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Google Ads Attribution Models: All you need to know

Have you ever been stuck trying to figure out what campaigns and content is impacting your customers most?

These days everyone using the web is exposed to thousands of messages per day. And every day, thousands of businesses are pushing to be seen by those same people you hope to reach. So the money you spend has to be justified by its return, whether that is awareness, social shares or—our favourite thing—conversions.

So, how do you know you are spending your money wisely? 

We’re here to tell you that there is a way to measure the effectiveness of your channels and campaign performance along the customer journey, and gain a full picture of the ad interactions your potential clients have on their path to conversion.

Your customer data is not only there to give you insights but to help you use them to your advantage. This is where Attribution Modeling comes in!

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What is Attribution Modeling?

Attribution (or Attribution Modeling) is a way for marketers to evaluate the marketing touchpoints a consumer encounters on their path to purchase. It decides how credit is assigned for conversions made in every step of the customer journey. The goal here will be to determine which channels had the greatest impact on the decision to convert or take the next desired action.

It’s essential to understand how people convert on your website by measuring the touchpoints they have before conversions happen. Attribution Modeling allows you to:

  • Understand your audiences
  • Find opportunities to influence customers earlier in your sales funnel
  • Improve your budget allocation and make accurate spending decisions
  • Improve your bidding, optimizing it according to the insights you get of their performance
  • Increase your marketing investment return
  • Set factors based on your goals, and work with more than one model

Attribution models in Google Ads you can take advantage of:

First Click: Here the first-clicked ad and corresponding keyword receive all credit for the conversion.

Pro: It helps you determine the best keywords at the top of the funnel, allowing you to invest more budget increasing new customers’ rate.

Con: it could give too much value to awareness touchpoints, ignoring other places that the customer could hit before converting. Also, non-branded terms might not be so helpful.

Last Click: Same principle, the last-clicked ad and corresponding keyword receive all credit for the conversion.

Pro: It is the easiest to understand and apply. It lets you discover the best keywords at the bottom of the funnel. You can use it to determine which AdWords keywords are driving the most revenue.

Con: The idea that a customer converts in one click is idealistic. This model presumes you understand how the other channels/keywords contribute to the conversion.

Last Non-Direct Click: Here 100% of the credit is still assigned to just one interaction but, it takes the one that happens right before the conversion, pointing to the channel that led to conversion.

Pro: It´s a little more insightful because it lets you discover conversions triggers behind direct interactions.

Con: It gives you a limited vision of all the customer journey

Linear: Credit is distributed equally among all touchpoints that the person has made along the path.

Pro: It gives you a complete view of every single touchpoint in the customer journey. You can find which channels are making the conversions, focusing on these to increase their budget and optimize them.

Con: Not all touchpoints deserve spending time and money; at first you could be focusing on keywords or channels that aren’t as important as others.

Position-Based: Here first- and last-clicked ads and corresponding keywords receive 40% of the credit each, and the last 20% is distributed between the rest of the clicks on the path.

Pro: This is a good model to see which channels are driving audiences and which are best converting them. While it shows you all keywords on the path, you can see the ones that are worth investing in (or not).

Con: This channel undervalues terms between first and last touchpoints, which could have generated a bigger impact on the led to conversion.

Time Decay: The closer in time a touchpoint is to the conversion, the more credit it receives. This means the first touchpoints on the path receive less credit than the last ones.

Pro: This model lets you discover which channels are at the top of the funnel and which are more likely to covert with regularity. Once you know that, you can increase your budget according to your goals (traffic/lead generation or customer acquisition).

Con: You could be getting into brand terms´ inflation as this model still over values the last click.

Data-driven: This gives all touchpoints exactly the credit it deserves—no more, no less—and this is based on current data of every interaction (it also builds based on previous data). You can be 100% sure where you can invest your money and where not.

Pro: Theoretically, it is the best model to work on because it doesn’t have the other models’ cons and solves most of their underlying biases. This means you can be much more certain about where you should be investing your money and forego ineffective channels.

Con: It is not available for anyone, just for accounts with between 15,000 clicks and 600 conversions over 30 days. That´s not an easy number to get if you are a smaller advertiser/business, but if you have the opportunity to try this model, that would be a huge asset.

Custom Model: If your clients or business have a long customer journey and plenty of data, this could be a good model to check out. You can build your model with your specialized business needs; this means a pretty clear view of where your sales come from. People usually combine other models’ features instead of creating something from scratch.

Pro: It gives you precise control over how you spread out the conversion´s credit.

Con: It requires a lot of data and could be hard to develop at first as it is resource-intensive. Many people prefer pre-built attribution models because they’re easier to implement and use.

Which Attribution Model is best for my business?

