Introduction to Attribution Models in Facebook
The attribution model is a set of rules or algorithm that determine which touchpoints should get credit for conversions and how much conversion credit each touchpoint should receive.
Different attribution models, give conversion credit differently.
Facebook Attribution models can be broadly classified into two categories:
- Rule based attribution models.
- Algorithmic attribution models.
Rule based attribution models
Rule based attribution models assign conversion credits to touchpoints based on some rules.
The following are examples of rule based attribution models available in Facebook Attribution reports:
- Even Credit
- Last Click or Visit
- Last Touch
- Positional 30%
- Positional 40%
- Time Decay 1-day
- Time Decay 7-day
Rule based attribution models can be further classified into single touch and multi touch attribution models.
Single touch attribution models assign 100% conversion credit only to a single touchpoint in a conversion path.
Follow are examples of single touch attribution models in Facebook: ‘Last Click or Visit’ and ‘Last Touch’.
Multi-touch attribution models distribute conversion credit to multiple touch points in a conversion path.
Follow are examples of multi-touch attribution models in Facebook: ‘Even Credit’, ‘Positional 30%’, ‘Positional 40%’, ‘Time Decay 1-day’ and ‘Time Decay 7-day’.
Algorithmic attribution models
Algorithmic attribution models assign conversion credits to touchpoints based on an algorithm.
The Data Driven attribution model is an algorithmic attribution model offered by Facebook (in its attribution reports).
Once you have set up attribution reporting in your Facebook ad manager account, you get the option to choose an attribution model:
Note: You can not choose ‘Data Driven’ Attribution Model from the ‘Attribution Model’ drop down menu.
Facebook provides following seven rule based attribution models:
- Even Credit
- Last Click or Visit
- Last Touch
- Positional 30%
- Positional 40%
- Time Decay 1-day
- Time Decay 7-day
#1 Even Credit attribution model
This attribution model gives equal credit for conversion to all the touchpoints in a conversion path.
For example, consider the following conversion path:
Ad Impression > Ad Click > Visit > Ad Impression
This conversion path is made up of four touchpoints.
Under ‘even credit’ attribution model, each touchpoint would receive 25% (100 / 4 touchpoints) credit for conversion.
However, if the ‘ad click’ and ‘visit’ happened within 60 seconds of one another, then the ‘ad click’ and ‘visit’ would be counted as the same touchpoint and only the ‘ad click’ is credited.
So the conversion path (if the ‘ad click’ and ‘visit’ happened within 60 seconds of one another) would now look, like the one below:
Ad Impression > Ad Click > Ad Impression
This conversion path is now made up of only three touchpoints.
Under ‘even credit’ attribution model, each touchpoint would now receive 33.33% (100 / 3 touchpoints) credit for conversion.
Note: Under ‘even credit’ attribution model, if more than 60 seconds elapsed between ‘ad click’ and ‘visit’ then each touchpoint would receive 25% (100 / 4 touchpoints) credit for conversion.
When to use the ‘even credit’ attribution model?
Use this attribution model if you have a business model where each interaction with your customers is equally important for your conversions.
For example, if you provide a customer support service then each interaction with your customers is equally important for you.
In that case, use the even credit 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
#2 Last Click or Visit attribution model
This attribution model gives 100% credit for conversion to the last ad click or visit in a conversion path.
For example, consider the following conversion path:
Ad Impression > Ad Click > Visit > Ad Impression
This conversion path is made up of four touchpoints.
Under ‘last click or visit’ attribution model, the last ‘visit’ would get 100% credit for the conversion.
This attribution model recognize only last ad click or last visit as last touchpoint.
That’s why the last ad impression won’t get 100% credit for the conversion.
Now if the ‘ad click’ and ‘visit’ happened within 60 seconds of one another, then the ‘ad click’ and ‘visit’ would be counted as the same touchpoint and only the ‘ad click’ is credited.
So in that case the conversion path would now look, like the one below:
Ad Impression > Ad Click > Ad Impression
This conversion path is now made up of only three touchpoints.
