity
- Modeled conversions for iOS users
Incremental Attribution (2025)
> "In April 2025, Meta rolled out Incremental Attribution, an AI-powered technique that uses holdout testing to separate conversions driven by ads from those that occur naturally."
Benefits:
- 20%+ boost in incremental conversions identified
- True incrementality measurement
- AI-powered holdout testing
- Better budget allocation insights
| Scenario | Recommended Window |
| Impulse products (<$50) | 1-day click |
| Standard e-commerce | 7-day click |
| High-consideration ($500+) | 7-day click |
| Brand awareness | 7-day click + 1-day view |
| Flash sales | 1-day click |
The 7-day click + 1-day view default is appropriate for most advertisers. Change it only if you have a specific reason.
Google Ads Attribution
Window Options
| Platform | Min Window | Max Window | Default |
| Google Ads (Search) | 1 day | 90 days | 30 days |
| Google Ads (Display) | 1 day | 90 days | 30 days |
| Google Ads (Video) | 1 day | 90 days | 30 days |
| GA4 | 1 day | 90 days | 30 days |
Attribution Models in Google
| Data-Driven | ML-based credit distribution | Most advertisers |
| Last Click | 100% to final click | Direct response |
| First Click | 100% to first click | Awareness campaigns |
| Linear | Equal credit to all | Understanding full path |
| Time Decay | More credit to recent | Shorter cycles |
| Position-Based | 40/20/40 first/middle/last | Balanced view |
Google's Time Decay
> "Google differs from Meta in that credit is distributed through a 7-day half life. An ad interaction 8 days before the conversion event gets half as much credit as an interaction 1 day before."
Key Differences
| Max click window | 7 days | 90 days |
| View-through | 1 day (soon limited) | Varies by campaign |
| Default model | Last touch | Data-driven |
| Cross-device | Limited post-iOS 14 | Better with login data |
| Granularity | Restricted | More detailed |
Why Numbers Never Match
> "Window misalignment guarantees numerical disagreement."
Causes of Discrepancy:
Different attribution windows
Different attribution models
Different conversion definitions
Cross-device tracking differences
View-through methodology
Time zone differences
Conversion delay handling
Comparing Apples to Apples
To minimize discrepancy:
- Align windows where possible
- Use same conversion events
- Understand each platform's methodology
- Don't expect 100% match
- Use incrementality testing for truth
Setting Up Attribution
Location: Ads Manager → Ad Set Level → Attribution Setting
| Click window | 1-day or 7-day |
| View window | 1-day or none |
| Combination | Click-only or Click + View |
Google Ads Attribution Settings
Location: Tools & Settings → Measurement → Attribution
| Model | Data-driven, Last click, etc. |
| Window | 1-90 days |
| Conversions | Include in conversions toggle |
GA4 Attribution Settings
Location: Admin → Attribution Settings
| Reporting model | Data-driven or rules-based |
| Lookback window | Acquisition: 30 days default |
| Other: 90 days default |
Attribution Strategy by Business Type
E-commerce
| Factor | Recommended Approach |
| Meta | 7-day click for most products |
| Google | 30-day click for standard, 7-14 for impulse |
| High AOV | Longer windows (consider full journey) |
| Low AOV | Shorter windows (impulse behavior) |
Lead Generation
| Factor | Recommended Approach |
| Meta | 7-day click (form fills are quick decisions) |
| Google | 30-60 day for B2B, 14-30 for B2C |
| Long sales cycle | Supplement with offline conversion import |
| Short sales cycle | 7-14 day windows |
Subscription/SaaS
| Factor | Recommended Approach |
| Trial signups | 7-30 day click |
| Paid conversions | 30-60 day |
| Enterprise | 60-90 day, plus CRM integration |
| Consumer | 14-30 day |
View-Through Attribution
The Debate
View-through attribution credits conversions to users who saw but didn't click your ad. It's controversial:
Arguments For:
- Captures awareness influence
- Recognizes brand impact
- More complete picture
- Especially relevant for video/display
Arguments Against:
- Hard to prove causality
- Inflates reported performance
- Can overlap with other channels
- Open to manipulation
Best Practices
Use conservatively — 1-day view maximum
Compare with and without — Understand the delta
Consider incrementality — View-through lift testing
Don't double count — Deduplicate across channels
Question high view-through — If most conversions are VT, investigate
High view-through percentages often indicate you're getting credit for conversions that would have happened anyway. Use incrementality testing to verify.
Advanced Attribution Approaches
Incrementality Testing
The gold standard for true attribution:
Holdout groups — Don't show ads to control
Geo testing — Dark markets vs. exposed
Conversion lift — Platform-native measurement
Matched market analysis — Statistical comparison
Marketing Mix Modeling (MMM)
For macro-level attribution:
- All channels together
- Historical data analysis
- Accounts for external factors
- No individual tracking needed
- Privacy-compliant
Multi-Touch Attribution (MTA)
Distributes credit across touchpoints:
- Requires cross-channel data
- Various models available
- Better than last-touch alone
- Still limited by tracking gaps
Common Mistakes
1. Using Misaligned Windows
Comparing Meta 7-day to Google 30-day makes no sense. Align or understand the delta.
2. Ignoring Window in Optimization
Meta optimizes for your chosen window. Wrong window = wrong optimization.
3. Over-Relying on View-Through
High view-through conversion percentages should trigger skepticism, not celebration.
4. Forgetting Conversion Delay
Some conversions take days/weeks. Don't evaluate campaigns before window closes.
5. Not Testing Windows
Your optimal window may differ from defaults. Test different settings.
The Bottom Line
Attribution windows in 2026 require:
Platform understanding — Meta and Google work differently
Business alignment — Match windows to purchase cycle
Consistency — Same settings across similar campaigns
Skepticism — Question high view-through rates
Supplemental testing — Incrementality for truth
Adaptability — Privacy changes will continue
> "The right approach is to use multiple measurement methods by combining attribution, MMM, and incrementality testing for a complete picture."
AdBid normalizes attribution across platforms, showing you comparable data regardless of window settings. Understand your true performance. See unified attribution.
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