Touch Point Analysis in Google Analytics Attribution Modelling
Table of Contents
This article is related to attribution modelling in Google Analytics.
If you are brand new to attribution modelling then I would suggest to read this article first: Beginners Guide to Google Analytics Attribution Modeling.
Introduction to Interaction (Touch Point)
Interaction is an exposure to a marketing channel.
Interaction is also known as ‘touch or touch point’.
For example in the chart below, a visitor is exposed to 6 different marketing channels before he made a purchase:
Each exposure is known by the name of ‘interaction’ in multi-channel funnel reports.
Note: Google Analytics can record up to 5000 interactions per conversion path.
Types of Interactions
There are several types of interactions.
For example:
#1 Interactions based on position – First interaction, middle interaction and last interaction.
These interactions are also known by the name: first touch, middle touch and last touch which are more commonly used in the web analytics world.
#2 Interactions based on type – click interactions (which is basically clicking on ads), impression interactions (which is basically viewing an ad), direct visit interactions etc.
#3 Interactions based on campaign or traffic source type – keyword interactions, campaign interactions, facebook interactions etc.
Any interaction other than the last interaction is called the assist interaction.
Any interaction other than the first and last interaction is called the middle interaction.
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Types of Interaction Analysis
In Google Analytics you can do two types of interaction analysis:
- Assisting Interaction Analysis
- First Interaction Analysis
As the name suggest, the ‘Assisting Interaction analysis’ is the analysis of assist interactions (any interaction other than the last one) and the ‘First Interaction Analysis’ is the analysis of the first interactions.
You can do such type of analysis in the ‘Assisted Conversions’ report (under Multi Channel Funnels)
Interaction Types for GDN Ads
If you have enabled GDN impression reporting, not only you will see the ‘Interaction Type’ drop down menu in your multi-channel funnel reports but you will also see a new set of interactions types in the ‘Top Conversion Paths’ report:
Following are the new interactions (touch points) for GDN (Google display network) ads:
#1 ‘Impression’ Interactions/Touch Points – it refers to unclicked non-text display ad impressions
#2 ‘Click’ Interactions/Touch Points – it refers to non-text display ad clicks
#3 ‘Direct’ Interactions/Touch Points – it refers to unclicked non-text display ad impressions which resulted in direct conversions on your website.
#4 ‘Rich media’ Interactions/Touch Points – it refers to following types of interactions:
- Click on a video ad: play, pause and resume button.
- Turning a video ad to full screen
- Expanding an ad
To learn more about these interactions types, read this article: View-through conversion tracking in Google Analytics
Not All Touch Points Are Equally Valuable
The exposure to a marketing channel during the path to conversion is known as interaction, touch or touch point.
So if you are exposed to one marketing channel in your path to conversion then your conversion path includes only one touch point.
Similarly, if you are exposed to 4 marketing channels in your path to conversion then your conversion path will include 4 touch points.
Now consider, I follow this conversion path:
Here I am exposed to 7 different acquisition channels before I made a purchase.
Since each of these exposure is considered as a touch point, there are 7 different touch points in my conversion path.
Now let us see how credit for the conversion is distributed to different touch points under different attribution models:
In case of first touch attribution model 100% credit for conversion is attributed to the first touch.
So according to first touch model, my reading of the blog post gets all the credit for conversion.
But this is not true.
As you can see 6 other acquisition channels have also played an important role in my path to conversion.
In case of last touch attribution model 100% credit for conversion is attributed to the last touch.
So according to last touch model, direct traffic gets all the credit for conversions.
Again this is simply not the case as there are 6 more channels in play.
In case of Linear attribution model all touch points get equal credit for conversion.
So according to linear model, all 7 touch points are equally important in my path to purchase.
But this is also not true.
I read product reviews and went to product comparison website before making a purchase.
These two touches were more valuable to me than the exposure to the blog post, display ad, PPC ad and organic search listing as they played a very important role in my purchase decision.
Had I not been satisfied with the product review or pricing, I wouldn’t have made the purchase in the first place.
In case of time decay model the touch points which are closest in the time to conversions get more credit.
So according to time decay model, my exposure to organic search result and visiting the website directly should get more credit than to my exposure to product reviews and pricing.
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
Again such type of credit distribution is not accurate as had I not been satisfied with the product review or pricing, I wouldn’t have made the purchase in the first place.
The time decay model is the modified last touch attribution model.
