Google Analytics Attribution Modeling Tutorial

Table of Contents for Google Analytics Attribution Modeling Tutorial

  1. What is Attribution Modelling?
  2. What are the objectives of Attribution Modelling?
  3. Why Attribution Modelling is the KEY to online business success?
  4. How is Attribution Modelling helpful for ecommerce and non-ecommerce websites?
  5. Why you need formal training in Attribution Modelling
  6. How does Attribution work?
  7. Difference between Attribution Modelling and Marketing Mix Modelling
  8. Different types of Attributions
  9. Online-Offline Attribution
  10. Multi-Device Attribution
  11. Multi-Channel Attribution
  12. Real World Attribution
  13. Introduction to Attribution Models
  14. Types of Google Analytics Attribution Models
  15. What is the advantage of using an Attribution Model?
  16. Before you start Attribution Modelling
  17. Acquisition channels and Attribution Modelling
  18. Introduction to Acquisition Channels
  19. Multi-Channel Funnel Reports
  20. Understanding Conversions in Google Analytics Multi-Channel Funnel Reports
  21. Data discrepancy between Multi-Channel Funnel Reports and other reports in Google Analytics
  22. Introduction to Conversion Paths
  23. Introduction to Multi-Channel Funnel Data
  24. Introduction to Interactions (Touchpoints)
  25. Introduction to Channel Labels
  26. Introduction to Channel Grouping
  27. Conversion Path Analysis
  28. Segmenting Conversion Paths
  29. Understanding First click and Assisted Conversions
  30. Conversion Values
  31. How Assisted/Last click conversion of a marketing channel is calculated and what insight you can get from it?
  32. How First/Last click conversion of a marketing channel is calculated and what insight you can get from it?
  33. Google Analytics Attribution Reports

What is Attribution Modelling?

Attribution modelling is the process of understanding and assigning conversion credits to marketing channels. These marketing channels are primarily digital marketing channels (like paid search, display advertising, Facebook, etc.) but can also include offline touchpoints (like store visits, phone calls, etc.)

What are the objectives of Attribution Modelling?

Attribution modelling is carried out to understand the buying behaviour of your website users and to determine the most effective marketing channels for investment at a particular point in time.

Through attribution modelling you can get answers to business questions like:

  • Why do people buy from my website?
  • What happens before they buy?
  • What prompted them to make a purchase or complete a predefined goal?

Why Attribution Modelling is the KEY to online business success?

A long time ago, I received an email from a client which read something like this:

Hi,

I will put this month’s payment through but I have to ask – are you happy with the results so far? 

Our cost per acquisition is so high. We don’t see any ROI from our Google AdWords campaigns. 

If this continues after this month we will have to discontinue using your services.

Regards

Your client

This email was basically a final warning for me to either improve the campaigns’ performance or lose the project.

The cost per acquisition for the Google Ads campaigns was pretty high and all the generic keywords that I was bidding on were not resulting in enough sales to cover the ad spend. Despite my best efforts, I was not able to make the campaigns profitable.

However, I knew from past experience that whenever I reduced the ad spend or paused the campaigns, there was a decline in the overall website sales. At that time, I just believed what I saw in the analytics reports and the reports were telling me and my client that the cost per acquisition from the Google Ads campaigns was high and the campaigns were not profitable.

Later on, I had another client and I was in charge of their Facebook marketing campaigns. Google Analytics wasn’t reporting many sales from Facebook and the Facebook campaigns didn’t seem to be profitable. But, yet again, every time I reduced the ad spend or paused the Facebook campaigns, I noticed a decline in overall website sales.

I couldn’t figure it out! What was going wrong?

I was just relying on correlation is causation. Meaning that when I do something, something happens as a result.

So I was basically losing business because I did not understand the true customer purchase journey. I did not understand how Google Analytics, Google Ads and Facebook actually attribute conversions and sales. 

Attribution Modelling in Google Ads and FacebookAttribution Modelling in Google Analytics and Beyond

Get my best selling books on Attribution Modelling

  • Learn to implement attribution modelling in your organization
  • Understand the customer purchase journey across devices
  • Determine the most effective marketing channels for investment

 Click book covers to find out more.

Because my client was not aware of the Last Ad Click attribution model used by Google Ads, and not really familiar with attribution modelling in general, he had no reason to doubt his interpretation of the data. He simply believed whatever he saw in the analytics reports. He thought that he was correctly interpreting the data and I could not change his belief.

After this, I came to the conclusion that if I do not understand, pretty fast, how marketing platforms actually attribute conversions and how customers use different marketing channels and devices in their purchase journey then one thing was certain, I was going to go out of business.

