Attribution Model - Best Marketers Tool( Review )

Hey, Marketers out there, it is pretty much easy to develop an e-commerce website that you want to earn money.

But it is much more important to be aware of which marketing channel is contributing ROI to you.

So, you spend a lot on UX and design stuff, prepare good content, publish Ads through a paid platform or organic platform, or any social platform.

All these you create to get conversions from each platform. It may be for generating leads, adding to your cart, or making the final sale.

This all leads you to understand the fundamental concepts of how your marketing channels are working.

The case is, it won't result in a single-end conversion process at all times.

Rather it is to calculate on each of these channels depending on the type of attribution model you choose.

If a customer is seeing your Ad in organic platform, clicks and get in your site but not purchasing. And next time the same person clicks your remarketing Ad that you made, go in and buy a product on your site.

Then the channel which led to conversion is not the only Ad shown in the organic platform. It must give credits including the remarketing platforms that traveled along.

So, the Value of the conversion shares among both of these channels,

Ad in organic platform + Ad in the remarketing platform.

Both of these channels give credit to the conversion which happened.

The above is a simple glimpse of how the conversion occurs. But this isn't necessary to be the same for a standard way of calculating conversion.

CXL Institute has given me a good idea to think deeper about how this attribution model is working.

Let us get in to know more...

What is Attribution?

Attribution is actually the concept change that's required.

It's a psychological shift in how you actually understand the value of a customer.

Thus it's less about the math, and it's more about how you change the way that you understand.

It's in the way that you're marketing is changing the way that it impacts customers.

The important thing you need to understand is,

" What do you want to get from Attribution? "

So, when coming to analytics, it is important to have skill sets from "People and Resources" required to use attribution.

It is very easy to signup with new technology and sign up for a new way of working.

But actually using the outputs to change the way the organization running, is the key thing that you need to think.

Here is now to discuss deeper on how this attribution model is list into 7 important types.

• First interaction
• Last interaction
• Last non-direct interaction
• Linear Attribution
• Time decay
• Position-Based Attribution
• Custom Attribution Model

Let us understand each one this model with examples deeper.

1. First interaction

This model explains the credit given to the "First Touch-point", and it defines the same way.

For instance, if a customer finds your site on Facebook first time and clicks. Then your 100% credit goes to the Facebook platform.

Even if the same customer clicks your remarketing ads through email, and they buy a product, it will not give credit to your last click of conversion.

So in here, the credit goes to the first click a customer does.

2. Last interaction

This model is quite opposite to the first interaction model.

Here consider the same scenario...

The customer makes conversion through the remarketing ad in the email which he received.

So, the first click on his Facebook doesn't get in the count, instead, the 100% credit goes to the last click he did (i.e. Email).

3. Last non-direct interaction

In this model, it again shows a small difference than the last click model.

Let us understand through a scenario,

When the customer clicks your ad for the first time in Pinterest and goes.

Then a week later he is prompt through your another Ad in say Google PPC.

And next, he receives your Ad through Email and buys your product.

This means... your Last non-direct click will lead to traffic in Google PPC Ad which he saw.

In clear terms, it rejects the Last interaction happened. It shows the previous interaction of the Last interaction that occurred.

Google PPC receives 100% credit!

4. Linear Attribution

In this model, the credit gets shared among the platforms which had the touchpoints.

Take the previous scenario...

so three touchpoints involved in the previous case,

• Pinterest - 33.33%
• Google PPC - 33.33%
• Email - 33.33%

As I'd Mentioned, credits for conversion get shared among these platforms.

5. Time Decay

This model modifies the Linear attribution on a timely basis.

i.e, The channel which pays the most time as a reason for purchase will get the highest credit.

Consider the previous case...

Out of Pinterest, Google PPC, and Email,

The Email will get the most credit compared to other platforms which led to the conversion.

6. Position-Based Attribution

This model gives you an understanding of giving credit to the first and the last touchpoint.

It is also called the "Bath-Tub" Model were the first and last touchpoints receive 40% and 40%.

Rest 20% applies between the two interactions.

This model gives you an understanding of the challenge of Acquisition and Conversion.

7. Custom Attribution Model

Here, you as a marketer will set each touchpoint to have a different value.

This model is Super-dangerous because...

As a Marketer saying this has much value without the context of what actually is important to the customers.

The other side of custom attribution is the Algorithmic Output.

So, this is where you use basic algorithms through to more complex algorithms.

You'll use Logistic Regression, all the way through to Machine learning. It will put data back through the system and give it the ability to train.

And you can also learn what values are important.

All these models have their own kind of advantage and it is most valued when we choose a proper model.

P.S: As a wise marketer, you must know to choose the right model that suits your organization. Understand the value of conversion each model is making.

Additional resource--------> Detailed explanation of Attribution models

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