Master Guide To Marketing Attribution Models To Grow Your Business

As a Digital Marketer, you would be using multiple channels to market your business including Google, Facebook, Email etc. It’s important for you to know which sources are performing and at what level during the customer journey.

Marketing attribution helps you to understand the journey of customer touch points in detail,  which further helps you to optimize marketing mix and drive more value from your marketing efforts.

This article will guide you in understanding marketing attribution, the types of marketing attribution and which one to choose to grow your business!

Let’s get started!

So What is Marketing Attribution?

Marketing Attribution is the process of identifying set of users action in the form of events or touch points which leads to a conversion or sale.

In simple words, it’s the action taken by the user during the journey of a sale from seeing an ad to buying the product.

Different Types of Marketing Attribution Models!

  1. First-Touch Attribution Model
  2. Last-Touch Attribution Model
  3. Linear (Even Weighted) Attribution Model
  4. Time-Decay Attribution Model
  5. U-Shaped or Position Based Attribution Model
  6. W-Shaped Attribution Model
  7. Algorithmic Attribution Model

Let’s understand each one in details!

1. First-Touch Attribution Model

First-Touch attribution model also known as the first click attribution model, which gives all credit to the first click/first touch, that leads a user to a website.

First Click Attribution Model

This model is applicable to the users if they don’t fill up a form or subscribe or purchase on the website. This model helps you to understand the entry source of the customer on your website which is also driving value to your business.

If you go first-touch attribution model, you actually don’t know which other touch points contributed to a conversion in the journey. So it’s not that helpful, to review the key factor which generated conversion.

First-touch attribution model can be used when your objective is awareness and driving visitors to your website, in this case you want to know from where the users are entering your website. If you are looking to understand the conversion funnel, I won’t recommend going with first-touch attribution model

2. Last-Touch Attribution Model

Last-touch attribution model is also known as last click attribution model. In this model the entire credit is given to the last click which generated a conversion or a sale.

Last Click Attribution Model

Most of the marketers go with his model because they want to know which keyword generated conversion or which website generated conversion or through which source the actual conversion happened.

This model will completely focus on the last touch point. But you won’t understand which other touch points were part of the customer journey, because to you, they would also be equally important to understand and optimize them in the funnel.

You should look for “Last Non-Direct Click” on Google Analytics to measure the effectiveness of the campaign, here it ignores the direct click

3. Linear (Even Weighted) Attribution Model

A Linear attribution model gives equal credit to all the touch points in the customer journey. In this model we are able to understand all the touch points which actually generated conversion or sale, this helps us to further define our marketing strategy.

Linear Attribution Model

The only challenge with this model is that we actually don’t know which touch point was the major contributor to the final action, who ideally should get the maximum credit.   

I would go with linear attribution model if my objective is to understand what all touch points are generating sales. Through this I know all customer touch points which are driving value to my business and I can further optimize them.

4. Time Decay Attribution Model

Time decay attribution model gives maximum credit to the touch point which was closer to the point of conversion. It gives different values to each touch point from the point of interaction to the point of conversion with the last touch getting the maximum and the first touch getting the minimum, refer below. Time Decay Attribution Model

This model ignores what touchpoints actually directed a visitor to a website or business. It’s not a recommended attribution model.

5. U-Shaped or Position Based Attribution Model

U-shaped attribution model is also called as position based attribution model. In this model, the first touch and the last touch is credited with 40% each as the value and the remaining 20% is divided between the other touch points.

U Shaped Attribution Model

In this model, all the touch points get credit, whereas first and last touch points are considered as the key drivers for action, so they are credited with 40% each as the credit.

The other touch points between first and last are also important touch points when we are looking at the consumer journey, so giving credit to first and last ignores the importance of other touch points, as they are equally important for the action to happen. Won’t recommend with going U-Shaped or Position based attribution model.