This fear of losing clients and going out of business prompted me to dig deep into attribution modelling. 

Then I came to the conclusion that the cost per acquisition that my client was referring to in the case of their Google Ads campaigns, was actually ‘cost per last ad click acquisition’. 

Then I started to understand how platforms like Google Analytics, Google Ads and Facebook actually attribute conversions. 

Even if a campaign is not directly completing a sale, it may be initiating a sale or assisting a sale.

Even if a keyword is not directly completing a sale, it may be initiating or assisting a sale.

Not all direct traffic is actually direct. Whenever a referrer is not passed, that traffic is reported as direct traffic by Google Analytics.

Then I realised that if I can track offline marketing activities and conversions online and correlate them with the website usage data then I would be able to truly understand the customer purchase journey and determine the most effective marketing channels for investment.

So that is how I came to the conclusion that learning and implementing attribution modelling is the key to online business success.

How is Attribution Modelling helpful for ecommerce and non-ecommerce websites?

Why you need formal training in Attribution Modelling

For many people, Attribution Modelling is a mumbo jumbo. They may have heard about it somewhere. And they may have a vague idea of what it is but they don’t really know how to use and benefit from it.

And that is because attribution modelling is full of jargon. We have got ‘last click conversions’, we have got ‘first click conversions’, ‘data-driven conversions’. We have got ‘click-through conversions’, we have got ‘view-through conversions’.

Then we have got dozens of different attribution windows, conversion windows, attribution models. And then under each attribution window, conversion window and attribution model, we can have a range of different conversion volume and conversion values. 

Then we have got different types of cost per acquisitions (CPA) like Last Interaction CPA, Last non-direct click CPA, Linear CPA, Time Decay CPA…. and the list goes on and on. 

And the biggest headache of all is to decide which attribution window, conversion window and/or attribution model to use for optimizing marketing campaigns and interpreting data. 

All of this has made web analytics and optimization incredibly hard and complex. 

However, you need to learn all of this attribution modelling jargon. And not just learn it but truly understand it, if you want to remain relevant in the current marketplace and in demand. 

Attribution Modelling in Google Ads and FacebookAttribution Modelling in Google Analytics and Beyond

Get my best selling books on Attribution Modelling

  • Learn to implement attribution modelling in your organization
  • Understand the customer purchase journey across devices
  • Determine the most effective marketing channels for investment

 Click book covers to find out more.

Gone are those days when you were advertising on just one marketing platform and device, and attributing sales was as easy as looking into an analytics report.  Analytics reports are not what you see is what you get. They are what you interpret is what you get. 

Now in the world of multi-channel and multi-device marketing and the ever-increasing number of marketing platforms, attributing conversions to the right touchpoint is becoming progressively complex and hard. 

Let’s be honest. Most of the online marketing that is exact today is not based on science or any formalized process. People are doing all sorts of different things to generate sales.

They blog, they produce videos, they are on Instagram, they do podcasts, they speak on stages throughout the world. But they don’t really know what is working and what is not working. 

They are just copying each other, like blind leading the blind. They do not have any data to back up their theory, formulate a hypothesis, or increase the budget. They have got no way of knowing which marketing channels are actually working.

They can not put their finger on anyone marketing activity and can say with any degree of confidence that this is the marketing activity which has the most impact on our sales. 

What they have got is an ‘attribution problem’.

So you can no longer ignore attribution modelling unless you don’t mind getting obsolete. Because markets reward those who continue to add value to the marketplace. Those who refuse to upgrade themselves or believe they know it all are left behind. 

How does Attribution work?

Attribution works just like a football team.

A football team is made up of players. Each player passes the ball to the other players with the aim of scoring a goal. The end goal of the team is to score as many goals as possible.

In the case of online marketing, your team is made up of different marketing channels, campaigns, keywords and devices. These are your players. All of these players work together to create sales and other conversions. All of these players pass customers through different user experiences which lead to sales. The end goal of your marketing team is to generate as many sales as possible.

In a football match, no single player is solely responsible for winning a match. Different players work together to win a match. The win is always a team effort. Similarly, in a multi-channel marketing world, no single channel is solely responsible for generating conversions and sales.

Different marketing channels work together to create the user experience that leads to sales and conversions. 

That is why in attribution modelling we do not focus on measuring and optimizing just one marketing channel or campaign. We do not create attribution strategies around a single channel or campaign. Instead, we focus on measuring and optimizing the mix and weight of the portfolio of marketing channels or campaigns.