Though it is crappy but less crappy than the last touch and other GA models.
One issue worth pointing out about giving more credit to last touches/interactions:
Last interactions act as a last point of contact prior to a purchase.
By the time a customer experience last touches to marketing channel(s), a purchase decision has already been made.
So it doesn’t really matter which channel closed the sale when it comes to allocating budget.
In case of Last Non Direct click attribution model 100% credit for conversion is attributed to the last non-direct click.
So according to this model, organic search gets all the credit for conversion.
So this model also give incorrect picture of the conversion path.
In case of Last Adwords Click attribution model 100% credit for conversion is attributed to the last Adwords click.
So according to this model, paid search result gets all the credit for conversion.
But this is also not a true representation of my buying behavior.
In case of Proportional Multi touch attribution model the credit is distributed to touches in proportion to their contribution in the conversion.
The acquisition channel which assists the most gets the maximum credit for conversion and maximum resources are allocated to it regardless of it being the first touch, last touch or middle touch.
All other touches would get credit in proportion to their contribution in the conversion path.
So according to this model, exposure to product review and product comparison websites get more credit for conversion than all other touch points as they played key role in the decision making process and my purchase journey.
Note: Proportional multi touch attribution model is my model and GA does not directly support it. But it indirectly support it through data driven attribution model (only available to GA premium customers at present).
The Concept of Missing Touch Points in Conversion Paths
Google Analytics provide best attribution modelling capabilities in the world but it has it own drawbacks.
You need to be aware of following limitations before you interpret GA multi-channel funnel and attribution reports:
#1 Google Analytics and Adwords attribution modelling is based on only ‘known’ touch points
#2 Both Google Analytics and Google Adwords, record and report attribution for only online touch points.
#3 Both Google Analytics and Google Adwords, do not record and report attribution for ‘all’ digital marketing channels
#4 Both Google Analytics and Google Adwords, do not record and report attribution across devices and browsers
#5 Adwords conversion paths in Google Analytics do not include impression interactions (unless you use GA premium)
#6 Filtered views omit certain touch points in conversion paths
If you wish to minimize the number of missing touch points in your conversion path, you need to integrate as much data as possible from different data sources.
To learn more about the concept of missing touch points in a conversion path, read this article: Understanding Missing Touch Points in Attribution Modelling
Other articles on Attribution Modelling in Google Analytics
- Touch Point Analysis in Google Analytics Attribution Modelling
- 8 Google Analytics Conversions Segments You Must Use
- Default and Custom Attribution Models in Google Analytics
- Attribution Model Comparison Tool in Google Analytics
- Which Attribution Model to use in Google Analytics?
- How to create Custom Attribution Model in Google Analytics
- How to do ROI Analysis in Google Analytics
- Google Analytics Attribution Modelling – Complete Guide
- Guide to Data Driven Attribution Model in Google Analytics
- Conversion Credit distribution for Attribution Models in Google Analytics
- You are doing Google Analytics all wrong. Here is why
- Marketing Mix Modelling or Attribution Modelling. Which one is for you?
- Introduction to Nonline Analytics – True Multi Channel Analytics
- How to set up Data driven attribution model in Google Analytics
- How to valuate Display Advertising through Attribution Modelling
- Understanding Shopping Carts for Analytics and Conversion Optimization
- View-through conversion tracking in Google Analytics
- Understanding Missing Touch Points in Attribution Modelling
- Guide to Offline Conversion Tracking in Google Analytics
- How to explain attribution modelling to your clients
- 6 Keys to Digital Success in Attribution Modelling
- How to use ZMOT to increase Conversions and Sales exponentially
- How to Measure and Improve the Quality of SEO Traffic through Google Analytics
- How to analyse and report the true value of your SEO Campaign
- How to allocate Budgets in Multi Channel Marketing
- What You Should Know about Historical Data in Web Analytics
- Google Analytics Not Provided Keywords and how to unlock and analyze them
- Selecting the Best Attribution Model for Inbound Marketing
- Introduction to TV attribution in Google Analytics Attribution 360
- Cross Device Reports in Google Analytics via Google Signals
- Data-Driven Attribution Model Explorer in Google Analytics
- What is Attribution Modelling and why it is the ‘key’ to online business success?
- How Does Attribution Work?
- How is Attribution Modelling helpful for e-commerce and non-e-commerce websites?
