Attribution determines which clicks get credit for conversions. For Shopping campaigns, the attribution model you use can swing your reported ROAS by 20-40%. Most advertisers don't realize the model they're using is systematically undervaluing their best campaigns.
The problem is straightforward: Shopping ads often introduce customers to products, but brand search or direct visits close the sale. Under last-click attribution, Shopping gets zero credit for those conversions. The result is a distorted view where your discovery campaigns look unprofitable while your brand campaigns look like they're doing all the work. Understanding how attribution models distribute credit is essential for making accurate ROAS-based optimization decisions.
How Attribution Works in Google Ads
When a customer converts, Google needs to decide which ad interaction or interactions deserve credit for that conversion. This sounds simple when there's only one click in the path, but the reality of modern shopping behavior is rarely that clean.
A typical e-commerce conversion path involves multiple touchpoints. A user might discover a product through a Shopping ad, compare prices across retailers, read reviews, and then return through a brand search ad or a direct visit to complete the purchase. Each of those interactions had a role in the eventual conversion, but attribution models differ on how they assign value.
With Shopping campaigns specifically, users often sit at the top of this funnel. They discover products through Shopping ads with images, prices, and reviews visible right in the search results. That first impression drives the entire purchase journey, but if the final click happens through a different campaign, Shopping may get no credit at all depending on the model. For a deeper look at the full conversion path, see Google's attribution models documentation.
The attribution model you choose determines how credit is split across these touchpoints, and it has a direct impact on which campaigns appear profitable and which appear to be wasting money.
Available Attribution Models
Google Ads currently offers two attribution models for search and Shopping campaigns. The landscape has simplified significantly since 2023, when Google deprecated several models.
Data-Driven Attribution (DDA)
Data-driven attribution has been the default model for new conversion actions since 2023. It uses machine learning to analyze your account's actual conversion patterns and assign credit based on how much each touchpoint contributed to the conversion. If Shopping ads consistently appear in the paths of users who convert, DDA gives Shopping proportional credit even when it wasn't the last click.
According to Google's documentation on data-driven attribution, DDA compares the paths of users who converted with those who didn't, then uses this comparison to identify which touchpoints had the greatest influence on conversion likelihood.
Last-Click Attribution
Last-click gives 100% of the conversion credit to the final ad interaction before the conversion. It ignores every other touchpoint in the path. If a user clicked a Shopping ad on Monday, a display ad on Wednesday, and a brand search ad on Friday before purchasing, only the brand search ad gets credit.
While last-click is simple to understand, it systematically favors campaigns that close sales (brand search, retargeting) over campaigns that initiate them (Shopping, broad search). Many accounts still have legacy conversion actions set to last-click even though the default has changed.
Deprecated Models
In June 2023, Google removed linear, time-decay, and position-based attribution models. As the Google Ads blog announcement explained, these rule-based models couldn't adapt to the complexity of real conversion paths. Accounts using them were automatically migrated to data-driven attribution.
| Model | Status | How It Assigns Credit |
|---|---|---|
| Data-Driven | Default | ML-based, proportional to actual contribution |
| Last-Click | Legacy | 100% to the final click |
| Linear | Removed | Equal credit to all touchpoints |
| Time-Decay | Removed | More credit to recent touchpoints |
| Position-Based | Removed | 40% first, 40% last, 20% middle |
Why Last-Click Understates Shopping
Shopping ads typically sit at the top of the purchase funnel. Users discover products through Shopping ads with rich product imagery and pricing, then continue their research before converting through a different channel. Under last-click attribution, Shopping gets zero credit for the conversions it initiated.
Here is a concrete example of how this plays out:
- Day 1: User searches "running shoes for flat feet," clicks your Shopping ad ($1.20 CPC), browses your product page, leaves
- Day 2: User reads reviews, compares prices on other sites
- Day 3: User searches your brand name, clicks your brand search ad ($0.40 CPC), purchases for $120
Under last-click attribution, Shopping ROAS = $0 / $1.20 = 0x, and brand search ROAS = $120 / $0.40 = 300x. The Shopping ad gets nothing. The brand search ad looks impossibly efficient.
Under data-driven attribution, both touchpoints share credit based on their actual contribution. If DDA determines Shopping was responsible for 40% of the conversion value, the numbers become: Shopping ROAS = $48 / $1.20 = 40x, and brand search ROAS = $72 / $0.40 = 180x. Both campaigns get credit that reflects their role.
Key Insight
Across accounts that switch from last-click to data-driven attribution, Shopping campaigns typically see a 20-40% increase in attributed ROAS. The total revenue doesn't change; only how it's distributed across campaigns. Shopping was always driving these conversions, but last-click hid the evidence.
This matters beyond reporting. Attribution directly influences optimization decisions. If you're using last-click and your Shopping ROAS looks weak, you might reduce Shopping bids or budget. That reduces the top-of-funnel discovery that feeds your entire conversion path, and eventually brand search performance drops too. It's a self-reinforcing cycle of underinvestment driven by a measurement flaw, and it's one of the most common forms of wasted spend in Shopping accounts.
Checking Your Current Model
Before making any changes, you need to know which attribution model your conversion actions currently use. Here's how to check:
- In Google Ads, click the Tools & Settings icon (wrench) in the top navigation
- Under "Measurement," select Conversions
- Click on the specific conversion action you want to check (e.g., "Purchase" or "Transaction")
- Scroll to the Attribution model field
If you see "Data-driven" you're already on the recommended model. If you see "Last click," your Shopping campaign data is likely understated.
Using the Model Comparison Report
Google Ads provides a tool that lets you compare how conversions would be distributed under different attribution models. Access it through Tools & Settings > Measurement > Attribution > Model comparison. This report shows side-by-side how each campaign's conversions and conversion value change between models.