Attribution Modelling in Google Ads and FacebookAttribution Modelling in Google Analytics and Beyond

Get my best selling books on Attribution Modelling

  • Learn to implement attribution modelling in your organization
  • Understand the customer purchase journey across devices
  • Determine the most effective marketing channels for investment

 Click book covers to find out more.

In a football team, some players really shine in defense (i.e. stopping a competitor from scoring a goal) and some players really shine in offense (i.e. scoring a goal for their team). However, if you do not understand their natural skills and abilities and end up placing a player which is good in defence in an offensive position, he will not be able to score as many goals as required to win a match.

Similarly, in the case of online marketing, some channels and campaigns are really good at initiating a customer’s purchase journey, whilst some are really good at building relationships and some are really good at closing sales. 

For example, display advertising (when done right) can help a lot in creating brand awareness and retention but it usually does not result in any direct sales. So if you evaluate a display ad campaign by its ability to close sales, you are likely to face disappointment and may choose to deinvest in it. It is like judging a fish by its ability to climb a tree.

Similarly, some marketing campaigns are really good at getting ‘add to carts’, some are really good at ‘initiating checkouts’ and some are really good at closing sales. As an online marketer, you need to optimize your campaigns for the right conversion objective.

If you optimize all of your campaigns only for closing sales, you are going to lose money. Just like if you instruct your entire football team to only play offense, the competing team could easily score more goals and win. 

Difference between Attribution Modelling and Marketing Mix Modelling

Attribution modelling is not the same as marketing mix modelling (MMM).

Marketing mix modelling is carried out to measure and forecast the impact of various offline marketing activities on sales and ROI. Whereas, Attribution Modelling is carried out to measure the impact of various online marketing activities on sales and ROI. So in the context of digital media, the marketing mix modelling can be referred to as attribution modelling.

To learn more about the difference between Attribution Modelling and Marketing Mix Modelling, check out this article: Marketing Mix Modeling vs. Attribution Modeling. Which one is right for your business?

Different types of Attributions

There are four types of attributions:

  1. Online-Offline Attribution
  2. Multi-Device Attribution
  3. Multi-Channel Attribution
  4. Real World Attribution

Online-Offline Attribution

In the case of online-offline attribution, we determine the impact of digital marketing channels on offline marketing channels and vice versa.

We try to understand how online and offline marketing campaigns work together to create conversions and how the credit for conversions should be distributed among different online and offline marketing channels. Google Analytics support this type of attribution (to an extent).

Multi-Device Attribution

In the case of multi-device attribution, we determine the impact of multiple devices (desktop, tablets, smartphones, smart TVs, etc) on conversions.

We try to understand how different devices work together to create conversions and how the credit for conversions should be distributed among different devices. Google Analytics support this type of attribution (to an extent).

Multi-Channel Attribution

Multi-channel Attribution is the most popular attribution and when marketers talk about attribution they are generally referring to this attribution.

In the case of ‘multi-channel attribution’, we determine the impact of multiple digital marketing channels (paid search, organic search, email marketing, direct traffic, referral traffic, display advertising, etc) on conversions.

We try to understand how different digital channels work together to create conversions and how the credit for conversions should be distributed among various channels. Google Analytics supports this type of attribution via Multi-Channel Funnel Reports and Model Comparison Tool.

The multi-channel attribution can be single-touch or multi-touch. Single-touch attribution models include first and last touch attribution models. Whereas multi-touch attribution models include time decay, linear and position-based attribution models.

Real World Attribution

In the real world, customers do not prioritize offline marketing channels over online marketing channels and vice versa. They don’t even prioritize one device over the other (like desktop over tablets or smartphones over smart TVs) all the time.

In the real world, customers can go back and forth between online and offline marketing channels or they can go back and forth between tablet and desktop depending upon what stage they are in their purchase process, what they are buying, where they are, what device they own and what is their comfort level.

For example, some customers are more comfortable buying from a store than buying online. Whereas some customers are more comfortable buying online than buying from a store.

Some customers don’t purchase high price items online. Some customers always make a purchase offline and use online channels only for research work. Some customers always make a purchase from a desktop or laptops. Some customers never make a purchase from smartphones while some always do. So there can be ‘N’ types of buying behaviour.

None of the existing attribution models (online-offline, multi-device, and multi-channel) take these back and forth activities of customers between multiple devices both online and offline into account while distributing credit for conversions. So we can’t get the complete picture of the conversion path followed by customers.

Attribution Modelling in Google Ads and FacebookAttribution Modelling in Google Analytics and Beyond

Get my best selling books on Attribution Modelling

  • Learn to implement attribution modelling in your organization
  • Understand the customer purchase journey across devices
  • Determine the most effective marketing channels for investment

 Click book covers to find out more.