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Table of Contents
This article is related to attribution modelling in Google Analytics.
If you are brand new to attribution modelling then I would suggest to read this article first: Beginners Guide to Google Analytics Attribution Modeling.
Introduction to Interaction (Touch Point)
Interaction is an exposure to a marketing channel.
Interaction is also known as ‘touch or touch point’.
For example in the chart below, a visitor is exposed to 6 different marketing channels before he made a purchase:
Each exposure is known by the name of ‘interaction’ in multi-channel funnel reports.
Note: Google Analytics can record up to 5000 interactions per conversion path.
Types of Interactions
There are several types of interactions.
For example:
#1 Interactions based on position – First interaction, middle interaction and last interaction.
These interactions are also known by the name: first touch, middle touch and last touch which are more commonly used in the web analytics world.
#2 Interactions based on type – click interactions (which is basically clicking on ads), impression interactions (which is basically viewing an ad), direct visit interactions etc.
#3 Interactions based on campaign or traffic source type – keyword interactions, campaign interactions, facebook interactions etc.
Any interaction other than the last interaction is called the assist interaction.
Any interaction other than the first and last interaction is called the middle interaction.
Get the Free E-Book (52 Pages)
Types of Interaction Analysis
In Google Analytics you can do two types of interaction analysis:
- Assisting Interaction Analysis
- First Interaction Analysis
As the name suggest, the ‘Assisting Interaction analysis’ is the analysis of assist interactions (any interaction other than the last one) and the ‘First Interaction Analysis’ is the analysis of the first interactions.
You can do such type of analysis in the ‘Assisted Conversions’ report (under Multi Channel Funnels)
Interaction Types for GDN Ads
If you have enabled GDN impression reporting, not only you will see the ‘Interaction Type’ drop down menu in your multi-channel funnel reports but you will also see a new set of interactions types in the ‘Top Conversion Paths’ report:
Following are the new interactions (touch points) for GDN (Google display network) ads:
#1 ‘Impression’ Interactions/Touch Points – it refers to unclicked non-text display ad impressions
#2 ‘Click’ Interactions/Touch Points – it refers to non-text display ad clicks
#3 ‘Direct’ Interactions/Touch Points – it refers to unclicked non-text display ad impressions which resulted in direct conversions on your website.
#4 ‘Rich media’ Interactions/Touch Points – it refers to following types of interactions:
- Click on a video ad: play, pause and resume button.
- Turning a video ad to full screen
- Expanding an ad
To learn more about these interactions types, read this article: View-through conversion tracking in Google Analytics
Not All Touch Points Are Equally Valuable
The exposure to a marketing channel during the path to conversion is known as interaction, touch or touch point.
So if you are exposed to one marketing channel in your path to conversion then your conversion path includes only one touch point.
Similarly, if you are exposed to 4 marketing channels in your path to conversion then your conversion path will include 4 touch points.
Now consider, I follow this conversion path:
Here I am exposed to 7 different acquisition channels before I made a purchase.
Since each of these exposure is considered as a touch point, there are 7 different touch points in my conversion path.
Now let us see how credit for the conversion is distributed to different touch points under different attribution models:
In case of first touch attribution model 100% credit for conversion is attributed to the first touch.
So according to first touch model, my reading of the blog post gets all the credit for conversion.
But this is not true.
As you can see 6 other acquisition channels have also played an important role in my path to conversion.
In case of last touch attribution model 100% credit for conversion is attributed to the last touch.
So according to last touch model, direct traffic gets all the credit for conversions.
Again this is simply not the case as there are 6 more channels in play.
In case of Linear attribution model all touch points get equal credit for conversion.
So according to linear model, all 7 touch points are equally important in my path to purchase.
But this is also not true.
I read product reviews and went to product comparison website before making a purchase.
These two touches were more valuable to me than the exposure to the blog post, display ad, PPC ad and organic search listing as they played a very important role in my purchase decision.
Had I not been satisfied with the product review or pricing, I wouldn’t have made the purchase in the first place.
In case of time decay model the touch points which are closest in the time to conversions get more credit.
So according to time decay model, my exposure to organic search result and visiting the website directly should get more credit than to my exposure to product reviews and pricing.
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
Again such type of credit distribution is not accurate as had I not been satisfied with the product review or pricing, I wouldn’t have made the purchase in the first place.
The time decay model is the modified last touch attribution model.
Though it is crappy but less crappy than the last touch and other GA models.
