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Using Data-Driven Attribution For Better Results

In our continuing series of articles on Conversion Attribution in Google Ads – and in a supplementary post to our one on The Benefits of Attribution Model Reporting – we now take a look at the benefits of using data-driven attribution.

Google recently made data-driven attribution the default attribution model as the digital marketing landscape evolves and the need for ‘nimble and durable measurement’ grows. Data-driven attribution uses a Google Ads account’s historical data to determine how people interact with the various ads and decide to become your customers. Currently data-driven attribution is the most-used attribution model for conversions using automated bidding in Google Ads.

As advertisers find more success with smarter attribution Google wants to help them feel confident making the switch to the data-driven from other models. It therefore provides the ability to see how data-driven attribution will affect the account’s performance before making the switch, and it’s possible to get insights for Discovery campaigns.

Google Ads uses six attribution methods:

  • Last Click Attribution
  • First Click Attribution
  • Linear Attribution
  • Time decay Attribution
  • Position Based Attribution
  • Data-Driven Attribution

When considering which attribution is right for Google Ads campaigns, you should examine the uniqueness of your business, your customers’ buying habits, your goals and the attribution model that makes most sense in that case.

Think about how you want to assign credit and how much dedication you have to understand your user journey. To understand and compare conversion options available in your Google Ads account, see the Google Attribution Tool by getting there through these steps:

Step 1: Go to your Google Ads main menu and select “Tools and Settings”
Step 2: Under “Measurement” select “Attribution”

Step 3: On the left-hand side, select “Model Comparison”

On this tab, you can compare how the different attribution models’ conversion data vary on a campaign (or any other dimension). It’s also possible filter down to the specific conversion action (if the account uses more than one conversion action) for the various attribution models.

When comparing models, look for a change in conversions with different attribution models. Also, observe how the cost/conversion metric is affected after changing the attribution models. The data variance is expected as every attribution model credits ad interactions differently.

Google states that advertisers who switch to data-driven attribution from another attribution model typically see a 6% average increase in conversions as machine learning algorithms assign fractional credit to customer touch points which may have previously been undervalued. Smart Bidding, particularly the Maximize Conversions bidding strategy, can then react to these opportunities, resulting in performance gains.

Data-driven attribution is Google’s recommended attribution tool and a foundational practice for automated campaign success so it brought one of attribution’s key reports – Conversion Paths – to the Overview page so that its easy to see how the ads work together to lead users to convert.

Google’s also making it easier to see the effects of switching to a data-driven attribution model before doing it, so it’s soon launching a simulation tool to eligible advertisers that will allow them to see how automated bidding would have reacted to data-driven attribution over the last 7 days. This will help to understand the effects of data-driven attribution on the account before making the switch.

Lastly, data-driven attribution is being brought to more advertisers and more ad types. Historically, data-driven attribution has supported Search, Shopping, Display and YouTube ads, but it’s being expanded to app conversions and will begin to support Discovery formats (including those in Performance Max) next year.

Google says they are committed to helping advertisers to more accurately measure campaign goals and provide the tools needed to succeed. With continued advancements in machine learning and automation, advertisers can feel more confident using data-driven attribution to deliver positive marketing results.

If you want to know more about how data-driven attribution can help to bring more conversions to your business please get in touch.