The real-world attribution is the hybrid of online-offline, multi-device, and multi-channel attributions. It takes into account the back and forth activities of customers between multiple devices both online and offline while distributing credit for conversions.

Because of that property, the real world attribution model is much more complex and difficult to develop than any existing attribution model. But at that same time, it is the only true attribution model.

Contrary to popular belief, marketing especially in the developed world is neither purely online nor purely offline, it is nonline. In nonline marketing, we do not prioritise online marketing channels/touchpoints over offline marketing channels/touchpoints and vice versa, as customers can go back and forth between the two.

In nonline analytics, we do not measure just the online customer purchase journey or just the offline customer journey but we measure the overall customer journey which includes exposure to both online and offline marketing channels/touchpoints.

To learn more about nonline marketing and analytics, check out this article: Introduction to Nonline Analytics – True Multi Channel Analytics

Introduction to Attribution Models

In the context of Google Analytics, an attribution model is a set of rules or algorithms that determine how credit for conversions should be attributed/distributed to various touchpoints in a conversion path.

A touchpoint (also known as an interaction) is exposure to a marketing channel.

A conversion path is the navigation path which a user followed to complete a conversion on your website. It is made up of a sequence of interactions/touchpoints with digital marketing channels during the 1 to 90 day period that led to conversions.

Types of Google Analytics Attribution Models

Attribution models in Google Analytics can be broadly classified into two categories:

1) Default attribution models – These are pre-built models that define how credit for conversion should be distributed to various interactions (or touchpoints) in a conversion path before the custom credit rules are applied.

2) Custom attribution models – These are user-defined attribution models.

Google Analytics provides eight different types of default attribution models. They are:

  1. Last interaction attribution model (also known as the last touch attribution model)
  2. First interaction attribution model (also known as the first touch attribution model)
  3. Linear attribution model
  4. Time decay attribution model
  5. Position based attribution model
  6. Last non-direct click model
  7. Last Ad Click
  8. Data-Driven Attribution Model

To learn more about the different types of Google Analytics attribution models, check out this article: Default & Custom Google Analytics Attribution Models Explained

What is the advantage of using an Attribution Model?

Through attribution models, you can test your assumptions by experimenting.

For example, under the last-click attribution model, your display advertising may be heavily undervalued because of your customers’ unique purchase behaviour. Maybe the majority of your customers are getting influenced by your display ads in their conversion journey but they are not clicking on these ads before making a purchase.

But how can you know for sure whether or not display advertising is undervalued or overvalued without creating and comparing an attribution model with the last-touch attribution model. This is where custom attribution models come into the picture.

You create a hypothesis and then test it by creating a custom attribution model. You then compare your model with the last-touch model or some other attribution model. The hypothesis you create is based on your analysis. Your hypothesis could be something like:

“If a user completes a goal conversion on my website within 12 hours after viewing (but not clicking) one of my display ads, then the display ad impressions should get two times more conversion credit than the other interactions in the conversion path.”

You can test this hypothesis by creating a custom attribution model. 

Before you start Attribution Modelling

Before you start attribution modelling make sure that you have acquired a very deep understanding of your client’s business, their industry, and their target market. Because if you don’t, then you will end up applying/creating a wrong attribution model and lose a lot of money.

You have developed a great understanding of a business when you can do all of the following:

1. You can confidently look beyond data and raw numbers and can make business and marketing decisions based on: 

  • Context.
  • Faith (collective know-how of your organisation, target audience, and industry).
  • All business and marketing activities outside the digital realm. 

2. You do not dismiss any claim just because it cannot be backed up with data.

3. You understand what your analytics tools and KPIs can measure and cannot measure, and where to trade-off. 

4. You know exactly what data needs to be collected, integrated and analysed, and what data should be overlooked. 

Attribution Modelling in Google Ads and FacebookAttribution Modelling in Google Analytics and Beyond

Get my best selling books on Attribution Modelling

  • Learn to implement attribution modelling in your organization
  • Understand the customer purchase journey across devices
  • Determine the most effective marketing channels for investment

 Click book covers to find out more.

Before you start attribution modelling purge your analytics data

Any business or marketing decision based on flawed data will not produce optimum results and could also result in financial loss.

So for example, be careful what you track as Goal conversions in Google Analytics. I have seen analytics accounts where marketers track ‘visits to the home page’ as a conversion or ‘visits to the product category page’ as conversion.

