# Measure the incremental impact of every ad — Whether it’s clicked or not

Every day you spend thousands on Meta, but most impressions never get clicked. The impact was hard to measure — we bring it back into the picture with the Full Impact model.

## Trusted by 20,000+ brands

## Current attribution models miss what truly drives the purchase

Your display ads like Meta, YouTube, and TikTok create intent long before a shopper clicks anything. Traditional attribution only credits what gets clicked — not what drives incremental revenue.

## We reveal the influence behind every impression, click, and journey.

### Track customer events across channels

Capture the complete user journey — every interaction with your ads and your website: view, click, search, add-to-cart, revisit...

### Model the impact of non-clicked impressions

Analyze massive user behavioral patterns with AI to estimate the contribution of unseen impressions to the final conversion.

### Weight touchpoints with AI attribution model

Dynamically measure the actual value of touchpoints, rather than just their position like Last Click models. We analyze whether a specific touchpoint truly drives an increase in conversion rate, creating a credit distribution uniquely tailored to your business characteristics.

## How it works

### Synthetic exposure modeling

Upper-funnel campaigns like display ads are deeply undervalued with traditional click-based attribution models.

Attribuly’s Synthetic Exposure uses AI to learn large-scale behavioral patterns and infer how these “invisible” impressions actually contributed to the final conversion — without relying on user-level impression logs, making brand-awareness investment measurable.

- Learn patterns through AI and action correlation from millions of user journeys
- Predict the likelihood of an impression contributing
- Fully privacy-friendly. Assign proportional impact without needing impression logs

### Weight touchpoints with AI attribution model

Most attribution models rely on arbitrary rules—giving all credit to the last click or splitting it equally. This ignores the true influence of each interaction.

Our model evaluates the unique contribution of every touchpoint by calculating how much it increased the probability of conversion. It reveals the actual value of your upper-funnel marketing and cross-channel interactions, ensuring fair credit distribution.

- Fairly distribute credit based on actual conversion impact
- Identify undervalued high-impact touchpoints
- Tailored to your specific store's customer journeys

## What you get

### Real impact from display ads

Identify the impact of upper-funnel campaigns that drive lift but never get clicks, like display ads on Meta, YouTube, TikTok, etc.

### Better budget allocation

Stop shifting dollars to “what gets last-click credit.” Invest where incremental growth actually comes from.

## Compare with DDA of Google Analytics 4

| Category | GA4 | Attribuly Full Impact |
| --- | --- | --- |
| **Dataset** | Google ecosystem only | All datapoints you connect to Attribuly |
| **Transparency** | Black box design | You see customer journey of every order |
| **Attribution Algorithm** | Focus on relevance | Focus on incremental impact |
| **View-through** | Google ads only | Meta, Tiktok, Amazon and more |

Ada  
DTC manager  
@A leading home Brand  
> "We were looking for a solution to measuring display ads for years. This is exactly what we need. We now allocate our budgets smarter with a more clear view."

## Frequently Asked Questions

For which scenarios is the modeling of non-clicked impression impact applicable?

It mainly applies to orders where the first touchpoint in the user's behavior path is Direct, organic search, brand term search ads, Email, and other channels with obvious touchpoint information loss.

For KOL/content-type exposures on platforms like YouTube: Can it be included in Full Impact or attribution analysis?

If the YouTube KOL video placement is an ad, its data can be included in Full Impact. If it is just organic YouTube content views, it cannot be included in the Full Impact prediction scope.

How does Full Impact reduce 'Direct' traffic?

High 'Direct' traffic usually means the source is lost (e.g., from iOS privacy blocks). Full Impact uses AI to analyze user behavior patterns and probabilistic modeling to re-assign this traffic to its most likely true source, often revealing hidden contributions from social or display ads.

How does it help with branding ads?

Branding ads (like top-of-funnel display or video) often don't get immediate clicks but drive later conversions. Full Impact measures this 'view-through' influence, ensuring these campaigns get the credit they deserve instead of being undervalued by last-click models.