Google Ads Attribution Models Compared

As a performance marketer, you live and breathe the Google Ads interface. You meticulously craft campaigns, research keywords, and optimize ad copy. You see conversions being reported, and your cost per acquisition (CPA) seems stable. But a nagging question lingers beneath the surface of your dashboards: are you giving credit where credit is truly due? Is that high performing branded keyword really the hero of your account, or is it just the last player to touch the ball in a much longer game?

The answer to this question is determined by your choice of attribution model within Google Ads. This single setting is one of the most critical, yet frequently overlooked, components of a successful advertising strategy. It is the rulebook that Google uses to assign credit for conversions to the different ads, keywords, and campaigns a user interacts with on their path to purchase.

This deep dive will compare the various attribution models available in Google Ads, from the default last click model to the sophisticated data driven approach. We will explore how each one works, its specific pros and cons, and provide a clear framework for choosing the right model for your business. Understanding these differences is the first step toward unlocking more accurate reporting, smarter bidding, and ultimately, a higher return on your ad spend.

For a broader overview of attribution theory that extends beyond Google Ads, we recommend reading our comprehensive guide, Marketing Attribution Models: From Last-Click to Data-Driven

Part 1: Why Your Google Ads Attribution Model Matters More Than Ever

In the past, the attribution model was primarily a reporting feature. It changed how you viewed your data, but its direct impact on campaign performance was less pronounced. Today, that has completely changed. Your choice of attribution model is now a direct input that fundamentally influences Google's powerful machine learning algorithms.

The primary reason for this is the rise of Smart Bidding. Strategies like Target CPA, Target ROAS, and Maximize Conversions do not just react to your bids; they proactively adjust bids in real time for every single auction based on the likelihood of a conversion. The attribution model you select is what teaches the algorithm what a valuable "path to conversion" looks like.

• If you use Last Click Attribution: You are telling Smart Bidding that only the final keyword and ad a user clicks matter. The algorithm will then learn to aggressively bid on these bottom of the funnel terms, while undervaluing the generic, top of funnel keywords that may have started the customer's journey. Over time, this can starve your pipeline of new customers.
• If you use a Multi Touch Model: You are teaching Smart Bidding that early and mid journey interactions have value. The algorithm will then learn to assign a portion of the conversion value to those initial discovery keywords and awareness campaigns, ensuring they continue to get the budget they need to introduce new users to your brand.

Choosing an attribution model is no longer a passive reporting choice. It is an active strategic decision that dictates how your budget is spent and how your account will be optimized by Google's AI.

Part 2: The Rule Based Models in Google Ads: A Detailed Comparison

Google Ads offers several rule based attribution models. These models distribute credit according to a fixed, predetermined rule, regardless of the actual user behavior patterns in your account. While they are less sophisticated than the data driven model, they are a significant improvement over the default last click setting.

To illustrate the differences, let's use a consistent example of a customer journey:

1. Touchpoint 1: User searches "best waterproof running shoes" (a generic keyword) and clicks a standard Search Ad. They browse but do not buy.
2. Touchpoint 2: Two days later, they see one of your Shopping ads while browsing Google Images and click it.
3. Touchpoint 3: A week later, they search for "Nike Pegasus Shield review" (a specific, mid funnel keyword) and click another one of your Search Ads.
4. Touchpoint 4: The next day, they search for "Your Brand Name Nike shoes" (a branded keyword), click your final Search Ad, and make a purchase.

Here is how each rule based model would assign credit for this conversion:

Last Click

• How it Works: Assigns 100% of the conversion credit to the very last ad the customer clicked before converting.
• Example: The branded search ad ("Your Brand Name Nike shoes") receives 100% of the credit. All previous three touchpoints receive 0%.
• When to Use It: Honestly, it is rarely the best choice. Its only real use case is for businesses with extremely short, transactional sales cycles (e.g., emergency plumbing services) where the first and last click are almost always the same.
• Potential Pitfalls: It systematically overvalues branded keywords and undervalues the prospecting and research keywords that generate initial demand. It provides a completely distorted view of your marketing funnel.

