How to valuate Display Advertising through Attribution Modelling
# How can my display advertising be valued from a different perspective?
# Is display advertising undervalued or overvalued, under last click and last non direct click attribution model?
# If I invest in display advertising, how much incrementality can display channel bring to my business bottomline?
# How can I make my display campaigns more effective?
# If I change my display ad spend, how it will effect my website conversions?
You can get answers to such questions by adjusting conversion credit for impressions, while creating an attribution model.
This articles 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.
Get the E-book (52 Pages)
Before you can adjust conversion credit for ‘impressions’, while creating an attribution model, you first need to set up view-through conversion tracking in Google Analytics.
Without view-through conversion tracking setup, you won’t get the option to adjust credit for ‘impression’ while creating a new attribution model in Google Analytics.
If you are brand new to view-through conversions then read this article first: Understanding view-through conversions in Google Adwords where I explained in great detail, what view through conversions are and when they are reported.
In order to valuate display advertising through attribution modelling, follow the steps below:
Step-1: Navigate to ‘Model Comparison Tool’ (under Conversions > Attribution):
Step-2: Click on ‘Select Model’ drop down menu:
Step-3: Set date range to the last 3 months or longer.
Step-4: Click on the link ‘create new custom model’:
Step-5: Give your new attribution model, a name and then select ‘Data Driven’ as baseline model:
# An attribution model is a set of rules which is used to determine, how credit for conversions should be attributed to different marketing channels.
# Baseline attribution models are the pre-built attribution models available in Google Analytics.
# Custom attribution models are user defined attribution models.
I selected ‘data driven’ attribution model as ‘baseline’ model because it analyse the data (related to organic search traffic, direct traffic, referral traffic, uploaded cost data etc) not only from my GA account but also from all those Google Accounts (like Doubleclick Campaign Manager, Google Adwords etc) which are linked to my GA account, in order to algorithmically generate a custom attribution model.
Also when I choose data driven attribution model, I do not have to worry about how to set up the lookback window option to get optimum results from my analysis.
Note: lookback window option has no effect on attribution when you use ‘data driven’ attribution model as ‘baseline’ model.
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.
Step-6: Switch on the toggle button next to ‘Adjust credit for impressions’:
Step-7: Click on the ‘Advanced option…’ link:
Step-8: Adjust credit for impressions like the one below:
Here I have set my attribution model, to give display ad impressions, two times more conversion credit than the other interactions in the conversion path, provided the display ad impressions occurs within 12 hours before a visit is recorded for my website which results in a conversion.
In other words, I have set my attribution model, to give display ad impressions, two times more conversion credit than the other interactions in the conversion path, provided a user completes a goal on my website within 12 hours after viewing (but not clicking) one of my display ads.
That means I can decide which ad exposure should be valued more, based on my understanding of the context/business/marketing.
Bear in mind that,
More an ad impression occurs closer in time to conversion, the more effective it can be considered, in driving conversion.
In other words, an ad impression which resulted in sales within 6 hours, can be considered more effective than an ad impression which resulted in sales after 1 day.
Similarly, an ad impression which resulted in sales within 1 day, can be considered more effective than an ad impression which resulted in sales after 7 days.
In a world of multi-channel, multi-device marketing, there are many touch points which can influence the buying behavior of a customer, in a short span of time.
This makes it quite difficult to effectively assign credit for conversions to a comparatively weak touch point, such as ‘impression’.
So I would suggest to keep the lookback window (not to be confused with the lookback window option in the custom attribution model) as short as possible.
Step-9: Click on ‘Save and apply’ button. This will create a new attribution model which will take ad impressions in the conversion paths, into account and help in the valuation of display advertising:
Step-10: Compare the ‘Last Interaction’ model with ‘Display Advertising Model’ and ‘Last Non-Direct Click’ model:
Step-11: Select ‘Conversions and Value’ from the drop down menu located in the middle of your ‘model comparison tool’ report:
Step-12: Now look at the column named ‘% change in conversion (from last interaction)’ for ‘display’:
Form this report we can conclude that, the % of change in conversion for ‘Display’ from last interaction model to ‘Display Advertising Model’ is 398.39%.
What that means, if you use ‘Display Advertising Model’ (instead of last interaction model) to distribute credit for conversions to Display advertising then the ‘Display Advertising’ deserves 398.39% more credit for conversions.
It also means that ‘Display’ is undervalued by 398.39% under last click attribution model (which is used in GA multi channel funnel reports by default), when this model is compared with ‘Display Advertising Model’.
The upward green arrow next to 398.39% indicates positive change in conversions from last interaction model.
Google Analytics make an arrow coloured when the change in conversions is 10% or more.
If the change is positive and is 10% or more than the arrow gets green color.
If the change is negative and is 10% or more than the arrow gets red color.
Similarly, from the report above, we can conclude that, the % of change in conversion for ‘Display’ from last interaction model to ‘Last Non-Direct click Model’ (which used by default for all GA non-MCF reports) is 236.88%.
What that means, if you use ‘Last Non-Direct click Model’ (instead of last interaction model) to distribute credit for conversions to Display advertising then the ‘Display Advertising’ deserves 236.88% more credit for conversions.
It also means that ‘Display’ is undervalued by 236.88% under last click attribution model, when this model is compared with ‘last non-direct click model’.
So what insight we have got from this analysis?
The insight is that overall display advertising is undervalued.
