Today I am going to share with you the six 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 touchpoints’
3. Fix data integration issues
4. Go beyond Google Analytics
5. Understand not all “touchpoints” are equally valuable
6. Use a data-driven attribution model.

Key #1: Understand Customers Purchase Journey

Understanding the customer purchase journey is the no.1 requirement for fixing attribution problems.

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 the following steps:

1. Interview your client, customer support, and the salespeople.
2. Understand the decision-making process
3. Understand ZMOT
4. Use data from ‘Consumer Barometer with Google’
5. Do Proper Market Research

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

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#1.1 Interview your client, customer support and the salespeople

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 the following questions:

1. How do you define your target audience (age-group, gender, education, income, likings, ethnicity, lifestyle, etc.) and where do the majority of them live?
2. Who are your best customer types in terms of revenue generation, and why?
3. What kind of relationship do 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 customers 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 a few examples.

#1.2 Understand the decision-making process

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

In the case of fast-moving consumer 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 a dozen reviews websites, product comparison, and coupon websites just to make an informed decision on buying a toothpaste.

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

However, they are many products/services which require a lot of consideration and evaluation before a purchase is made as they are bought occasionally. Often in the case of such products, the decision criteria framework cannot be established quickly because of ever-changing specifications, which result in a  long sales cycle.

For example:

People don’t buy a new car every 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. They need to do a 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 are set, consideration and evaluation begin to take place, and ZMOT occurs.

#1.3 Understand ZMOT

There is no attribution without understanding ZMOT. 

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

It is the moment when the customer does research and make a 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 bottom line.

ZMOT is the most powerful moment in a customer journey to purchase as it shapes the consumer’s purchase decision. 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 article: How to use ZMOT to increase Conversions and Sales exponentially.

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

#1.4 Use data from Consumer Barometer With Google

Consumer Barometer With Google is an excellent tool to understand how certain acquisition channels assist conversions in your industry and how the length of the customer journey impacts the order size.

Without such understanding, you could negatively impact your brand awareness by dumping campaigns that actually play a key role in initiating conversions.

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#1.5 Do proper market research

By ‘proper’ I mean, investing a 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.

Key #2: Understand the concept of missing touchpoints

Both Google Analytics and Google Ads attribution modelling is based on only ‘known’ touchpoints, i.e. the users’ interactions which can be tracked and reported in Google Analytics and Google Ads.

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

I have explained the concept of missing touchpoints in great detail in the article: Understanding Missing Touchpoints in Attribution Modelling.

Key #3: Fix data integration issues

Data integration is the key to fixing attribution issues.

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

To learn more about minimizing the number of missing touchpoints in a conversion path, read this article: Understanding Missing Touchpoints in Attribution Modelling.

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Key #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 the Model Comparison Tool and Multi-channel funnel reports.

There is a lot of attribution modelling software out there that can provide much more robust attribution solutions than Google Analytics. You should definitely consider them, especially if you are a big company.

In the end, only custom made attribution tools can minimize attribution issues because 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 all businesses are different.

Key #5: Understand that not all touchpoints are equally valuable

In a conversion path, not all touchpoints 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 to the conversion path.

I have explained this concept in great detail in the article: Touchpoint Analysis in Google Analytics Attribution Modelling.

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

Key #6: Use the Data-Driven Attribution Model

The data-driven attribution (DDA) model is an algorithmic attribution model.

What that means, it uses algorithms (predictive algorithms) to find and analyze statistically significant data from multiple data sources (Doubleclick Campaign Manager, Google Ads, Google Search Console, YouTube, etc.) and then assign conversion credit to the four most influential touchpoints in a conversion path, in the last 90 days prior to conversion.

These touchpoints are reported by the Model Explorer Tool‘.

The following attributes make this model by far the best attribution model:

• The data-driven attribution model is the first generation of real-world attribution models. Because of that attribute, it has the ability to provide a better picture of the conversion path followed by your customers than any other attribution model.
• The data-driven attribution model 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/touchpoints (both online and offline) in proportion to their contribution to the conversion process. Thus it provides more flexibility than linear, position-based, and time decay attribution models ever will, in terms of credit distribution.
• The usage of a data-driven attribution model goes beyond Google Analytics. Because of this attribute, it faces fewer issues of ‘missing touchpoints’ than the traditional Google Analytics attribution models.

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