Data Driven Attribution Model in Google Adwords

Customers do not always click on your Adwords ad and then make a purchase straightaway.

They generally start their purchase journey by doing multiple searches using generic search terms.

Then they refine their search queries as they get better understanding of what they are looking for.

Sometimes customers click on your Adword ads just to return to your website.

During their purchase journey, customers may see/click several of your ads via different devices/browsers and over the course of multiple different sessions, days or even weeks.

As such, customers purchase journey is not as easy, as clicking on an adwords ad and then making a purchase.

Different search terms, different ads and users experience on different devices can play an important role in shaping the purchase decision of your customer.

Then there are external factors like: weather, better price/deal offered by your competition, level and type of remarketing campaigns run by your competitors etc which can influence the purchase decision of a customer.

However such external factors are generally not taken into account by attribution models while calculating which ad interaction (ad click/ ad impression) should get more credit for conversions.

For the sake of simplicity, let us ignore these factors for now, from our attribution modelling.

By default, Google Adwords use the last ad click’ attribution model.

According to this attribution model, the last adwords ad click in a conversion path gets 100% credit for a conversion.

In other words, according to last click model, the last ad your customer clicked on, is solely responsible for generating a sale on your website.

But know you know that, this can not be true.

As long as you keep using last ad click attribution model, you will get inaccurate/incomplete insight from your Google Adwords reports.

As long as you keep using last ad click attribution model, you will remain busy optimizing your Adwords campaigns for last ad click and keep losing money.

Get the FREE E-Book (52 Pages)

So what is the solution?

Should you use ‘last click model’ or ‘last non direct click model’ or some other attribution model offered by Adwords?

As long as you use any rule based model (models which assign conversion credits based on some predefined rules) whether it is ‘first click’, ‘last click’, ‘time decay’ , ‘linear’ etc  you are more likely to assign conversion credits to wrong ad clicks / impression and loose money.

In order to determine the most effective ad campaigns, ad groups, ads or keywords for conversions, you need to move beyond ‘rule based models’ and use ‘algorithmic attribution models’.

The algorithmic attribution model offered by Google Adwords is ‘Data Driven Attribution Model’.

This attribution model use conversion data from your adwords account to determine:

  • How people searched for your business and then turned into customers.
  • How each campaign, ad group, ads and keywords actually contributed, across a conversion path.
  • Which campaigns, ad groups, ads and keywords have the most influence / greatest effect on your customers’ purchase decision.
  • Which campaigns, ad groups, ads and keywords have the biggest impact on your website conversions.
  • Which campaigns, ad groups, ads and keywords are likely to generate more sales.

It is important to note that, in the context of Google Adwords attribution modelling, a conversion path is just made of Google Adwords ad clicks and/or impressions.

The conversion path does not take the role of other marketing channels (like ‘organic search’, ‘social media’, ‘email’ etc) into account.

Following is an example of Adwords conversion path:

generic impression > generic click > generic impression > brand click => Conversion

There are several types of adwords conversion paths:

  1. Click Paths
  2. Transition Click Paths
  3. Impression Paths
  4. Transition Impression Paths

I have explained all of these conversion paths in great detail in this article: Beginners Guide to Attribution Modelling in Google Adwords

The data driven attribution model uses a predictive algorithm (algorithm used to predict the users’ probability of making a purchase or completing some other conversion) to assign or reassign conversion credit to various ‘ad interactions’ in a conversion path according to the most recent conversion data.

It is a conversion probability model.

It does not distribute conversion credit just based on ad interactions’ position.

In other words ‘data driven attribution model’ is not a rule/position based model.

Following are the examples of rule based attribution models available in Google Adwords:

  1. Last Click
  2. First Click
  3. Linear
  4. Time Decay
  5. Position-based

Data driven attribution model is used to identify the most influential ad interactions at a particular point in time.

The most influential ad interactions are the interactions / touchpoints which lead to conversions or maximum conversions.

In order to identify the most influential ‘ad interactions’ at a particular point in time, the data driven attribution model:

#1 Compare the ‘conversion paths’ of your website users to each other. These website users can be: customers, non-customers, prospects (who abandoned the shopping cart or checkout) or customers who completed more conversion than the others.  

#2 Add or remove touch points in conversion paths to determine higher conversion probability.

For example, consider the following two Adwords conversion paths:

Ad1 > Ad2 > Ad3     Conversion Probability 5%

Ad1 > Ad3    Conversion Probability 10%

Here the second conversion path has higher conversion probability.

What that means, if the Ad2 is not shown to users, there is a high probability of generating sales.

The data driven attribution model add or remove touchpoints algorithmically to assign/reassign conversion credit to various ad interactions and to show ad or ads combinations which have higher probability of generating sales or completing some other conversions.

Google recommends that you use an automated bidding strategy (like ‘target CPA’, ‘enhanced cost per click’) in order to benefit from a data driven attribution model. 

By default, data driven attribution model is not available in Google Adwords.

Web Analytics Training – Attribution Modelling in Google Analytics


Learn about the Google Analytics Usage Trends Tool

The Google Analytics usage trend is a new tool which is used to visualise trends in your Google Analytics data and to perform trend analysis.

Take your knowledge of Web Analytics to the next level. Checkout my web analytics training course.

Become a Web Analytics & Conversion Optimization PRO with my FIVE most popular FREE e-Books

Select the ebook you want:

E-Book #1: Best Excel Charts For Data Analysis And Reporting (40 Pages)

E-Book #2: Beginners Guide To Google Analytics Attribution Modelling (52 Pages)

E-Book #3: Beginners Guide To Google Tag Manager (72 Pages)

E-Book #4: Google Tag Manager Data Layers (62 Pages)

E-Book #5: Key Performance Indicator - KPI (32 Pages)

Take your Analytics knowledge to the next level. Checkout my Best Selling Books on Amazon

Maths and Stats for Web Analytics and Conversion Optimization
This expert guide will teach you how to leverage the knowledge of maths and statistics in order to accurately interpret data and take actions, which can quickly improve the bottom-line of your online business.

Master the Essentials of Email Marketing Analytics
This book focuses solely on the ‘analytics’ that power your email marketing optimization program and will help you dramatically reduce your cost per acquisition and increase marketing ROI by tracking the performance of the various KPIs and metrics used for email marketing.

Attribution Modelling in Google Analytics and Beyond
Attribution modelling is the process of determining the most effective marketing channels for investment. This book has been written to help you implement attribution modelling. It will teach you how to leverage the knowledge of attribution modelling in order to allocate marketing budget and understand buying behaviour.

Himanshu Sharma

Certified web analyst and founder of

My name is Himanshu Sharma and I help businesses find and fix their Google Analytics and conversion issues. If you have any questions or comments please contact me.

  • Over eleven years' experience in SEO, PPC and web analytics
  • Google Analytics certified
  • Google AdWords certified
  • Nominated for Digital Analytics Association Award for Excellence
  • Bachelors degree in Internet Science
  • Founder of and

I am also the author of three books:

error: Alert: Content is protected !!