Track only those goals which are beneficial to your customers and company. Irrelevant goals can drastically skew your conversion rate and the data in the multi-channel funnel reports.

Related Article: You are doing Conversion Tracking all wrong. Here is why

Acquisition channels and Attribution Modelling

Just like hits and sessions, acquisition channels are the building blocks of Google Analytics data and reports. They are the very foundation of Google Analytics (GA) data interpretation. In order to understand user behaviour and website usage data, you need to understand:

1. How Google Analytics defines various traffic sources and mediums. For example, how GA defines organic search and how this differs to paid search. 

2. How Google Analytics defines campaigns and channels.

The knowledge of attribution channels will later help you to understand channel groupings, multi-channel funnel groupings and conversion paths, all of which are an integral part of various multi-channel funnel reports. 

Through multi-channel funnel reports, you can understand how different marketing channels work together to create conversions and sales on your website.  

Introduction to Acquisition Channels

Also known as marketing channels, digital channels or channels, these are the sources of traffic to your website. For example, paid search, organic search, direct, social media, email, affiliate, referral, etc are all examples of acquisition channels.

In multi-channel funnel reports, the acquisition channels are commonly referred to as marketing channels or channels.

To learn more about acquisition channels, read this article: Understanding Channels in Google Analytics.

Multi-Channel Funnel Reports

In Google Analytics, you can carry out Attribution Modelling through the multi-channel funnel reports.

Through multi-channel funnel reports, you can determine:

  1. How marketing channels work together to create conversions.
  2. How much time elapsed between visitors’ initial interest and their purchase
  3. What role did prior website referrals, searches and ads played in a conversion?
  4. How to attribute conversions to a marketing channel.

There are five types of multi-channel funnel reports available in Google Analytics:

#1 Overview report– This report contains a ‘multi-channel funnel conversion visualizer’ through which you can visualize how different marketing channels are working together to create conversions:

multi channel conversion visualizer

The overlapped areas show the channels which worked together to create conversions.

#2 Assisted Conversions Report – This report shows the number of conversions each marketing channel initiated, assisted and completed. It also shows the value of assisted and last interaction conversions.

#3 Top Conversion Path Report – This report shows all of the unique conversion paths that lead to conversions. It also shows the number of conversions from each path and the value of those conversions.

#4 Time Lag Report – This report shows how long it took (in days) for users/visitors to convert. Through this report, you can get an insight into the length of your online sales cycle.

#5 Path Length Report – This report shows the number of interactions it took for your website visitors to convert.

Understanding Conversions in Google Analytics Multi-Channel Funnel Reports

Following is a short video on understanding conversions in the context of Google Analytics Multi-Channel Funnel (MCF) reports:

The definition of conversion is different in multi-channel funnel reports. It can be a goal conversion and/or an ecommerce transaction.

The total conversions in multi-channel funnel reports are the sum of the total number of goal conversions and the total number of ecommerce transactions.

conversions-multi-channel-funnel

For the remainder of this article, whenever I talk about conversions, I am referring to conversions in the context of multi-channel funnels. If I am referring to goal conversions, I will explicitly mention it. So remember that and don’t get confused later on.

Data discrepancy between Multi-Channel Funnel Reports and other reports in Google Analytics

In multi-channel funnel reports, a conversion can be a goal conversion or ecommerce transaction. Whereas in non-multi channel funnel reports, conversion means a goal conversion. The ecommerce transactions are reported separately in non multi-channel funnel reports.

So the total number of conversions in multi-channel funnel reports can be different than the total number of conversions in non-multi channel funnel reports. Also, Multi-channel funnels data collection lags by up to two days. So their results are temporary out of sync with non-multi channel funnel reports.

Introduction to Conversion Paths

A conversion path is the sequence of interactions (clicks, visits, impressions) with digital marketing channels during the 1 to 90 days period that leads to conversions.

The period of 1 to 90 days prior to conversions is known as the lookback window:

look back window

Note: The lookback window is available in all MCF reports, and you can change the setting by dragging the slider.

Now consider the following hypothetical conversion path of a user:

conversion-path
Fig.1

Here a visitor is exposed to 6 marketing channels before he made a purchase. Google Analytics will show this conversion path in the ‘top conversion path report’ as:

google analytics attribution modeling
Fig.2

Note(1): The conversion path is created for each conversion recorded by Google Analytics.

Note(2): The conversion paths are recorded via _ga cookie. 

To know more about Google Analytics cookies, check out the article: How Google Analytics uses cookies.

Note(3): There is no limit to the number of conversion paths Google Analytics can record.

