Data Driven Attribution Model in Google Ads (Adwords)
Customers do not always click on your Google ads 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 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 Google ad and then making a purchase.
Get my best selling books on Attribution Modelling
- Learn to implement attribution modelling in your organisation
- Understand the customer purchase journey across devices
- Determine the most effective marketing channels for investment
Click book covers to find out more
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 Ads use the ‘last ad click’ attribution model.
According to this attribution model, the last 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 Ads reports.
As long as you keep using last ad click attribution model, you will remain busy optimizing your Ad campaigns for last ad click and keep losing money.
Get the 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 Google Ads?
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 Ads is ‘Data Driven Attribution Model’.
This attribution model use conversion data from your Google Ads 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 Ads attribution modelling, a conversion path is just made of Google 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 Google Ads conversion path:
generic impression > generic click > generic impression > brand click => Conversion
There are several types of Google Ads conversion paths:
- Click Paths
- Transition Click Paths
- Impression Paths
- Transition Impression Paths
I have explained all of these conversion paths in great detail in this article: Understanding Conversion Paths in Google Ads (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 on the basis of 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 Ads:
- Last Click
- First Click
- Linear
- Time Decay
- 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 Google Ads 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 Ads account.
As such, a traditional MMM model is not suitable for carrying out digital marketing mix modelling aka attribution modelling.
Get my best selling books on Attribution Modelling
- Learn to implement attribution modelling in your organisation
- Understand the customer purchase journey across devices
- Determine the most effective marketing channels for investment
Click book covers to find out more
Other Articles Related to Attribution Modelling in Google Ads
- Guide to Attribution Modelling in Google Ads (Google Adwords)
- Which Attribution Model to use in Google Ads (Google Adwords)?
- Cross device attribution reports in Google Ads (Google AdWords)
- How to change Attribution Model in Google Ads (Google Adwords)
- Setting up Data Driven Attribution Model in Google Ads (Google Adwords)
- Store visit conversion tracking in Google Ads (Google AdWords)
- Understanding the Analytics behind Google Ads (Google Adwords)
- Cross Account Conversion Tracking in Google Ads (Google Adwords)
- Understanding View-Through conversions In Google Ads (Google Adwords)
- Assisted Conversions Report in Google Ads (Google Adwords)
- Understanding Conversion Paths in Google Ads (Google Adwords)
- Understanding Search Attribution Reports in Google Ads (Adwords)
- How to test Attribution Model in Google Ads (Adwords)
Do you know the difference between Web Analytics and Google Analytics?
99.99% of course creators themselves don’t know the difference between Web analytics, Google Analytics (GA) and Google Tag Manager (GTM).
So they are teaching GA and GTM in the name of teaching Web analytics.
They just copy each other. Monkey see, monkey do.
But Web analytics is not about GA, GTM.
It is about analyzing and interpreting data, setting up goals, strategies and KPIs.
It’s about creating strategic roadmap for your business.
Web Analytics is the core skill. Google Analytics is just a tool used to implement ‘Web Analytics’.
You can also implement ‘Web analytics’ via other tools like ‘adobe analytics’, ‘kissmetrics’ etc.
Using Google Analytics without the good understanding of ‘Web analytics’ is like driving around in a car, in a big city without understanding the traffic rules and road signs.
You are either likely to end up somewhere other than your destination or you get involved in an accident.
You learn data analysis and interpretation from Web analytics and not from Google Analytics.
The direction in which your analysis will move, will determine the direction in which your marketing campaigns and eventually your company will move to get the highest possible return on investment.
You get that direction from ‘Web analytics’ and not from ‘Google Analytics’.
You learn to set up KPIs, strategies and measurement framework for your business from ‘Web analytics’ and not from ‘Google Analytics’.
So if you are taking a course only on 'Google Analytics’, you are learning to use one of the tools of ‘Web analytics’. You are not learning the ‘Web analytics’ itself.
Since any person can learn to use Google Analytics in couple of weeks, you do no get any competitive advantage in the marketplace just by knowing GA.
You need to know lot more than GA in order to work in Web analytics and marketing field.
So what I have done, if you are interested, is I have put together a completely free training that will teach you exactly how I have been able to leverage web/digital analytics to generate floods of news sales and customers and how you can literally copy what I have done to get similar results.
Here what You'll Learn On This FREE Web Class!
1) Why digital analytics is the key to online business success
2) The number 1 reason why most marketers are not able to scale their advertising and maximize sales.
3) Why Google and Facebook ads don’t work for most businesses & how to make them work.
4) Why you won’t get any competitive advantage in the marketplace just by knowing Google Analytics.
5) The number 1 reason why conversion optimization is not working for your business.
6) How to advertise on any marketing platform for FREE with an unlimited budget.
7) How to learn and master digital analytics and conversion optimization in record time.
My best selling books on Digital Analytics and Conversion Optimization
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.
Attribution Modelling in Google Ads and Facebook
This book has been written to help you implement attribution modelling in Google Ads (Google AdWords) and Facebook. It will teach you, how to leverage the knowledge of attribution modelling in order to understand the customer purchasing journey and determine the most effective marketing channels for investment.
