Attribution Models in Google Ads: Choosing the Right One for Your Campaigns

If you’re running paid ads, it’s important to recognise how much of an impact each touchpoint has on the final sale. Imagine someone clicks on your ad several times on many different devices, sees display ads multiple times, and then later types in a brand-related search term and converts. Who gets credit for this sale?  Attribution Models in Google Ads play an important role in determining campaign effectiveness, meaning that if you properly analyse how to allocate your budget over time based on analysis, you’ll identify strong sources of revenue or wasteful spending.

Understanding How Attribution Really Works

Think about the last time you made a significant purchase online. You probably didn’t buy immediately after seeing one ad, right? Maybe you researched on your phone during lunch, compared prices on your laptop that evening, and completed the purchase on your tablet the next day. Each of those touchpoints played a role in your decision.

Data attribution is essentially the process of assigning value to each of these interactions. It’s about understanding your customer’s journey from first impression to final conversion. Without proper attribution, you’re essentially flying blind – making decisions based on incomplete information about what’s actually working.

Why This Matters More Than You Think

Here’s something most advertisers don’t realise until it’s too late: the attribution model you choose directly shapes which campaigns appear successful in your reports. This affects everything from budget allocation to which keywords you optimise for, and it plays a huge role in measuring ad profitability across your account.

I’ve worked with businesses that were on the verge of killing their best-performing campaigns simply because they were using an attribution model that didn’t capture the full picture. Once we switched to a more appropriate model, those “underperforming” campaigns suddenly showed their true value.

What Google Sets Up for You Automatically

When you create a new conversion action, Google automatically assigns you a default attribution model. For most advertisers with sufficient conversion data, this means data-driven attribution becomes your starting point. But if your account doesn’t meet the volume requirements, you’ll likely start with last-click attribution instead.

Now, here’s the thing about defaults – they’re designed to work for the average advertiser, not necessarily for your specific business model. A local service business with same-day conversions needs something different from an e-commerce store with a two-week consideration cycle. The default attribution models in Google Ads serve as a reasonable starting point, but they shouldn’t be your final answer.

The Different Approaches You Can Take

Let me walk you through the various types of attribution models available, because each one tells a fundamentally different story about your marketing effectiveness.

Last Click: The Simplest But Most Limited

This model gives 100% credit to whichever ad got clicked right before the conversion happened. It’s incredibly straightforward, which is why many advertisers stick with it. But here’s the problem: it completely ignores every interaction that came before that final click.

Think about how it looks when you’re running brand awareness initiatives and bottom-funnel search campaign ads together. In this case, last-click attribution will credit your search ads as superstars, but report your display campaign as if it were a “dud,” even if those display ads are doing the bulk of the work to get consumers familiar with your brand.

First Click: Focusing on Customer Acquisition

If you do an opposite flip, you could refer to first-click attribution. This type of attribution counts whichever ad first brought someone into your funnel as the source of that conversion. First-click attribution is useful when you want to measure how many customers were acquired through different advertising channels; however, it will not provide any insight into what ultimately convinced someone to make a purchase.

Linear: The Democratic Approach

What if every touchpoint got equal credit? That’s linear attribution in a nutshell. Does someone interact with four different ads before buying? Each ad gets 25% of the credit. It’s fair and balanced, but maybe too balanced – some interactions genuinely matter more than others in the decision-making process.

Valuing Future Conversions: Time Decay System

This model presumes that as time gets closer to the conversion date, weight is added on each touchpoint associated with that conversion (i.e., a user who clicks on an ad yesterday gives more credit for the conversion than another user who clicks on the same ad last week). For businesses that are involved in time-determined promotions or have a short decision-making period, time decay could be very logical.

Position-based: Recognising Historic Moments

The U-shaped attribution or first/last interaction model is an attribution model that gives 40% to both the first and the last interaction, where the other 20% is distributed equally across all interactions between them. This model acknowledges the significance of both of these times in establishing trust with potential customers.

The Power of Machine Learning

Now we get to the really interesting option. Data-driven attribution models use Google’s machine learning to analyse your actual conversion patterns and figure out how much credit each touchpoint truly deserves based on your specific data.

Instead of following rigid rules, this approach looks at thousands of conversion paths in your account and identifies patterns. Maybe it discovers that your YouTube ads are exceptionally good at starting customer journeys, while your Shopping campaigns excel at converting people who are already familiar with your brand. The data-driven attribution models in Google Ads adjust credit distribution to reflect these insights.