First Click

• How it Works: Assigns 100% of the conversion credit to the very first ad the customer clicked.
• Example: The generic search ad ("best waterproof running shoes") receives 100% of the credit. All subsequent three touchpoints receive 0%.
• When to Use It: If your primary goal is pure brand awareness and you want to identify which keywords are most effective at introducing new customers, this model can be insightful.
• Potential Pitfalls: It completely ignores the crucial role of mid and bottom funnel keywords that nurture interest and close the sale. It can make you overinvest in broad terms that generate clicks but not necessarily qualified, high intent traffic.

Linear

• How it Works: Distributes the conversion credit equally across all ad clicks on the path to conversion.
• Example: Each of the four ad clicks (generic search, Shopping, review search, branded search) receives 25% of the credit.
• When to Use It: This is a great "starter" multi touch model. It is a safe and balanced choice for advertisers who want to ensure every touchpoint is valued and whose marketing strategy is focused on maintaining contact and awareness throughout the entire customer journey.
• Potential Pitfalls: It operates on the unrealistic assumption that all touchpoints are equally important. A click on a generic discovery keyword is likely less influential than a click on a high intent, branded keyword just before purchase, yet this model treats them the same.

Time Decay

• How it Works: Gives more credit to ad clicks that happened closer in time to the conversion. It uses a 7 day half life, meaning a click 7 days before the conversion gets half as much credit as a click on the day of the conversion.
• Example: The final branded ad click would get the most credit. The click from the day before would get slightly less. The Shopping ad click from over a week prior would get significantly less, and the initial generic search click would get the least credit of all.
• When to Use It: This model is particularly effective for businesses with shorter consideration phases or for promotional campaigns. It acknowledges earlier touchpoints but correctly weights the interactions that pushed the customer to make a final decision.
• Potential Pitfalls: For businesses with very long sales cycles (e.g., high end B2B services, luxury cars), this model can still undervalue the critical first touchpoint that initiated a months long research process.

Position Based (U-Shaped)

• How it Works: This model attempts to get the best of both worlds. It assigns 40% of the credit to the first ad click, 40% to the last ad click, and distributes the remaining 20% evenly among the clicks in the middle.
• Example: The first ad click ("best waterproof running shoes") gets 40%. The last ad click ("Your Brand Name Nike shoes") gets 40%. The two middle clicks (Shopping and review search) share the remaining 20%, receiving 10% each.
• When to Use It: This is often considered the most advanced and balanced of the rule based models. It is an excellent choice when you value both the touchpoints that introduce customers to your brand and the touchpoints that close the sale.
• Potential Pitfalls: Its main weakness is that it can undervalue the mid funnel nurturing phase, which can be critical for complex purchases that require significant research and consideration.

Rule Based Model Comparison Table

Part 3: The Gold Standard: Data Driven Attribution (DDA)

While the rule based models are a major step up from last click, they all share a common limitation: the rules are static and based on general assumptions. Data Driven Attribution (DDA) shatters this limitation. It is Google's most advanced and intelligent model, and it should be the goal for any serious advertiser.

What is Data Driven Attribution?

Instead of using a fixed rule, DDA uses Google's machine learning to analyze your account's unique conversion data. It looks at the paths of customers who convert and compares them to the paths of customers who do not. By analyzing thousands of these paths, the algorithm identifies which ad interactions at which points in the journey have the greatest statistical impact on the probability of a conversion.

It creates a custom model tailored specifically to your business and your customers. It might learn, for example, that for your account, clicks on Shopping ads early in the journey are highly influential, while clicks on certain display ads are not. It then assigns credit based on this data driven insight, not a generic rule.

As PPC expert Brad Geddes notes, "You want to be able to see the entire customer journey... If you are only looking at the last click, you are missing out on how users are finding you and what they are doing before they are converting." Data Driven Attribution is the only model that truly attempts to see and value that entire journey algorithmically.

The Prerequisites and the Data Integrity Problem

DDA is incredibly powerful, but it needs sufficient data to work its magic. To be eligible for DDA, a conversion action must have at least 3,000 ad interactions (clicks or video engagements) and 300 conversions within a 30 day period.