Himanshu Sharma
Digital Marketing Consultant and Founder of Optimizesmart.com
Customers do not always click on your Google ads 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 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 Google ad and then making a purchase.
Get my best selling books on Attribution Modelling
- Learn to implement attribution modelling in your organisation
- Understand the customer purchase journey across devices
- Determine the most effective marketing channels for investment
Click book covers to find out more
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 Ads use the ‘last ad click’ attribution model.
According to this attribution model, the last 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 Ads reports.
As long as you keep using last ad click attribution model, you will remain busy optimizing your Ad campaigns for last ad click and keep losing money.
Get the 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 Google Ads?
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 Ads is ‘Data Driven Attribution Model’.
This attribution model use conversion data from your Google Ads 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 Ads attribution modelling, a conversion path is just made of Google 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 Google Ads conversion path:
generic impression > generic click > generic impression > brand click => Conversion
There are several types of Google Ads conversion paths:
- Click Paths
- Transition Click Paths
- Impression Paths
- Transition Impression Paths
I have explained all of these conversion paths in great detail in this article: Understanding Conversion Paths in Google Ads (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 on the basis of 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 Ads:
- Last Click
- First Click
- Linear
- Time Decay
- 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 Google Ads 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 Ads account.
As such, a traditional MMM model is not suitable for carrying out digital marketing mix modelling aka attribution modelling.
Get my best selling books on Attribution Modelling
- Learn to implement attribution modelling in your organisation
- Understand the customer purchase journey across devices
- Determine the most effective marketing channels for investment
Click book covers to find out more
Other Articles Related to Attribution Modelling in Google Ads
- Guide to Attribution Modelling in Google Ads (Google Adwords)
- Which Attribution Model to use in Google Ads (Google Adwords)?
- Cross device attribution reports in Google Ads (Google AdWords)
- How to change Attribution Model in Google Ads (Google Adwords)
- Setting up Data Driven Attribution Model in Google Ads (Google Adwords)
- Store visit conversion tracking in Google Ads (Google AdWords)
- Understanding the Analytics behind Google Ads (Google Adwords)
- Cross Account Conversion Tracking in Google Ads (Google Adwords)
- Understanding View-Through conversions In Google Ads (Google Adwords)
- Assisted Conversions Report in Google Ads (Google Adwords)
- Understanding Conversion Paths in Google Ads (Google Adwords)
- Understanding Search Attribution Reports in Google Ads (Adwords)
- How to test Attribution Model in Google Ads (Adwords)
Do you know the difference between Web Analytics and Google Analytics?
99.99% of course creators themselves don’t know the difference between Web analytics, Google Analytics (GA) and Google Tag Manager (GTM).So they are teaching GA and GTM in the name of teaching Web analytics.
They just copy each other. Monkey see, monkey do.
But Web analytics is not about GA, GTM.
It is about analyzing and interpreting data, setting up goals, strategies and KPIs.
It’s about creating strategic roadmap for your business.
Web Analytics is the core skill. Google Analytics is just a tool used to implement ‘Web Analytics’.You can also implement ‘Web analytics’ via other tools like ‘adobe analytics’, ‘kissmetrics’ etc.
Using Google Analytics without the good understanding of ‘Web analytics’ is like driving around in a car, in a big city without understanding the traffic rules and road signs.
You are either likely to end up somewhere other than your destination or you get involved in an accident.
You learn data analysis and interpretation from Web analytics and not from Google Analytics.The direction in which your analysis will move, will determine the direction in which your marketing campaigns and eventually your company will move to get the highest possible return on investment.
You get that direction from ‘Web analytics’ and not from ‘Google Analytics’.
You learn to set up KPIs, strategies and measurement framework for your business from ‘Web analytics’ and not from ‘Google Analytics’.So if you are taking a course only on 'Google Analytics’, you are learning to use one of the tools of ‘Web analytics’. You are not learning the ‘Web analytics’ itself.
Since any person can learn to use Google Analytics in couple of weeks, you do no get any competitive advantage in the marketplace just by knowing GA.
You need to know lot more than GA in order to work in Web analytics and marketing field.
So what I have done, if you are interested, is I have put together a completely free training that will teach you exactly how I have been able to leverage web/digital analytics to generate floods of news sales and customers and how you can literally copy what I have done to get similar results.
Here what You'll Learn On This FREE Web Class!
1) Why digital analytics is the key to online business success
2) The number 1 reason why most marketers are not able to scale their advertising and maximize sales.
3) Why Google and Facebook ads don’t work for most businesses & how to make them work.
4) Why you won’t get any competitive advantage in the marketplace just by knowing Google Analytics.
5) The number 1 reason why conversion optimization is not working for your business.
6) How to advertise on any marketing platform for FREE with an unlimited budget.
7) How to learn and master digital analytics and conversion optimization in record time.
My best selling books on Digital Analytics and Conversion Optimization
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.
Attribution Modelling in Google Ads and Facebook
This book has been written to help you implement attribution modelling in Google Ads (Google AdWords) and Facebook. It will teach you, how to leverage the knowledge of attribution modelling in order to understand the customer purchasing journey and determine the most effective marketing channels for investment.
Himanshu Sharma
Digital Marketing Consultant and Founder of Optimizesmart.com