In the tutorial, we will take a look at the attribution models used by Google Analytics.

In an ideal world, we would want our visitors to click on one of our ads or blog posts and convert into a lead almost instantly.

In the real world, the purchase made on a website is the result of a buyer’s journey during which there are a sequence of interactions with your website that take place within a given time frame.

In Google Analytics, an interaction (also known as ‘touchpoint’ or just ‘touch’) is an exposure to a marketing channel, while, the sequence of interactions that lead a customer to conversion, is called conversion path.

In a conversion path, channels can have three roles:

• First Interaction: First referral (or initiator) on the conversion path.

• Assist Interaction: Any non-last referral on the conversion path.

• Last Interaction: Immediately preceding the conversion referral.

Note: Google Analytics Google relies on cookies to record up to 5000 interactions per conversion path for up to 90 days.

Let’s look at an example of conversion path that involved many channels.

Kate wants to buy a chair for her home office.

• Interaction 1 (Organic Search)

  Kate Googles “comfortable office chair,” looks at some pages on yourofficechairs.com, and leaves.

  3 days later,

• Interaction 2 (Social Network)

  Kate sees an article on Facebook that mentions how comfortable your chairs are. She clicks the link to yourofficechairs.com and looks at the recommended chairs.

  7 days later,

• Interaction 3 (Paid Search)

  Kate Googles “chairs for home office” and sees your ad. She clicks it and completes the purchase.

The conversion path would look like this:

The example above raises three kinds of analysis:

1. Conversion Paths

How many interactions lead to conversion?

How long takes to conversion?

2. Channel Interactions

Which channel interaction is most responsible for nudging the user to convert?

3. Attribution Model

Which of these marketing channels should the conversion be attributed to?

We can answer to these questions using the Multi-Channel Funnels reports in Google analytics, under the Conversions menu.

How many interactions lead to conversion? #

There are two report within the Multi-Channel Funnels that help you to answer this question:

• Path Length

• Top Conversion Paths

The Path Length Report tell you how many interactions with your site leads to a conversion.

Looking at the picture above, we can see that 28% of all conversions occurred after more than one channel interaction, also, 57% of all conversion value occurred after more than one interaction.

Now you know how many interactions you need to have with a visitor before they convert. But which channel comes first (“introduces our brand to the customer”), which channel comes second (“nurtures our potential customer”), which channel comes fourth, fifth … and last. You can use the Top Conversion Paths report.

If it takes many interactions to convert on your site, it important to determine how many channels it takes to convert. You can use the Top Conversion Paths report.

The Top Conversion Paths report give you a list of every combination of channel interactions that led to a conversion.

Most likely, the paths will be very diverse: 3%-5% of visitors followed the top path. But there are still actionable trends you can obtain from this report.

Start off by identifying the ideal conversion paths through which users are converting most.

We can take the data here a step further and look at which “Source Path” are assisting the conversions by using filters to drill into the data.

From the Top Conversion Path report, add a secondary dimension for “Source Path.”

source: https://searchengineland.com/drilling-into-top-conversion-paths-for-valuable-insights-150383

The next step to analyse the conversion path is to see how long your customers takes to convert. You can use the Time Log report.

….

Which channel interaction was most responsible for nudging the user to convert? #

The Venn diagram in the muti-channel visualizer report give you on the overview of how the various channels interact with each other.

But let’s get more details about various channel interactions and see where they fall in the funnel. That’s the job of the Assisted Conversions report.

Look at the last column: “Assisted/Last Click or Direct Conversions”. I like what Justin Cutroni calls it: the “Exposer to Closer Ratio”.

This metric tells you which traffic sources are Exposers, meaning they spread your brand message, and which ones are Closers, meaning they get people to convert.

“A value close to 0 indicates that this channel functioned primarily as the final conversion interaction. A value close to 1 indicates that this channel functioned equally in an assist role and as the final conversion interaction. The more this value exceeds 1, the more this channel functioned in an assist role.” – Brian Clifton in Advanced Web Metric

Note: The channels with value greater than one, are getting zero credit in last click attribution platforms.

Who gets the credit for any revenue created? #

Well, that will depend on the attribution model.

Attribution may sound complicated but in simple terms, comes down to assigning credit of each consumer interaction that led to the conversion.

“Attribution means dividing the value of an online sale (or conversion) and distributing fractions of that value across the different interactions that led to the sale.” – ThinkwithGoogle, in measure-what-matters-most

There is a tool inside the Multi-Channel Funnels called Model Comparison Tool.

To understand how to use this tool need you have a basic understanding of the difference between the attribution models and the limitations of each of these.

Let’s have a look at the most commonly attribution models using the below conversion path as a reference.

• 1. First Interaction/Click

  All the credit for a conversion goes to the first interaction.

  

  

• 2. Last Interaction/Click

  All the credit goes to the last interaction.

  

  

• 3. Linear

  Conversion is attributed equally to all the interactions.

  

  

• 4. Time decay

  Recent interactions are given more credit than older ones.

  

  

• 5. Position Based

  Credits are given based on the specific position of the interactions.

  

  

Google Analytics uses, in all of its reports, the last click attribution model with an important exception: If the last interaction is ‘direct’, GA remembers the previous interaction and attributes all the credit to that.

In our example this model would say all credit goes to Paid.

But is that right? There are various channels involved in conversion without which conversion would not have taken place.

That’s where the Model Comparison Tool comes in so handy!

The Model Comparison Tool allows you to compare the attribution models and see how they impact the valuation of your marketing channels.

For example, what if we used a time decay attribution model instead of last click?

Essentially, we’re splitting up the revenue of the orders among the touch points that lead to the conversion, and rewarding the channels differently based on the model.

Look at the last column called ‘% change in conversion (from last interaction)’, we see a 16.7% increase in conversions for Paid Search if we consider the time decay model compared to the last click attribution model.

In other words, ‘Paid Search’ is undervalued under the last-click attribution model (when this model is compared with the ‘data-driven’ attribution model).