One issue worth pointing out about giving more credit to last touches/interactions:
Last interactions act as a last point of contact prior to a purchase.
By the time a customer experience last touches to marketing channel(s), a purchase decision has already been made.
So it doesn’t really matter which channel closed the sale when it comes to allocating budget.
In case of Last Non Direct click attribution model 100% credit for conversion is attributed to the last non-direct click.
So according to this model, organic search gets all the credit for conversion.
So this model also give incorrect picture of the conversion path.
In case of Last Adwords Click attribution model 100% credit for conversion is attributed to the last Adwords click.
So according to this model, paid search result gets all the credit for conversion.
But this is also not a true representation of my buying behavior.
In case of Proportional Multi touch attribution model the credit is distributed to touches in proportion to their contribution in the conversion.
The acquisition channel which assists the most gets the maximum credit for conversion and maximum resources are allocated to it regardless of it being the first touch, last touch or middle touch.
All other touches would get credit in proportion to their contribution in the conversion path.
So according to this model, exposure to product review and product comparison websites get more credit for conversion than all other touch points as they played key role in the decision making process and my purchase journey.
Note: Proportional multi touch attribution model is my model and GA does not directly support it. But it indirectly support it through data driven attribution model (only available to GA premium customers at present).
The Concept of Missing Touch Points in Conversion Paths
Google Analytics provide best attribution modelling capabilities in the world but it has it own drawbacks.
You need to be aware of following limitations before you interpret GA multi-channel funnel and attribution reports:
#1 Google Analytics and Adwords attribution modelling is based on only ‘known’ touch points
#2 Both Google Analytics and Google Adwords, record and report attribution for only online touch points.
#3 Both Google Analytics and Google Adwords, do not record and report attribution for ‘all’ digital marketing channels
#4 Both Google Analytics and Google Adwords, do not record and report attribution across devices and browsers
#5 Adwords conversion paths in Google Analytics do not include impression interactions (unless you use GA premium)
#6 Filtered views omit certain touch points in conversion paths
If you wish to minimize the number of missing touch points in your conversion path, you need to integrate as much data as possible from different data sources.
To learn more about the concept of missing touch points in a conversion path, read this article: Understanding Missing Touch Points in Attribution Modelling
Other articles on Attribution Modelling in Google Analytics
- Touch Point Analysis in Google Analytics Attribution Modelling
- 8 Google Analytics Conversions Segments You Must Use
- Default and Custom Attribution Models in Google Analytics
- Attribution Model Comparison Tool in Google Analytics
- Which Attribution Model to use in Google Analytics?
- How to create Custom Attribution Model in Google Analytics
- How to do ROI Analysis in Google Analytics
- Google Analytics Attribution Modelling – Complete Guide
- Guide to Data Driven Attribution Model in Google Analytics
- Conversion Credit distribution for Attribution Models in Google Analytics
- You are doing Google Analytics all wrong. Here is why
- Marketing Mix Modelling or Attribution Modelling. Which one is for you?
- Introduction to Nonline Analytics – True Multi Channel Analytics
- How to set up Data driven attribution model in Google Analytics
- How to valuate Display Advertising through Attribution Modelling
- Understanding Shopping Carts for Analytics and Conversion Optimization
- View-through conversion tracking in Google Analytics
- Understanding Missing Touch Points in Attribution Modelling
- Guide to Offline Conversion Tracking in Google Analytics
- How to explain attribution modelling to your clients
- 6 Keys to Digital Success in Attribution Modelling
- How to use ZMOT to increase Conversions and Sales exponentially
- How to Measure and Improve the Quality of SEO Traffic through Google Analytics
- How to analyse and report the true value of your SEO Campaign
- How to allocate Budgets in Multi Channel Marketing
- What You Should Know about Historical Data in Web Analytics
- Google Analytics Not Provided Keywords and how to unlock and analyze them
- Selecting the Best Attribution Model for Inbound Marketing
- Introduction to TV attribution in Google Analytics Attribution 360
- Cross Device Reports in Google Analytics via Google Signals
- Data-Driven Attribution Model Explorer in Google Analytics
- What is Attribution Modelling and why it is the ‘key’ to online business success?
- How Does Attribution Work?
- How is Attribution Modelling helpful for e-commerce and non-e-commerce websites?
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Himanshu Sharma
Certified web analyst and founder of OptimizeSmart.com