Under ‘last click or visit’ attribution model, the last ad click would now receive 100% credit for conversion.
Note: Under ‘last click or visit’ attribution model, if more than 60 seconds elapsed between ‘ad click’ and ‘visit’ then the last ‘visit’ would get 100% credit for the conversion.
When to use the ‘last click or visit’ attribution model?
Use this model, if least amount of buying consideration is involved.
For example, if you are a FMCG (fast moving consumer goods) company like ‘Tesco’ or ‘Walmart’ and you sell products which involve the least amount of consideration by a buyer (like purchasing toothpaste), then you can use the ‘Last Click or Visit’ attribution model.
This is because you do not need to assign more conversion credit to the first and middle interactions in your conversion path.
#3 Last touch attribution model
Facebook uses this attribution model by default.
The last touch attribution model gives 100% credit for conversion to the last touch point in a conversion path.
This touch point can be an ad click, visit or ad impression.
However the last touch model gives 100% credit to the last ad impression only when there was no ad click or visit prior to conversion.
In other words, by default Facebook report conversion on the day, an ad was last clicked or viewed and not always on the day the conversion actually took place.
Use the Ads Insights API, if you want Facebook to report a conversion on the day it happened.
For example, consider the following conversion path:
Ad Impression > Ad Click > Visit > Ad Impression
This conversion path is made up of four touchpoints.
Under ‘last touch’ attribution model, the last ‘visit’ would get 100% credit for the conversion.
The last touch model gives 100% credit to the last ad impression only when there was no ‘ad click’ or ‘visit’ prior to conversion.
For example in the conversion path:
Ad Impression > Ad Impression > Ad Impression
the last ad impression would receive 100% credit for conversion as there are no ‘ad click’ or ‘visit’ touchpoints in the conversion path.
Now if the ‘ad click’ and ‘visit’ happened within 60 seconds of one another, then the ‘ad click’ and ‘visit’ would be counted as the same touchpoint and only the ‘ad click’ is credited.
So for the following conversion path where the ‘ad click’ and ‘visit’ happened within 60 seconds of one another :
Ad Impression > Ad Click > Visit > Ad Impression
the last ad click would now receive 100% credit for conversion.
Note: Under ‘last touch’ attribution model, if more than 60 seconds elapsed between ‘ad click’ and ‘visit’ then the last ‘visit’ would get 100% credit for the conversion.
When to use the ‘last touch’ attribution model?
Use this model, if least amount of buying consideration is involved.
#4 Positional 30% attribution model
It is a position based attribution model which gives 30% conversion credit to the first touchpoint and 30% conversion credit to the last touchpoint in a conversion path.
The remaining 40% conversion credit is equally distributed among all other touchpoints in a conversion path.
For example, consider the following conversion path:
Ad Impression > Ad Click > Visit > Ad Impression
This conversion path is made up of four touchpoints.
Under ‘Positional 30%’ attribution model, the first ‘ad impression’ would receive 30% credit for the conversion.
The last ‘ad impression’ would receive 30% credit for the conversion.
The remaining conversion credit (100 – (30 + 30) = 40) would be equally divided between ‘ad click’ and ‘visit’ touchpoints.
So the ‘ad click touch point would receive 20% (40 / 2) credit for conversion and the ‘visit’ touch point would receive 20% (40/2) credit for conversion:
Here, 30 + 20 + 20 + 30 = 100
This proves that each touch point received accurate conversion credit.
If the sum of all conversion credit turned out to be below or above 100 then it would mean, the conversion credits were not assigned correctly.
Now if the ‘ad click’ and ‘visit’ happened within 60 seconds of one another, then the ‘ad click’ and ‘visit’ would be counted as the same touchpoint and only the ‘ad click’ is credited.
So for the following conversion path where the ‘ad click’ and ‘visit’ happened within 60 seconds of one another :
Ad Impression > Ad Click > Visit > Ad Impression
The ‘Positional 30%’ attribution model will give 30% conversion credit to each first and last ‘ad impression’ and the remaining 40% conversion credit (100 – 60) to the ‘ad click’ touch point.