The catch? You need significant conversion volume to qualify – at least 3,000 ad interactions and 300 conversions within 30 days for Search campaigns. Many smaller advertisers won’t meet this threshold, which means sticking with rule-based models.

Finding Out What You’re Currently Using

To figure out which model is being used for tracking conversions, here’s how to check attribution models in Google Ads: you can check it in Google Ads by going to Tools & Settings, then finding Conversions under Measurement. Open any conversion action, and you’ll see the current attribution model in the details.

But here’s an awesome pro tip: you can also check out your model comparisons via the Model Comparison report, located under Tools & Settings > Attribution. The report will use your data to show you how well your campaigns would have performed using other attribution models (but no actual changes will be made). This report is great for understanding what kind of impact the current model would have before you make the switch.

Making Changes When Needed

Decided that a different model would better serve your business goals? The process to change attribution models in Google Ads is straightforward. Go to your Conversions settings, select the conversion action you want to modify, click Edit Settings, choose Attribution model from the options, select your preferred model, and save your changes.

One word of caution: this change affects how your historical data gets reported going forward. I always recommend running that model comparison report first to understand exactly what will change in your metrics. Many pay-per-click companies make this mistake – they switch models impulsively and then panic when their numbers shift dramatically.

Selecting the Right Model for Your Situation

So which attribution model should you actually use? If I’m being honest, there’s no universal answer that works for everyone. Your ideal choice depends entirely on your business model, customer journey, and campaign goals.

If you have enough conversion data to qualify, the Google Ads attribution models that leverage machine learning are almost always your best bet. Why manually guess at which touchpoints matter when algorithms can analyse your actual data and tell you?

But for businesses that don’t meet those volume requirements, here’s how I think about it: Are you running primarily bottom-funnel search campaigns with quick conversion cycles? Last-click might work fine for you. Focused heavily on bringing in new customers through awareness campaigns? Consider first-click. Running complex, multi-touchpoint campaigns across awareness, consideration, and decision stages? Position-based or time-decay could give you better insights.

The key is matching the model to how your customers actually make purchase decisions. A B2B software company with six-month sales cycles needs dramatically different attribution than a restaurant promoting daily lunch specials.

How Attribution Impacts Your Bidding Strategy

Here’s something crucial that many advertisers overlook: your attribution model directly influences choosing the right bidding model and how automated bidding strategies perform. If you’re using Target CPA, Target ROAS, or Maximise Conversions, Google’s algorithms rely on attribution data to decide where to place bids.

Switch from last-click to data attribution models in Google Ads, and campaigns that were getting shortchanged suddenly show more value. Google’s smart bidding adjusts accordingly, potentially shifting budget to campaigns that were always contributing but just weren’t getting recognised. This can completely reshape your campaign performance.

Connecting to Broader Performance Measurement

Attribution also ties directly into how you evaluate overall campaign profitability. When you’re trying to determine ROI across different campaign types and channels, the attribution model determines which campaigns get credit for revenue. Use the wrong model, and you might be reporting vastly different profitability numbers than reality.

I’ve seen situations where switching types of attribution models in Google Ads revealed that supposedly unprofitable campaigns were actually driving significant value – they just weren’t getting the credit they deserved under the previous model.

Final Thoughts on Getting This Right

Understanding Google Ads attribution models isn’t just an academic exercise in marketing theory; it’s about making smarter decisions with real money. The default attribution models in Google Ads might work perfectly well for your business, or they might be masking significant opportunities for improvement.

My recommendation? Start by running the model comparison report today. See how different types of attribution models would change your performance metrics. If you qualify for data-driven attribution models in Google Ads, seriously consider making that switch. The machine learning approach typically outperforms rule-based models once you have sufficient data.

If you’re not there yet, choose a rule-based model that actually reflects your customer journey rather than just accepting whatever was set up initially. And remember, attribution isn’t a one-time decision. As your business evolves, your campaigns mature, and your customer behaviour shifts, it’s worth periodically revisiting whether your attribution model still makes sense.

The goal isn’t perfect attribution; that’s probably impossible. The goal is understanding where your conversions actually come from well enough to invest more in what works and less in what doesn’t. Get that right, and attribution becomes one of your most powerful optimisation tools.