6 Keys to Digital Success in Attribution Modelling


Today I am going to share with you the ‘6 keys to success’ in attribution modelling. Learn my tricks and tips and your success in attribution is guaranteed.

  1. Understand Customers Purchase Journey
  2. Understand the concept of ‘Missing Touch Points’
  3. Fix Data Integration issues
  4. Go beyond Google Analytics
  5. Understand not all “touch points” are equally valuable
  6. Use Proportional Multi Touch Attribution Model


1. Understand Customers Purchase Journey

Understanding customers purchase journey is the no.1 requirement to fixing the attribution problem. If you fail to understand your customers then you have already lost the attribution battle. Well not just the attribution battle but almost every other battle in the business and marketing world.

I have broken down this journey into following steps:

  1. Interview your client, customer support and the sales people.
  2. Understand the decision making process
  3. Understand ZMOT
  4. Use data from ‘Google Think’
  5. Do Proper Market Research


Interview your client, customer support and the sales people

Your client and his staff know more about their business and industry than you ever will. So it is imperative that you leverage their industry expertise and get a better understanding of their target market.

Ask following questions:

1. How do you define your target audience (age-group, gender, education, income, likings, ethnicity, lifestyle etc) and where majority of them live?

2. Who are your best customer types in terms of revenue generation and why?

3. What kind of relationship you want to build with your target audience?

4. What are the desires and expectations of your target audience?

5. What is the level of product use? Are your customer loyal to you?

6. What are the most common objections raised by your customers?

7. Who are the actual decision makers (who has the final say)?

8. What are the buying triggers?

(A trigger is an event that causes a person to get into a serious buying mode.

For example you might have a vague interest in going to Seattle. This might have caused you to browse the web for hotels, flights etc. But an upcoming Mozcon event could act as a trigger that makes you seriously look for hotels and flights. )

Ask as many questions as you like. I have just given you few examples.


Understand the decision making process

Start your analysis by understanding the decision criteria framework of your customers.

In case of fast moving consumers goods (like toothpaste, milk, soap, vegetables etc which are bought frequently) least amount of consideration and evaluation is involved before making a purchase.

It is highly unlikely for someone to visit half dozen reviews websites, product comparison and coupon websites just to make an informed decision on buying a toothpaste.

Often in case of FMCG products, people already know what they want to buy. They already have set decision criteria in their mind (like certain model or make). So they just go to the store and make a purchase straightaway.

However they are many products/services which require lot of consideration and evaluation before a purchase is made as they are bought occasionally. Often in case of such products,

the decision criteria framework cannot be established quickly because of ever changing specifications which results in a  long sales cycle.

For example:

People don’t buy a new car ever week. So when they do think of buying a new car, there are not really sure what they are looking for in the new car.

So they need to do lot of research just to determine the ideal specifications of their new car. Once they have determined their ideal car’s specifications they have established their decision criteria framework.

Once the decision criteria is set, consideration and evaluation begins to take place and ZMOT occurs.


Understand ZMOT

There is no attribution without understanding ZMOT

Zero Moment of Truth or ZMOT is the moment which occurs after the customer has been exposed to your brand, but before a purchase is made.

It is the moment when the customer do research and make decision about buying your product by going back and forth between various digital and non-digital channels known as ZMOT sources:


Since 84% of all shoppers use ZMOT sources in the path to purchase (source: Google Think Insight),

you need to find ZMOT sources and optimally allocate your marketing spend across them.

You need to determine that if you invest in multiple ZMOT sources, then how much incrementality does each ZMOT source can bring to your company’s bottomline.

ZMOT is the most powerful moment in a customer journey to purchase as it shapes the consumer’s purchase decision. And

 If you fail to understand your customers at ZMOT, you have already lost the attribution battle

To know more about ZMOT and its importance, please read this amazing article: How to use ZMOT to increase Conversions and Sales exponentially


Use Data from ‘Google Think’

Google Think Customer journey to online purchase is an excellent tool to understand how certain acquisition channels assist conversions in your industry and how the length of the customer journey impact the order size.

For example:

Before you create your own attribution model, you need to understand the role of acquisition channels in your industry:


As seen in the graph above, within the tech industry, direct and ‘other paid’ interactions often act more as a last interaction.