Note: Under ‘Positional 30%’ attribution model, if more than 60 seconds elapsed between ‘ad click’ and ‘visit’ then the first and last ‘ad impressions’ would each receive 30% conversion credit and the ‘ad click’ and ‘visit’ touchpoints would each receive 20% conversion credit.
When to use the ‘Positional 30%’ attribution model?
If you have a business model, or advertising objectives, which value first and last customer interactions more than the middle interactions, then use the Position Based attribution model.
#5 Positional 40% attribution model
This attribution model is just like ‘Positional 30% model.
The only difference is that the ‘Positional 40%’ model gives 40% conversions credit (instead of 30%) to both first and last touch points in a conversion path.
The remaining 20% conversion credit is equally distributed among all other touchpoints.
#6 Time Decay 1-Day Attribution Model
The time decay attribution model assign more conversion credit to the touchpoints that happened closer in time to the conversion.
The ‘Time Decay 1-Day’ attribution model is a type of ‘time decay’ model which distribute conversion credit using 1 day half life.
What that means, the touch points that happened 1 day before the conversion get 50% of the conversion credit and the touch points that happened 2 days before the conversion get 25% of the conversion credit.
Under the ‘time decay model’, if the ‘ad click’ and ‘visit’ happened within 60 seconds of one another, then the ‘ad click’ and ‘visit’ would be counted as the same touchpoint and only the ‘ad click’ is credited.
When to use the ‘Time Decay’ model?
Use the Time Decay model if you are running time sensitive promotional campaigns.
If you want to understand the buying behavior of your customers during a promotional campaign, then you would want to assign more conversion credits to the touchpoints which occurred closest in time to conversions as they are more relevant than the touchpoints which occurred further in the past.
In that case use the Time Decay model.
#7 Time Decay 7-Day Attribution Model
The Time Decay 7-Day attribution model is another type of ‘time decay’ model which distribute conversion credit using 7 day half life (instead of 1 day half life).
What that means, the touch points that happened 7 days before the conversion get 50% of the conversion credit and the touch points that happened 14 days before the conversion, get 25% of the conversion credit.
Data Driven attribution (DDA) model in Facebook
The Data Driven attribution model (DDA) is an algorithmic attribution model (statistical model) which is updated periodically by Facebook.
This attribution model uses statistical modelling to understand and assign conversion credit to Facebook touchpoints in a conversion path.
The conversion credit distribution is based on the historical data as well as the estimated incremental value of the Facebook touchpoints.
Through the DDA model, you can identify the marketing campaigns across Facebook, Audience Network, Messenger and Instagram that have the greatest impact on generating conversions.
The DDA model help you measure incrementality i.e. how many additional conversions were caused by your Facebook marketing campaigns compared to those that would have happened without your campaigns.
Note: The Data Driven attribution model is not a rule based model and it only measures marketing campaigns on Facebook, Audience Network, Messenger and Instagram. In other words this model is available only for Facebook ad platform and not for other ad platforms like ‘Google Ads’, ‘Bing Ads’ etc.
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
Related Articles
- Facebook Attribution and Conversion Windows Guide
- How to set up the Facebook Attribution Tool
- How to calculate the ROI of your Facebook Marketing Campaigns
- How to Setup Funnels in Facebook Ads Manager
- How to use funnels for your Facebook Ad Campaigns
- How to advertise on Facebook for FREE with unlimited budget
- Secret to Setup Facebook Pixel Tracking Correctly in Google Tag Manager
- Why Facebook and Google Analytics data do not match
- Learn to correctly track Facebook Referral traffic in Google Analytics
- Learn to set up Facebook Pixel Tracking via Google Tag Manager
- Tracking Website Sales in Facebook via Google Tag Manager
- Understanding Facebook Referral traffic in Google Analytics
- Open Graph Protocol for Facebook Explained with Examples
- Tracking Facebook ‘Likes’ and ‘Unlikes’ in Google Analytics
- Complete Guide to Google Analytics for Facebook
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
The attribution model is a set of rules or algorithm that determine which touchpoints should get credit for conversions and how much conversion credit each touchpoint should receive.