6. W-Shaped Attribution Model

W-shaped attribution model is similar to U-shaped attribution model. But in W-shaped model, the credit is given to the touch point where a user is converted to a lead. This action takes place somewhere in the middle of the journey, hence it is known as W shaped attribution model. The remaining credit is divided between the other touch points other than first and last.

The three touch points are credited with 30% value for each and the rest of 10% is credited to the remaining touch points.

W Shaped Attribution Model

Won’t recommend this model as each and every touch point is getting a credit but the remaining one’s are credited with a lower value, ideally everyone should get equal value.

7. Algorithmic Attribution Model

Algorithmic attribution model also known as custom attribution model is an attribution model where you can custom set the credit value for each touch point basis your understanding. I have defined credit value for each touch point as below, as I want to give a bit higher credit to the first touch point as it starts the consumer journey and then I have given low credit to rest of the touch points which are in between the first and last touch point. Finally, for the last touch point I have given maximum credit, as that touch point is driving the action. Algorithmic Attribution Model
In order to set up this model, you would need a developers help to do so. Also basis the results you have to keep optimizing the efforts. It’s one of the best from the above all but would need technical guidance to setup, which might also consume some time.

So How to choose the right marketing attribution model for your business?

It’s important to select the right marketing attribution model for your business because basis multiple touch point data you would effectively optimize your marketing efforts leading to higher ROI. Below are a few factors which you should consider before selecting the attribution model for your business.

1. Sources Contributing To Action

Check the sources which are contributing to actions. Google analytics help you to understand which sources are performing for your website. Have a look at the below sources which show how each source is performing.

Google Analytics Sources

2. Check Different Touch Points For Conversions

Check different touch points which are part of the consumer journey prior to the conversion. Google analytics allows you to check the multiple touch points of the journey.
Google Analytics Assisted Conversions

3. Time To Convert Users

Know how much time it takes for users to convert post their first interaction with your business. This will help you to understand the duration and then you can mapp it with different touch points in the entire journey.

Google analytics helps you to understand the time to convert users under time lag report.

Time Lag in Google Analytics

4. Define Campaign Objective

Define campaign objective which will help you to choose the right attribution model for your business. If your objective is to generate awareness for your brand, then first touch attribution model is effective to measure the entry point for your customer.

If your objective is leads or sales, you can go with last touch or linear attribution model. If you go with last touch, it will help you to identify the last touch which is driving maximum results, basis which you can effectively optimize the touch point.

If you are going with linear, which I also prefer because, it helps me to understand each touch point in the entire consumer journey, which further helps me to build an effective strategy focused on each touch point.

5. Run Experiments & Optimize

Every touch point in the journey has a role to play, so you need to experiment continuously with different strategies including your ad copies, bidding strategies, targeting aspects etc so that you know how significantly it’s helping you to improve your conversions on a regular basis.

Attribution Modeling Tools 

1) Google Analytics:

Google Analytics is a widely-used web analytics platform that offers basic attribution modeling capabilities. It provides various attribution models, including last-click, first-click, linear, time decay, and more. Users can also create custom attribution models to suit their specific needs.

Pros: It’s free for most users, integrates well with other Google products, and offers a user-friendly interface.

Cons: Limited flexibility for advanced attribution modeling.

2) Adobe Analytics:

Adobe Analytics is an enterprise-level analytics solution that provides advanced attribution modeling capabilities. It offers a wide range of predefined attribution models and allows customization to create complex, data-driven models.

Pros: Powerful and flexible, suitable for large enterprises, and provides deep insights into customer behavior.

Cons: High cost, complex setup, and not as user-friendly as some other tools.

3) Attribution Software (e.g., Bizible, Convertro):

Attribution software solutions are specialized tools designed for advanced attribution modeling. They offer features like multi-touch attribution modeling, revenue tracking, and integration with various marketing platforms.

Pros: Tailored for attribution modeling, robust reporting, and customization options.