What to look for: large differences between last-click and data-driven for your Shopping campaigns. If Shopping shows significantly more conversions under DDA than under last-click, it's a strong signal that Shopping is driving conversions that last-click isn't crediting. Research from Search Engine Journal consistently finds that Shopping campaigns are among the most undervalued under last-click models.
Watch Out
If your model comparison shows minimal differences between last-click and DDA, your conversion paths may be short (single-touchpoint). This is common for low-consideration, impulse-purchase products. In these cases, the attribution model matters less.
Switching to Data-Driven Attribution
Prerequisites
Data-driven attribution requires minimum data thresholds to function. Your account needs at least 300 conversions in 30 days and 3,000 ad interactions in the same period. Google needs this volume to build a reliable model of which touchpoints drive conversions in your specific account.
If you don't meet these thresholds, Google will show last-click as the only available option. Focus on growing conversion volume first. Using micro-conversions like "add to cart" or "begin checkout" as interim conversion actions can help you qualify sooner, though your primary optimization should still target actual purchases.
How to Switch
- Go to Tools & Settings > Measurement > Conversions
- Click on each purchase conversion action
- Click Edit settings
- Under Attribution model, select Data-driven
- Save and repeat for all purchase conversion actions
Important
Switch all purchase conversion actions at the same time. Mixing models across conversion actions creates inconsistent reporting that makes campaign comparison unreliable.
What to Expect After Switching
When you switch to DDA, you'll see ROAS shift between campaigns. Shopping campaigns will typically show higher ROAS, while brand search campaigns will show lower ROAS. This is not a performance change; it's a measurement correction. Your total conversions and total revenue remain exactly the same.
If you're running Smart Bidding strategies like Target ROAS or Maximize Conversion Value, expect a recalibration period of 2-3 weeks. The bidding algorithms need time to adjust to the new credit distribution. During this period, you may see more volatility in daily performance. Don't panic or make manual adjustments during this learning phase.
According to Think with Google, advertisers who switch to DDA and allow Smart Bidding to recalibrate typically see improved overall account performance because budget allocation shifts toward campaigns that actually initiate conversions rather than campaigns that simply close them.
What This Means for Your Dashboard
The ROAS you see in SKU Analyzer reflects whatever attribution model your Google Ads account uses. The data is pulled directly from the Google Ads API, which reports conversions and conversion values based on your active attribution settings.
This means that if you're currently on last-click attribution, the product-level ROAS shown in your dashboard is understated for products that typically assist conversions rather than close them. High-funnel discovery products, the ones users find through Shopping and then buy through other channels, will show lower ROAS than they actually deserve.
The recommendation is clear: switch to data-driven attribution before making optimization decisions based on product-level ROAS. If your Shopping reports show certain products with unexpectedly low ROAS despite high click volume, the attribution model may be the culprit rather than the product itself.
After switching, there's an important nuance with historical data. Google Ads will re-attribute historical data under the new model within its own interface, but data that has already been synced to external tools (including SKU Analyzer) will reflect the attribution model that was active at the time of the sync. A fresh data sync after switching will pull the updated attribution values. Understanding conversion lag alongside attribution changes helps you set the right expectations for when your data will fully stabilize.
For accounts using POAS (Profit on Ad Spend) as their primary metric, the same attribution logic applies. DDA distributes profit credit across touchpoints the same way it distributes revenue credit, giving you a more accurate picture of which products generate actual profit through the Shopping channel.
If you use enhanced conversions, DDA becomes even more effective. Enhanced conversions provide more complete conversion data, which means the machine learning model has better signal to work with when distributing credit across touchpoints.
Frequently Asked Questions
How do I check which attribution model I'm using?
In Google Ads, go to Tools & Settings > Measurement > Conversions. Click on the conversion action you want to check, then look for the Attribution model field. Most accounts default to data-driven attribution since Google made it the default in 2023, but older conversion actions may still be set to last-click.
Will switching to data-driven attribution change my total conversions?
No, your total conversion count and total revenue stay exactly the same. The only thing that changes is how credit is distributed across campaigns and ad interactions. Shopping campaigns will typically see higher attributed conversions, while brand search campaigns will see lower attributed conversions, but the sum remains identical.
What if I don't have 300 conversions per month?
If your account doesn't meet the minimum threshold of 300 conversions in 30 days and 3,000 ad interactions, Google will default to last-click attribution. Focus on growing your conversion volume first, and consider using micro-conversions (add to cart, begin checkout) as interim conversion actions to qualify for data-driven attribution sooner.
Should I change all conversion actions at once?
Yes, switch all purchase conversion actions simultaneously for consistent reporting. If some actions use data-driven and others use last-click, your campaign-level data will be a confusing mix of attribution methodologies, making it impossible to compare performance accurately across campaigns.
Conclusion
Attribution isn't just a reporting detail. It shapes every optimization decision you make. Under last-click, Shopping campaigns appear less valuable than they are, which leads to underinvestment in the campaigns that drive product discovery. Switching to data-driven attribution corrects this by distributing credit based on actual contribution rather than last-touch position.
Key takeaways:
- Last-click systematically undervalues Shopping. Users discover through Shopping but convert through brand search, leaving Shopping with 0% credit.
- DDA corrects this by distributing credit based on actual conversion patterns, typically increasing Shopping ROAS by 20-40%.
- Total conversions don't change. Only the distribution across campaigns shifts.
- Many accounts still have legacy conversion actions on last-click without realizing it. Check yours today.
- Switch to DDA before making product-level ROAS decisions. Last-click data hides Shopping's real impact.
Fix your attribution model, let Smart Bidding recalibrate, then optimize based on data that reflects reality. For more on the conversion tracking fundamentals that make all of this work, see the rest of our measurement guides.