Different attribution models, give conversion credit differently.
Facebook Attribution models can be broadly classified into two categories:
- Rule based attribution models.
- Algorithmic attribution models.
Rule based attribution models
Rule based attribution models assign conversion credits to touchpoints based on some rules.
The following are examples of rule based attribution models available in Facebook Attribution reports:
- Even Credit
- Last Click or Visit
- Last Touch
- Positional 30%
- Positional 40%
- Time Decay 1-day
- Time Decay 7-day
Rule based attribution models can be further classified into single touch and multi touch attribution models.
Single touch attribution models assign 100% conversion credit only to a single touchpoint in a conversion path.
Follow are examples of single touch attribution models in Facebook: ‘Last Click or Visit’ and ‘Last Touch’.
Multi-touch attribution models distribute conversion credit to multiple touch points in a conversion path.
Follow are examples of multi-touch attribution models in Facebook: ‘Even Credit’, ‘Positional 30%’, ‘Positional 40%’, ‘Time Decay 1-day’ and ‘Time Decay 7-day’.
Algorithmic attribution models
Algorithmic attribution models assign conversion credits to touchpoints based on an algorithm.
The Data Driven attribution model is an algorithmic attribution model offered by Facebook (in its attribution reports).
Once you have set up attribution reporting in your Facebook ad manager account, you get the option to choose an attribution model:
Note: You can not choose ‘Data Driven’ Attribution Model from the ‘Attribution Model’ drop down menu.
Facebook provides following seven rule based attribution models:
- Even Credit
- Last Click or Visit
- Last Touch
- Positional 30%
- Positional 40%
- Time Decay 1-day
- Time Decay 7-day
#1 Even Credit attribution model
This attribution model gives equal credit for conversion to all the touchpoints in a conversion path.
For example, consider the following conversion path:
Ad Impression > Ad Click > Visit > Ad Impression
This conversion path is made up of four touchpoints.
Under ‘even credit’ attribution model, each touchpoint would receive 25% (100 / 4 touchpoints) credit for conversion.
However, if the ‘ad click’ and ‘visit’ happened within 60 seconds of one another, then the ‘ad click’ and ‘visit’ would be counted as the same touchpoint and only the ‘ad click’ is credited.
So the conversion path (if the ‘ad click’ and ‘visit’ happened within 60 seconds of one another) would now look, like the one below:
Ad Impression > Ad Click > Ad Impression
This conversion path is now made up of only three touchpoints.
Under ‘even credit’ attribution model, each touchpoint would now receive 33.33% (100 / 3 touchpoints) credit for conversion.
Note: Under ‘even credit’ attribution model, if more than 60 seconds elapsed between ‘ad click’ and ‘visit’ then each touchpoint would receive 25% (100 / 4 touchpoints) credit for conversion.
When to use the ‘even credit’ attribution model?
Use this attribution model if you have a business model where each interaction with your customers is equally important for your conversions.
For example, if you provide a customer support service then each interaction with your customers is equally important for you.
In that case, use the even credit 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
#2 Last Click or Visit attribution model
This attribution model gives 100% credit for conversion to the last ad click or visit in a conversion path.
For example, consider the following conversion path:
Ad Impression > Ad Click > Visit > Ad Impression
This conversion path is made up of four touchpoints.
Under ‘last click or visit’ attribution model, the last ‘visit’ would get 100% credit for the conversion.
This attribution model recognize only last ad click or last visit as last touchpoint.
That’s why the last ad impression won’t get 100% credit for the conversion.
Now if the ‘ad click’ and ‘visit’ happened within 60 seconds of one another, then the ‘ad click’ and ‘visit’ would be counted as the same touchpoint and only the ‘ad click’ is credited.
So in that case the conversion path would now look, like the one below:
Ad Impression > Ad Click > Ad Impression
This conversion path is now made up of only three touchpoints.