Cons: Costly for smaller businesses, may require a learning curve, and integration with existing systems can be complex.

4) CallRail

CallRail is a marketing analytics and call-tracking tool that focuses on providing insights into offline and online interactions, with a primary emphasis on tracking and attributing phone calls to marketing campaigns. It helps businesses understand the impact of their marketing efforts on phone call conversions. While CallRail primarily specializes in call tracking, it plays a significant role in attribution modeling, especially for businesses that rely heavily on phone leads and conversions. Here’s an explanation of CallRail’s features and its role in attribution modeling:

Key Features of CallRail:

  1. Call Tracking: CallRail enables businesses to assign unique phone numbers to different marketing channels, campaigns, or even individual ads. When a customer calls one of these numbers, CallRail records the call and tracks its source, allowing you to attribute conversions to specific marketing efforts.
  2. Dynamic Number Insertion (DNI): CallRail offers DNI, which automatically replaces the phone number displayed on your website with a tracking number based on the visitor’s source, such as a Google Ads click or an organic search.
  3. Keyword Tracking: It can track which keywords drove phone calls, particularly valuable for understanding the performance of your pay-per-click (PPC) campaigns.
  4. Source Attribution: CallRail provides insights into which marketing channels, campaigns, or keywords are responsible for driving phone calls and conversions. This data is crucial for attribution modeling.
  5. Recording and Transcription: The tool records phone calls, allowing you to review them for quality assurance and gather additional insights. It also offers transcription services to make call content searchable and analyzable.
5) DreamData

Dreamdata is a marketing attribution and revenue analytics platform designed to help businesses understand and optimize their marketing efforts by providing detailed insights into the customer journey and attributing revenue to specific marketing channels, campaigns, and touchpoints. Here’s an explanation of Dreamdata and its role in attribution modeling:

Dreamdata is a marketing attribution and revenue analytics platform designed to help businesses understand and optimize their marketing efforts by providing detailed insights into the customer journey and attributing revenue to specific marketing channels, campaigns, and touchpoints. Here’s an explanation of Dreamdata and its role in attribution modeling:

Key Features of Dreamdata:

  1. Multi-Touch Attribution Modeling: Dreamdata allows you to create advanced attribution models that go beyond the traditional last-click attribution. You can assign value to multiple touchpoints across the customer journey, such as clicks, views, and interactions, to understand how each contributes to conversions.
  2. Data Integration: The platform integrates with various data sources, including advertising platforms (Google Ads, Facebook Ads), CRM systems, analytics tools, and payment processors. This data integration enables a comprehensive view of your marketing and sales data.
  3. Revenue Attribution: Dreamdata specializes in revenue attribution, providing insights into how marketing activities impact revenue generation. It connects marketing efforts to actual revenue, helping you assess the true return on investment (ROI) of your marketing campaigns.
  4. Predictive Analytics: Dreamdata employs predictive analytics to forecast future revenue based on historical data and trends. This feature helps marketing teams make informed decisions and allocate resources effectively.
  5. Account-Based Marketing (ABM) Attribution: For B2B businesses, Dreamdata offers ABM attribution capabilities, allowing you to attribute revenue and engagement data to specific accounts, making it ideal for account-based marketing strategies.
  6. Custom Attribution Models: You can create custom attribution models tailored to your business goals and unique customer journey characteristics. This flexibility enables you to account for the complexity of your marketing funnel.
  7. Campaign Tracking: Dreamdata enables granular tracking of individual marketing campaigns, ad creatives, keywords, and other variables, providing a detailed understanding of which specific elements contribute to revenue.
  8. Cross-Device Attribution: It helps you track user interactions and conversions across different devices and platforms, ensuring that you account for the full customer journey

Conclusion:

Selecting the right marketing attribution model is important for your business, this will help you to effectively improve your performance and reduce marketing efforts for all the touch points in the entire consumer journey. Set up your marketing attribution model today and let me know how much value it’s adding to your business!