Many marketers tend to either not implement a model or choose the easiest like first click, last click, linear, etc. but sometimes it’s not the right model.

If you wonder which model is best for your business or your clients, the answer is sadly simple: it depends!.

Because every business is different, every customer is different and the buying journey is different. We know, not the answer anyone wants to hear.

But if you look at the business and the customer’s buying journey, you may be able to determine which model (or models) makes the most sense.

What you need to prepare your Google Analytics account for Attribution

First step: Define your goals (destination, duration, pages/screens per session, event).

Second step: Set up your e-commerce data.
Quick guide: Go to “Ecommerce Settings” section > then turn “Enable Ecommerce” and “Enable Enhanced Ecommerce Reporting” options.

Third step: Customize how your channels are viewed within Google Analytics (channel grouping lets you select it in the reports section. Review info with a new perspective by applying it to historical data, and change reports´ data display).
Quick guide: “Channel Settings” > “Channel Grouping.”

How to change attribution models in your Google Analytics account — for an existing conversion action

First, log in to your Google Ads account, click the tool icon (upper in the right corner), then select “Conversions” (under “Measurement” option).

There, you will see a table. Select the conversion action you want to edit (by clicking the name); this shows you all the existing information for that conversion action and a setting screen.

Click “Edit settings” (on the lower right), then click “Attribution model” and select the attribution model you want to switch to from the drop-down menu.

After that, click “Save” and then click “Done.”

Considerations:

After you change your attribution model, there may be some changes in the reporting in your “Campaigns” tab. Changes such as:

  • Fractional Credit: You will start to see decimals in “Conversions” and “All conv.” columns when you change your model to “non-last-click.”
  • In multi-touch models, time-lag associated with your “Campaigns” reporting may increase because conversion is reported according to the ads interactions date. This implies that after you change your attribution model, you may see a temporary decrease in conversions in the next few.

Tip: You can take a look at “Avg. days to conversion” in the “Path metrics” attribution report. Google recommends that you wait to evaluate performance until the average number of days to conversion has passed.

  • Credit shifts across the various campaigns, networks, ad groups, and keywords that use this conversion action.

The change in conversion attribution may result in over- or under-bidding unless you update your bids and targets for each conversion (included in the “Conversions” column). This is particularly important if you’re using Target CPA or Target ROAS bid strategies. If your bidding is manual, performance will not be impacted (until you begin to optimize based on the new data).

To see how changing to other models affects your understanding of each channel’s effectiveness, you can use the model comparison tool. Here is a quick guide:

Log in to your Google Ads account > click “Conversions” > then “Multi-Channel Funnels” > then “Attribution” > and “Model Comparison.”

Bonus: Google Ads attribution models now support YouTube and Display

Charles Huyi, product manager for Google Ads, wrote recently in an announcement, “We’ve upgraded all Google Ads non-last click models, including data-driven attribution, to support YouTube and Display ads. In addition to clicks, the data-driven attribution model also measures engaged views from YouTube”.

The attribution models were created to improve your Google Ads campaigns, helping you understand how all your efforts are performing, putting you in a better position to make decisions such as which formats or keywords are working, which ones are not. Now you can optimize and invest in what gives you the results you aim for.

To see YouTube and Google Display Network ad engagements in the reports just click the “Dimension” drop-down menu and select the “Networks” option.

This update brings a more complete view of the puzzle of the customer journey for every business, and provides a clear account of how these two channels (and all in general) contribute to the customer journey and conversions.

Data-Driven is the new attribution model by default

Google is setting Data-Driven attribution as the default model starting this month (October 2021), and it has plans to extend this to all Google Ads accounts by early next year.

This new change means that Google says goodbye to the last default, the Last Click model. Also, they say they will remove the data requirements and add support for additional types of conversions, so all advertisers can take better advantage of this more precise model.

What benefits will you have with Data-Driven?

  • You will see more accurate, calibrated and personalized data
  • It will allows you to better optimize your bidding
  • You won’t have guesswork
  • It will supports Search, Shopping, Display and YouTube ads
  • It will include in-app and offline conversions

*All five rule-based attribution models will still be available. You can change the attribution model anytime you want by following the instructions mentioned above.

Last words about Attribution Models:

The truth is that there aren’t any last words.

Business needs are changing all the time—it’s not only about reacting when necessary, but you also need to anticipate what might be in front of you, waiting to give you huge returns on your investment, if you know to watch for it and know where to look.

Let measurement results lead the way. Audiences today are too complex to rely on one sole measurement solution. Try to keep this in mind as you look at attribution models.

As you get better at using them, you’ll soon see the power they offer—and the amount of control you will have on your own customer journey. 

Good luck!

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