Under ‘last click or visit’ attribution model, the last ad click would now receive 100% credit for conversion.
Note: Under ‘last click or visit’ attribution model, if more than 60 seconds elapsed between ‘ad click’ and ‘visit’ then the last ‘visit’ would get 100% credit for the conversion.
When to use the ‘last click or visit’ attribution model?
Use this model, if least amount of buying consideration is involved.
For example, if you are a FMCG (fast moving consumer goods) company like ‘Tesco’ or ‘Walmart’ and you sell products which involve the least amount of consideration by a buyer (like purchasing toothpaste), then you can use the ‘Last Click or Visit’ attribution model.
This is because you do not need to assign more conversion credit to the first and middle interactions in your conversion path.
#3 Last touch attribution model
Facebook uses this attribution model by default.
The last touch attribution model gives 100% credit for conversion to the last touch point in a conversion path.
This touch point can be an ad click, visit or ad impression.
However the last touch model gives 100% credit to the last ad impression only when there was no ad click or visit prior to conversion.
In other words, by default Facebook report conversion on the day, an ad was last clicked or viewed and not always on the day the conversion actually took place.
Use the Ads Insights API, if you want Facebook to report a conversion on the day it happened.
For example, consider the following conversion path:
Ad Impression > Ad Click > Visit > Ad Impression
This conversion path is made up of four touchpoints.
Under ‘last touch’ attribution model, the last ‘visit’ would get 100% credit for the conversion.
The last touch model gives 100% credit to the last ad impression only when there was no ‘ad click’ or ‘visit’ prior to conversion.
For example in the conversion path:
Ad Impression > Ad Impression > Ad Impression
the last ad impression would receive 100% credit for conversion as there are no ‘ad click’ or ‘visit’ touchpoints in the conversion path.
Now if the ‘ad click’ and ‘visit’ happened within 60 seconds of one another, then the ‘ad click’ and ‘visit’ would be counted as the same touchpoint and only the ‘ad click’ is credited.
So for the following conversion path where the ‘ad click’ and ‘visit’ happened within 60 seconds of one another :
Ad Impression > Ad Click > Visit > Ad Impression
the last ad click would now receive 100% credit for conversion.
Note: Under ‘last touch’ attribution model, if more than 60 seconds elapsed between ‘ad click’ and ‘visit’ then the last ‘visit’ would get 100% credit for the conversion.
When to use the ‘last touch’ attribution model?
Use this model, if least amount of buying consideration is involved.
#4 Positional 30% attribution model
It is a position based attribution model which gives 30% conversion credit to the first touchpoint and 30% conversion credit to the last touchpoint in a conversion path.
The remaining 40% conversion credit is equally distributed among all other touchpoints in a conversion path.
For example, consider the following conversion path:
Ad Impression > Ad Click > Visit > Ad Impression
This conversion path is made up of four touchpoints.
Under ‘Positional 30%’ attribution model, the first ‘ad impression’ would receive 30% credit for the conversion.
The last ‘ad impression’ would receive 30% credit for the conversion.
The remaining conversion credit (100 – (30 + 30) = 40) would be equally divided between ‘ad click’ and ‘visit’ touchpoints.
So the ‘ad click touch point would receive 20% (40 / 2) credit for conversion and the ‘visit’ touch point would receive 20% (40/2) credit for conversion:
Here, 30 + 20 + 20 + 30 = 100
This proves that each touch point received accurate conversion credit.
If the sum of all conversion credit turned out to be below or above 100 then it would mean, the conversion credits were not assigned correctly.
Now if the ‘ad click’ and ‘visit’ happened within 60 seconds of one another, then the ‘ad click’ and ‘visit’ would be counted as the same touchpoint and only the ‘ad click’ is credited.
So for the following conversion path where the ‘ad click’ and ‘visit’ happened within 60 seconds of one another :
Ad Impression > Ad Click > Visit > Ad Impression
The ‘Positional 30%’ attribution model will give 30% conversion credit to each first and last ‘ad impression’ and the remaining 40% conversion credit (100 – 60) to the ‘ad click’ touch point.