Introduction to Multi-Channel Funnel Data

The multi-channel funnel data is a combination of conversion data and conversion paths and is compiled from un-sampled data. Since the multi-channel funnel data collection lags by up to two days, you may not see this data for today or yesterday in your multi-channel funnel reports.

You also won’t see this data if not a single conversion has occurred on your website in the last 90 days or conversion tracking has not been set up in your GA view.

Introduction to Interactions (Touchpoints)

Interaction is exposure to a marketing channel. An interaction is also known as a touch.

For example, in the chart below, the visitor is exposed to six different marketing channels before he made a purchase:

interaction

Each exposure is known as an interaction in multi-channel funnel reports.

To learn more about interactions, read this article: Multi Touch Attribution in Google Analytics

Introduction to Channel Labels

Channel label is the label applied to a digital marketing channel in Google Analytics.

For example, paid search, organic search, social, display, etc. are all examples of channel labels.

There are two types of channel labels in Google Analytics:

  1. Default channel labels
  2. Custom channel labels

The default channel labels are the predefined channel labels. For example, paid search, organic search, referral, display, email, social, direct and other are default channel labels:

The custom channel labels are the labels defined by a user.

Here, ‘Paid NB Keywords’, ‘Not Provided Keywords’, ‘Paid B Keywords’, ‘Organic NB Keywords’ and ‘Organic B Keywords’ are examples of custom channel labels.

Introduction to Channel Grouping

Channel grouping is a set of channel labels.

There are two types of channel grouping in Google Analytics:

  1. Default channel grouping
  2. Custom channel grouping

The default channel grouping is the set of predefined channel labels. The custom channel grouping is the channel grouping created by a user.

Defining channel labels is part of creating your own channel grouping. You can define a channel label by creating specific rules. Each rule is based on one or more conditions.

Note: You can create as many channel groupings as you want.

To learn more about defining your own channel labels and channel groupings in general, check out the following articles:

#1 Default and Custom Channel Grouping in Google Analytics Explained

#2 Understanding MCF Channel Groupings in Google Analytics

#3 Using Custom Channels to understand Google Analytics Reports

Conversion Path Analysis

You can analyze a conversion path by changing its primary dimension in the ‘Top Conversion Paths’ report:

channel-path

You can switch to the following 17 primary dimensions to analyze your conversion paths:

  1. MCF channel grouping path
  2. Source/medium path
  3. Source path
  4. Medium path
  5. Campaign path
  6. Campaign (or source/medium) path
  7. Keyword path
  8. Keyword (or source/medium) path
  9. Adwords campaign path
  10. Ad group path
  11. Adwords keyword path
  12. Ad content path
  13. Matched search query path
  14. Placement domain path
  15. Placement URL path
  16. Display URL path
  17. Destination URL path

All of these dimensions are pretty self-explanatory, and if you play with them, you can get a pretty good idea of how they can be used to analyze a conversion path.

You can access the last 13 dimensions by clicking on the ‘Other’ drop-down list in your Top Conversion Paths report:

others

Segmenting Conversion Paths

You can segment conversion paths through conversion segments.

They are just like the Google Analytics custom segments but are meant especially for multi-channel funnel data.

Fig.6

Through conversion segments, you can isolate and analyze specific subsets of conversion paths.

There are two types of conversions segments:

  1. Default conversion segments
  2. User-defined conversions segments

So if you want to see all of those conversion paths where the first interaction was ‘paid search’, then select ‘First Interaction is Paid Advertising’ from the ‘Default Segments’ and then click on the ‘Apply’ button.

Similarly, if you want to see all of those conversion paths where the first interaction was ‘Facebook’, then create a new user-defined segment named ‘First Interaction is Facebook’ by clicking on the link ‘create new conversion segment’ (see Fig.6 above) and then click on the ‘Apply’ button.

Read this article to learn more about creating user-defined conversion segments: 8 Google Analytics Conversions Segments you Must use

Note: You should look at your multi-channel funnel reports in an unfiltered view. A filtered view can corrupt your conversion path data. Use ‘Conversion segments’ instead of filtered views.

Understanding First click and Assisted Conversions

Many marketers/analysts still evaluate the performance of a marketing campaign according to the number of conversions it completed. This is a sub-optimal way of evaluating the performance of a marketing channel.

If a marketing channel is not directly completing a conversion, maybe it is assisting in conversion, or maybe it is initiating the conversion process. So before you discard or label a marketing channel as ineffective or over-invest in any particular channel determine the following things:

  1. The number of conversions initiated by the marketing channel (first click conversions).
  2. The number of conversions assisted by the marketing channel (assisted conversions).