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
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
# How can my display advertising be valued from a different perspective?
# Is display advertising undervalued or overvalued, under last click and last non direct click attribution model?
# If I invest in display advertising, how much incrementality can display channel bring to my business bottomline?
# How can I make my display campaigns more effective?
# If I change my display ad spend, how it will effect my website conversions?
You can get answers to such questions by adjusting conversion credit for impressions, while creating an attribution model.
This articles 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.
Get the E-book (52 Pages)
Before you can adjust conversion credit for ‘impressions’, while creating an attribution model, you first need to set up view-through conversion tracking in Google Analytics.
Without view-through conversion tracking setup, you won’t get the option to adjust credit for ‘impression’ while creating a new attribution model in Google Analytics.
If you are brand new to view-through conversions then read this article first: Understanding view-through conversions in Google Adwords where I explained in great detail, what view through conversions are and when they are reported.
In order to valuate display advertising through attribution modelling, follow the steps below:
Step-1: Navigate to ‘Model Comparison Tool’ (under Conversions > Attribution):
Step-2: Click on ‘Select Model’ drop down menu:
Step-3: Set date range to the last 3 months or longer.
Step-4: Click on the link ‘create new custom model’:
Step-5: Give your new attribution model, a name and then select ‘Data Driven’ as baseline model:
# An attribution model is a set of rules which is used to determine, how credit for conversions should be attributed to different marketing channels.
# Baseline attribution models are the pre-built attribution models available in Google Analytics.
# Custom attribution models are user defined attribution models.
I selected ‘data driven’ attribution model as ‘baseline’ model because it analyse the data (related to organic search traffic, direct traffic, referral traffic, uploaded cost data etc) not only from my GA account but also from all those Google Accounts (like Doubleclick Campaign Manager, Google Adwords etc) which are linked to my GA account, in order to algorithmically generate a custom attribution model.
Also when I choose data driven attribution model, I do not have to worry about how to set up the lookback window option to get optimum results from my analysis.
Note: lookback window option has no effect on attribution when you use ‘data driven’ attribution model as ‘baseline’ model.
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.
Step-6: Switch on the toggle button next to ‘Adjust credit for impressions’:
Step-7: Click on the ‘Advanced option…’ link:
Step-8: Adjust credit for impressions like the one below:
Here I have set my attribution model, to give display ad impressions, two times more conversion credit than the other interactions in the conversion path, provided the display ad impressions occurs within 12 hours before a visit is recorded for my website which results in a conversion.
In other words, I have set my attribution model, to give display ad impressions, two times more conversion credit than the other interactions in the conversion path, provided a user completes a goal on my website within 12 hours after viewing (but not clicking) one of my display ads.
That means I can decide which ad exposure should be valued more, based on my understanding of the context/business/marketing.
Bear in mind that,
More an ad impression occurs closer in time to conversion, the more effective it can be considered, in driving conversion.
In other words, an ad impression which resulted in sales within 6 hours, can be considered more effective than an ad impression which resulted in sales after 1 day.
Similarly, an ad impression which resulted in sales within 1 day, can be considered more effective than an ad impression which resulted in sales after 7 days.
In a world of multi-channel, multi-device marketing, there are many touch points which can influence the buying behavior of a customer, in a short span of time.
This makes it quite difficult to effectively assign credit for conversions to a comparatively weak touch point, such as ‘impression’.
So I would suggest to keep the lookback window (not to be confused with the lookback window option in the custom attribution model) as short as possible.
Step-9: Click on ‘Save and apply’ button. This will create a new attribution model which will take ad impressions in the conversion paths, into account and help in the valuation of display advertising:
Step-10: Compare the ‘Last Interaction’ model with ‘Display Advertising Model’ and ‘Last Non-Direct Click’ model:
Step-11: Select ‘Conversions and Value’ from the drop down menu located in the middle of your ‘model comparison tool’ report:
Step-12: Now look at the column named ‘% change in conversion (from last interaction)’ for ‘display’:
Form this report we can conclude that, the % of change in conversion for ‘Display’ from last interaction model to ‘Display Advertising Model’ is 398.39%.
What that means, if you use ‘Display Advertising Model’ (instead of last interaction model) to distribute credit for conversions to Display advertising then the ‘Display Advertising’ deserves 398.39% more credit for conversions.
It also means that ‘Display’ is undervalued by 398.39% under last click attribution model (which is used in GA multi channel funnel reports by default), when this model is compared with ‘Display Advertising Model’.
The upward green arrow next to 398.39% indicates positive change in conversions from last interaction model.
Google Analytics make an arrow coloured when the change in conversions is 10% or more.
If the change is positive and is 10% or more than the arrow gets green color.
If the change is negative and is 10% or more than the arrow gets red color.
Similarly, from the report above, we can conclude that, the % of change in conversion for ‘Display’ from last interaction model to ‘Last Non-Direct click Model’ (which used by default for all GA non-MCF reports) is 236.88%.
What that means, if you use ‘Last Non-Direct click Model’ (instead of last interaction model) to distribute credit for conversions to Display advertising then the ‘Display Advertising’ deserves 236.88% more credit for conversions.
It also means that ‘Display’ is undervalued by 236.88% under last click attribution model, when this model is compared with ‘last non-direct click model’.
So what insight we have got from this analysis?
The insight is that overall display advertising is undervalued.
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
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