Note: Under ‘Positional 30%’ attribution model, if more than 60 seconds elapsed between ‘ad click’ and ‘visit’ then the first and last ‘ad impressions’ would each receive 30% conversion credit and the ‘ad click’ and ‘visit’ touchpoints would each receive 20% conversion credit.
When to use the ‘Positional 30%’ attribution model?
If you have a business model, or advertising objectives, which value first and last customer interactions more than the middle interactions, then use the Position Based attribution model.
#5 Positional 40% attribution model
This attribution model is just like ‘Positional 30% model.
The only difference is that the ‘Positional 40%’ model gives 40% conversions credit (instead of 30%) to both first and last touch points in a conversion path.
The remaining 20% conversion credit is equally distributed among all other touchpoints.
#6 Time Decay 1-Day Attribution Model
The time decay attribution model assign more conversion credit to the touchpoints that happened closer in time to the conversion.
The ‘Time Decay 1-Day’ attribution model is a type of ‘time decay’ model which distribute conversion credit using 1 day half life.
What that means, the touch points that happened 1 day before the conversion get 50% of the conversion credit and the touch points that happened 2 days before the conversion get 25% of the conversion credit.
Under the ‘time decay model’, if the ‘ad click’ and ‘visit’ happened within 60 seconds of one another, then the ‘ad click’ and ‘visit’ would be counted as the same touchpoint and only the ‘ad click’ is credited.
When to use the ‘Time Decay’ model?
Use the Time Decay model if you are running time sensitive promotional campaigns.
If you want to understand the buying behavior of your customers during a promotional campaign, then you would want to assign more conversion credits to the touchpoints which occurred closest in time to conversions as they are more relevant than the touchpoints which occurred further in the past.
In that case use the Time Decay model.
#7 Time Decay 7-Day Attribution Model
The Time Decay 7-Day attribution model is another type of ‘time decay’ model which distribute conversion credit using 7 day half life (instead of 1 day half life).
What that means, the touch points that happened 7 days before the conversion get 50% of the conversion credit and the touch points that happened 14 days before the conversion, get 25% of the conversion credit.
Data Driven attribution (DDA) model in Facebook
The Data Driven attribution model (DDA) is an algorithmic attribution model (statistical model) which is updated periodically by Facebook.
This attribution model uses statistical modelling to understand and assign conversion credit to Facebook touchpoints in a conversion path.
The conversion credit distribution is based on the historical data as well as the estimated incremental value of the Facebook touchpoints.
Through the DDA model, you can identify the marketing campaigns across Facebook, Audience Network, Messenger and Instagram that have the greatest impact on generating conversions.
The DDA model help you measure incrementality i.e. how many additional conversions were caused by your Facebook marketing campaigns compared to those that would have happened without your campaigns.
Note: The Data Driven attribution model is not a rule based model and it only measures marketing campaigns on Facebook, Audience Network, Messenger and Instagram. In other words this model is available only for Facebook ad platform and not for other ad platforms like ‘Google Ads’, ‘Bing Ads’ etc.
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
Related Articles
- Facebook Attribution and Conversion Windows Guide
- How to set up the Facebook Attribution Tool
- How to calculate the ROI of your Facebook Marketing Campaigns
- How to Setup Funnels in Facebook Ads Manager
- How to use funnels for your Facebook Ad Campaigns
- How to advertise on Facebook for FREE with unlimited budget
- Secret to Setup Facebook Pixel Tracking Correctly in Google Tag Manager
- Why Facebook and Google Analytics data do not match
- Learn to correctly track Facebook Referral traffic in Google Analytics
- Learn to set up Facebook Pixel Tracking via Google Tag Manager
- Tracking Website Sales in Facebook via Google Tag Manager
- Understanding Facebook Referral traffic in Google Analytics
- Open Graph Protocol for Facebook Explained with Examples
- Tracking Facebook ‘Likes’ and ‘Unlikes’ in Google Analytics
- Complete Guide to Google Analytics for Facebook
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