The organic search acts both as assist interaction and last interaction.

Whereas display, social and email act more as an assist interaction.

Without such understanding, you could negatively impact your brand awareness if you dump campaigns which play key role in initiating conversions.


Do Proper Market Research

By ‘proper’ I mean, investing considerable amount of time and resources in conducting the research.  Market research is an excellent way of understanding your customers.

Conduct surveys, do A/B testing (see what works and what doesn’t work), hire a market research agency.

Buy market research and industry reports from companies like Experian and read them from page to page. The level of insight that you will get from such reports is unparalleled.


2. Understand the concept of ‘Missing Touch Points”

Both Google Analytics and Google Adwords attribution modelling is based on only ‘known’ touch points, i.e. the users’ interactions which can be tracked and reported in analytics and adwords.

Thus there is no guarantee, that your users’ conversion paths contain all touch points and provide complete picture of customers’ purchase journey.

I have explained the concept of missing touch points in great detail, in the article: Understanding Missing Touch Points in Attribution Modelling


3. Fix data integration issues

Data integration is the key to fixing attribution issues

You should always aim to minimize the number of missing touch points in your conversion path by integrating as much data as possible from different data sources.

To learn more about minimizing the number of missing touch points in a conversion path, read this article: Understanding Missing Touch Points in Attribution Modelling


4. Go beyond Google Analytics

Attribution is much more than Google Analytics.

It easily goes beyond Google Analytics. Don’t limit yourself by just using the GA attribution tools.

You are not limited to just what you can achieve through Model Comparison Tool and Multi-channel funnel reports. There are lot of attribution modelling softwares out there which can provide much more robust attribution solutions than Google Analytics.

You should definitely consider them esp. if you are a big company. In the end only custom made attribution tools can minimize attribution issues as they provide:

1.  Robust data integration capabilities

2.  Robust data forecasting platform

3.  More flexibility in terms of creating attribution models and applying credit rules.

4.  Customized solutions as each business is different


5. Understand not all “touch points” are equally valuable

In a conversion path, not all touch points can be equally valuable.

The acquisition channel which assists the most should get the maximum credit for conversion and maximum resources are allocated to it regardless of it being the first touch, last touch or middle touch. All other touches should get credit in proportion to their contribution in the conversion path.

I have explained this concept in great detail, in the article: Touch Point Analysis in Google Analytics Attribution Modelling


6. Use Proportional Multi Touch Attribution Model

I am suggesting this model not because I developed it but because it is incrementally better than all the attribution models out there.

Following attributes make this model by far the best attribution model in the world (ok that’s an exaggeration 🙂 )

1. Proportional multi touch is the first generation of real world attribution model.

Because of that property it has the ability to provide truly complete picture of the conversion path followed by customers. It is the first generation of truly multi-channel analytics modelling tool.


Source: Selecting the Best Attribution Model for Inbound Marketing

 2. Proportional Multi Touch takes into account your business model, marketing objectives, sales cycle, customers’ activities and seasonality as it allows you to assign credit to different marketing channels/touch points (both online and offline) in proportion to their contribution in the conversion process.

Thus it provides more flexibility than linear, position based and time decay models ever will in terms of credit distribution.

3. The usage of proportional multi touch model goes beyond Google Analytics as it is not just a digital model.  Because of this property it faces less issues of ‘missing touch points’ than the traditional Google Analytics models.

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Quick Announcement about my new books

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Book #1: 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.

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Himanshu Sharma

Certified web analyst and founder of OptimizeSmart.com

My name is Himanshu Sharma and I help businesses in finding and fixing their Google Analytics and conversion issues.
  • More than ten years' experience in SEO, PPC and web analytics
  • Certified web analyst (master level) from MarketMotive.com
  • Google Analytics certified
  • Google AdWords certified
  • Nominated for Digital Analytics Association Award for Excellence
  • Bachelors degree in Internet Science
  • Founder of OptimizeSmart.com and EventEducation.com
I am also the author of the book Maths and Stats for Web Analytics and Conversion Optimization If you have any questions or comments please contact me