For example, both display and email are poor cousins of search marketing campaigns. This is because they generally don’t get the credit for completing a conversion. But they do/can help in initiating or assisting a conversion.

So before you label these channels as ineffective or under invest in them, look at the number of assisted conversions in your Assisted Conversions report from these channels.

Remember, in the case of multi-channel marketing, no one marketing channel is solely responsible for conversions. Multi-Channel marketing is just like a football game. The success of the game depends upon the whole team. 

Conversion Values

conversion volume value

In multi-channel funnel reports, there are three types of conversion values:

  1. Assisted conversion value
  2. Last click or direct conversion value
  3. First click conversion value

The assisted conversion value is the total economic value of assisted conversions.

The higher the assisted conversion value, the more important a marketing channel is in assisting conversions.

The last click or direct conversion value is the total economic value of last interaction conversions.

The higher the last click conversion value, the more important a marketing channel is in completing conversions.

The first click conversion value is the total economic value of first click conversions.

The higher the first click conversion value, the more important a marketing channel is in initiating conversions.

How Assisted/Last click conversion of a marketing channel is calculated and what insight you can get from it?

This ratio is calculated as:  number of assisted conversions / number of last-click conversions

assited last click

#1 If the value of this ratio is close to zero, then it indicates that the marketing channel functions primarily in completing conversions.

#2 If the value of this ratio is close to one, then it indicates that the marketing channel functions equally in both assisting conversions and completing conversions.

#3 If the value of this ratio is more than one then it indicates that the marketing channel functions primarily in assisting conversions.

How First/Last click conversion of a marketing channel is calculated and what insight you can get from it?

This ratio is calculated as: number of first click conversions / number of last-click conversions

first last click

#1 If the value of this ratio is close to zero then it indicates that the marketing channel functions primarily in completing conversions.

#2 If the value of this ratio is close to one then it indicates that the marketing channel functions equally in both initiating conversions and completing conversions.

#3 If the value of this ratio is more than one then it indicates that the marketing channel functions primarily in initiating conversions.

Google Analytics Attribution Reports

Google Analytics provides the following attribution reports:

  1. Model Comparison Tool (also known as the Attribution Model Comparison Tool)
  2. ROI Analysis – This report is available only in GA premium/360 enabled properties.
  3. Model Explorer (also known as ‘Data-Driven Attribution Model explorer) – This report is available only in GA premium/360 enabled properties.

You can access these reports by navigating to Conversions > Attribution in your GA reporting view:

attribution-reports

Other Articles on Attribution Modelling

  1. How to analyse and report the true value of your SEO Campaign
  2. How to valuate Display Advertising through Attribution Modelling
  3. Understanding Shopping Carts for Analytics and Conversion Optimization
  4. 6 Keys to Digital Success in Attribution Modelling
  5. Google Analytics Attribution Modeling Tutorial
  6. How to Measure and Improve the Quality of SEO Traffic through Google Analytics
  7. How to explain attribution modelling to your clients
  8. Default and Custom Attribution Models in Google Analytics
  9. Understanding Missing Touchpoints in Attribution Modelling
  10. What You Should Know about Historical Data in Web Analytics
  11. Model Comparison Report Explained in Google Analytics Attribution
  12. Data-Driven Attribution Model in Google Analytics – Tutorial
  13. Conversion Lag Report Explained in Google Analytics Attribution
  14. Selecting the Best Attribution Model for Inbound Marketing
  15. How to do ROI Analysis in Google Analytics
  16. Conversion Credit Models Guide – Google Analytics Attribution
  17. Introduction to Nonline Analytics – True Multi Channel Analytics
  18. Conversion Types Explained in Google Analytics Attribution
  19. Attribution Channels Explained in Google Analytics Attribution
  20. Differences Between Google Attribution & Multi-Channel Funnel Reports
  21. Introduction to TV Attribution in Google Analytics Attribution 360
  22. Conversion Credit Distribution for Attribution Models in Google Analytics
  23. Conversion Paths Report Explained in Google Analytics Attribution
  24. Attribution Model Comparison Tool in Google Analytics
  25. Touchpoint Analysis in Google Analytics Attribution Modelling
  26. Attributed Conversions & Attributed Revenue Explained in Google Attribution
  27. Which Attribution Model to use in Google Analytics?
  28. Google Attribution Access and User Permissions – Tutorial
  29. Conversion Path Length Report Explained in Google Analytics Attribution
  30. How to set up a data-driven attribution model in Google Analytics
  31. View-Through Conversion Tracking in Google Analytics
  32. Offline Conversion Tracking in Google Analytics – Tutorial
  33. How to Create Custom Attribution Model in Google Analytics
  34. 8 Google Analytics Conversions Segments You Must Use
  35. You are doing Google Analytics all wrong. Here is why
  36. How to Use ZMOT to Increase Conversions and Sales Exponentially
  37. Connected Properties Explained in Google Analytics Attribution
  38. Marketing Mix Modelling or Attribution Modelling. Which one is for you?
  39. How is attribution modelling helpful for ecommerce and non-ecommerce websites?
  40. Conversion Time & Interaction Time Explained in Google Analytics Attribution
  41. How to Allocate Budgets in Multi Channel Marketing
  42. How Does Attribution Work?
  43. Data-Driven Attribution Model Explorer in Google Analytics
  44. Introduction to Attribution Beta – Attribution Project in Google Analytics