However, there is a more profound requirement: the data must be accurate and complete.

This is where the concepts from our main attribution hub become critically important. If a significant portion of your conversions are not being tracked because of ad blockers or browser privacy settings like Apple's ITP, then your data is incomplete. The DDA algorithm is trying to learn from a dataset that has massive holes in it. Its conclusions, while "data driven," will be based on a skewed reality.

By implementing a first party data collection solution, you ensure that a more complete and accurate set of conversion data is sent to Google Ads. This provides the DDA model with a cleaner, richer dataset to learn from, making its insights more accurate and its impact on Smart Bidding performance more powerful. You are giving the machine better fuel, so it produces better results.

Part 4: How to Choose and Implement Your Attribution Model

Ready to move beyond last click? Here is a practical, step by step guide to choosing and changing your attribution model in Google Ads.

Step 1: Audit Your Current Model
First, see what you are currently using.

• In your Google Ads account, navigate to Tools and Settings > Measurement > Conversions.
• Click on the name of the primary conversion action you want to investigate.
• Click Edit settings and expand the "Attribution model" section. This will show your current model. For many older accounts, this will still be "Last click."

Step 2: Assess Your Business and Sales Cycle
Before you change anything, think about your business.

• Short Sales Cycle (< 1 week): If your customers decide quickly, a model like Time Decay can be very effective as it weights the final interactions most heavily.
• Long Sales Cycle (> 1 month): If customers do a lot of research, a Linear or Position Based model is a much better starting point than last click, as it ensures those early research touchpoints get credit.

Step 3: Check Your Eligibility for Data Driven Attribution
This should be your ultimate goal. In the same attribution model settings from Step 1, Google will tell you if you are eligible for DDA. If you are, this is almost always the best choice. If you are not, it gives you a clear goal to work towards: increasing your conversion volume to meet the threshold.

Step 4: Use the Model Comparison Tool
This is one of the most powerful and underutilized tools in Google Ads.

• Navigate to Tools and Settings > Measurement > Attribution.
• In the left hand menu, click Model Comparison.
• This tool allows you to compare your current model against any other model. You can see how the number of conversions and the cost per conversion would have changed for your campaigns, ad groups, and keywords if you had been using a different model.
• For example, you can compare "Last click" to "Position based." You will likely see that your branded campaigns lose conversion credit, while your generic/prospecting campaigns gain credit. This exercise provides invaluable insight into the hidden value of your top of funnel efforts.

Step 5: Make the Switch and Be Patient
Once you have used the Model Comparison Tool and decided on a new model (ideally DDA, or a rule based model if you are not yet eligible), make the change in your conversion action settings.

Important: When you change your attribution model, be prepared for a period of adjustment.

• Your conversion data will change. Some campaigns will now report more conversions, others fewer. This is normal.
• If you are using Smart Bidding, the algorithm will enter a new learning phase. Performance may fluctuate for a week or two as it adjusts to the new way of valuing conversions. Do not panic and make drastic changes during this period.

Conclusion: Writing a More Profitable Story

Moving beyond last click attribution in Google Ads is no longer a suggestion; it is a necessity for competitive and growth focused advertisers. By failing to do so, you are operating with a blindfold on, ignoring the vast majority of the customer journey and feeding your Smart Bidding strategies incomplete information.

Your journey should be one of progressive enhancement. Start by using the Model Comparison Tool to understand the flaws in your current last click view. Move to a more balanced rule based model like Position Based or Time Decay to begin valuing the full funnel. Your ultimate objective should be to adopt Data Driven Attribution, as it provides the most nuanced, customized, and accurate picture of performance.

Remember, the attribution model you choose determines the story your data tells you. By choosing a more intelligent model, and by ensuring it is powered by the most complete and accurate data possible, you enable yourself to read that story correctly and, in turn, write a more profitable one for your business.

To explore these concepts of data integrity and their impact on all your marketing platforms, visit our main hub, Marketing Attribution Models: From Last-Click to Data-Driven