Understand Google Ads Attribution

Optimising a Google ads account based on incomplete or misleading data could see your best efforts go to waste.

Google Ads Conversions

What is Attribution?

In Google Ads, attribution is a method of giving a certain amount of credit to each touchpoint in a user's paid search journey. This is important because in many cases a potential customer will search more than once, and potentially click on more than one ad, before becoming a customer.

If a searcher clicks on just one ad before converting to a customer then it's easy to say that click should get all of the credit. But what if the searcher clicks on two ads and then purchases, how should the credit be split? 50/50? Would the searcher of clicked on the second ad if they hadn't first been made aware of your brand on their first click? Maybe 60/40 or 70/30 would be more appropriate? This is where attribution modelling comes in.

Optimising a Google Ads account based on data that isn't aligned with reality could see your best efforts go to waste and opportunities to generate real-world results missed.

Google Ads Attribution Models

Attribution models in Google Ads take into account paid clicks only. These models provide a way of splitting credit between different campaigns within your account but they do not consider any other channels or touchpoints.

Google Ads provides several attribution models and all you have to do is pick the one that's most applicable to your customer journey:

  • Last click: Gives all credit for the conversion to the last-clicked ad and corresponding keyword.

  • First click: Gives all credit for the conversion to the first-clicked ad and corresponding keyword.

  • Linear: Distributes the credit for the conversion equally across all ad interactions on the path.

  • Time decay: Gives more credit to ad interactions that happened closer in time to the conversion. Credit is distributed using a 7-day half-life. In other words, an ad interaction eight days before a conversion gets half as much credit as an ad interaction one day before a conversion.

  • Position-based: Gives 40% of credit to both the first and last ad interactions and corresponding keywords, with the remaining 20% spread out across the other ad interactions on the path.

  • Data-driven: Distributes credit for the conversion based on your past data for this conversion action. It's different from the other models, in that it uses your account's data to calculate the actual contribution of each interaction across the conversion path. This is only available to accounts with enough data.

At Tilious, 9 times out of 10, we use the position-based attribution model. This puts emphasis on the first and last clicks, to introduce the brand in the first instance and complete the sale in the last instance, but doesn't ignore what happens in the middle either.

The general rule is to use whatever attribution model best fits your customer journey, as long as it's not last click! Last click is the default attribution model and your first step should be to change all conversions to a different model.

The main criticism with last click attribution is it gives no credit to what came before. Accounts using the last click attribution model are likely to see a high proportion of brand campaign conversions. This happens because searchers will be introduced to the brand on a generic search and then return with a brand search to complete the purchase. The problem is this will undervalue your generic campaigns, which are in fact a key part of the purchasing journey, and could lead you to make poor decisions when it comes to optimising the account.

Native Google Ads Conversions

The other important element to consider is how you track conversions in the first place.

There are two main ways to implement Google Ads conversions: either directly via Google Ads using the code provided (native conversions) or by importing conversions from Google Analytics.

It's important to note that Google Ads attribution models will only work on conversions deemed to be a result of Google paid search. For this reason, Google Ads native conversion tracking, and not imported Google Analytics conversions, should always be used.

Let me explain, the attribution model used by Google Analytics is last non-direct click. That means only paid search traffic that was the last non-direct click will be passed to Google Ads. Here's an example:

  1. Google Ads Click > Conversion

  2. Organic Search Click > Google Ads Click > Conversion

  3. Google Ads Click > Direct Visit > Conversion

  4. Google Ads Click > Organic Search Click > Conversion

If you are using Google Analytics imported conversions then only the first three conversions will be passed to Google Ads. The fourth conversion will not be sent to Google Ads. It doesn't matter what attribution model is set in Google Ads, if you import conversions from Google Analytics some will be missed where Google Ads has played a part.

Using Google Ads native conversion tracking will give credit to all four conversions in which Google Ads played a part.


It's best to think of attribution for Google Ads in two steps. First is the data you feed Google Ads and second is how you attribute that data to various campaigns within your Google Ads account.

Google Ads attribution models can only act on the data they are fed. If you use imported Google Analytics conversions then only Google Ads last non-direct clicks will be given credit. For a more accurate reflection of performance make sure you're using native Google Ads conversion tracking.

Within Google Ads make sure to use an attribution model other than last click. We recommend a position-based attribution model to distribute credit across campaigns at each point in the customer journey with emphasis on the first and last touchpoints.

On average, our clients see a +60% increase in traffic and +65% increase in revenue from search in the first 12 months.

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