Frequently Asked Questions About Google Analytics Attribution Modelling

What are acquisition channels?

Also known as ‘marketing channels’, ‘digital channels’ or ‘channels’ are the sources of traffic to your website. For example: Paid search, Organic Search, Direct, Social Media, Email, Affiliate, Referral etc are all examples of acquisition channels. In multi-channel funnel reports, the acquisition channels are commonly referred to as marketing channels or channels.

What are multi-channel funnel reports in Google Analytics?

Through multi-channel funnel reports you can determine: 1) How marketing channels work together to create conversions. 2) How much time elapsed between visitors’ initial interest and his purchase 3) What role did prior website referrals, searches and ads played in a conversion. 4) How to attribute conversions to a marketing channel.

What is multi-channel funnel conversion visualizer’?

Through ‘multi-channel funnel conversion visualizer you can visualize how different marketing channels are working together to create conversions.

What is Assisted Conversion Report?

This report shows the number of conversions each marketing channel initiated, assisted and completed. It also shows the value of assisted and last interaction conversions.

What is Top Conversion path report?

Top Conversion Path Report shows all of the unique conversion paths that lead to conversions. It also shows the number of conversions from each path and value of those conversions.

What is Path Length Report?

Path Length Report shows the number of interactions it took for your website visitors to convert.

What is a Conversion Path?

A Conversion Path is the sequence of interactions (clicks, visits, impressions) with digital marketing channels during the 1 to 90 days period that lead to conversions.

What is a lookback window?

The period of 1 to 90 days prior to conversions is known as the ‘Lookback Window’. The lookback window is available in all Multi-Channel Funnel reports and you can change the setting by dragging the slider.

What is multi-channel funnel data?

Multi-channel funnel data is a combination of conversion data and conversion paths and is compiled from un-sampled data. Since the multi-channel funnel data collection lags by up to two days, you may not see this data for today or yesterday in your multi-channel funnel reports. You also won’t see this data if not a single conversion has occurred on your website in the last 90 days or conversion tracking has not been set up in your GA view.

What is an interaction/touch in multi-channel funnel reports?

Interaction is an exposure to a marketing channel. Interaction is also known as ‘touch or touchpoint’. Each exposure is known by the name of ‘interaction’ in multi-channel funnel reports. Google Analytics can record up to 5000 interactions per conversion path. 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.

What is Channel Grouping?

Channel grouping is a rule-based grouping of marketing channels. Channels groups are created for two main reasons: 1) To change the way Google Analytics label and aggregate the incoming traffic for advanced data analysis. 2) To quickly check the performance of a set of marketing channels or set of traffic sources.

What is a conversion segment?

They are just like the Google Analytics custom segments but are meant especially for multi-channel funnel data. Through conversion segments, you can isolate and analyze specific subsets of conversion paths. There are two types of conversions segments: 1) Default conversion segments 2) User-defined conversions segments.

What is Attribution Modelling?

Attribution modelling is the process of understanding and assigning credit to marketing channels that eventually leads to conversions.

Why is attribution modelling important?

Attribution Modelling is important because it helps you to understand the buying behavior of your website visitors. Why do people buy from my website? What happens before they buy? What prompted them to make a purchase or complete a predefined goal? The biggest insight that you can get from attribution modelling is that you can determine the most effective marketing channels for investment.

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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.

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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.

About the Author

Himanshu Sharma

  • Founder, OptimizeSmart.com
  • Over 15 years of experience in digital analytics and marketing
  • Author of four best-selling books on digital analytics and conversion optimization
  • Nominated for Digital Analytics Association Awards for Excellence
  • Runs one of the most popular blogs in the world on digital analytics
  • Consultant to countless small and big businesses over the decade
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