What is Attribution Modeling and Why It’s Important

Attribution modeling is the process of assigning credit to conversions and other desired actions that occur on your website. This credit can be assigned to different marketing channels, campaigns, ad groups, or even individual ads. There are many different attribution models, but not all models are created equal. The chosen model should be based on your specific business goals and objectives. In this blog post, we’ll give you an overview of the most popular attribution models and how they can be used to achieve your marketing goals.

Why is Attribution Modeling Important?

In the digital marketing sphere, attribution modeling serves as an evaluation framework. It helps marketing and analytics teams determine which marketing activities drive the most leads in different sales funnel stages. Thanks to attribution models, marketers can:

1. Optimize spending by redirecting the budget to the marketing efforts that work better
2. Design and implement marketing campaigns tailored to their buyer personas and their journeys
3. Figure out the efficiency of your channels and touchpoints and estimate ROIs
4. Gain a deeper understanding of the buyer’s journey and highlight the parts that need improvement

As you can see, attribution modeling drives results for your marketing and tells you which areas need more work and which are running strong.

Types of Attribution Models

There’s no single attribution model that your business should use. Here’re the most common attribution models to consider.

1. 1. First-touch attribution model. The first-touch attribution model gives credit for a conversion to the first marketing touchpoint a customer has with your brand. This could be an ad they saw, an email they received, or a search engine result they clicked on.This model is helpful for marketers who want to identify the best channels for introducing and raising brand awareness about your product or services. Also, it’s suitable for businesses with longer sales cycles that aim to establish long-term connections with clients.Proponents of this model argue that without that first touchpoint, the customer would never have been exposed to your brand and, therefore, would never have converted. Therefore, all credit for the conversion should be given to that initial touchpoint.

      However, critics of this model argue that it fails to consider the role that subsequent touchpoints play in the customer’s journey. Just because a customer saw your ad first doesn’t mean they would never have converted if they hadn’t seen it; it’s entirely possible that another touchpoint further down the line was what finally tipped them over the edge and convinced them to buy from you.

   2. Last-touch attribution model. The last-touch attribution model is basically the opposite of the first-touch model; instead of giving credit for a conversion to the first marketing touchpoint, it gives credit to the last one. So if a customer saw your ad, clicked on a search engine result, visited your website, and finally made a purchase, the last-touch attribution model would give all credit for the conversion to that final purchase.

1. 1. Linear attribution model. The linear attribution model splits credit evenly between all of the marketing touchpoints that led up to a conversion. So using our earlier example, if a customer saw your ad, clicked on a search engine result, visited your website, and finally made a purchase, each one of those touchpoints would get 25% credit for the conversion.

1. 1. U-shaped attribution model. The U-shaped attribution model is a linear model that attributes credit equally to all touchpoints in the customer journey. This means that each touchpoint gets equal credit regardless of whether it’s the first, second, or third touchpoint that a customer interacts with. One of the benefits of the U-shaped attribution model is that it’s easy to understand and implement. However, because all touchpoints are given equal credit, this model doesn’t provide much insight into which touchpoints are actually driving conversions. As a result, you may waste resources on touchpoints that don’t impact your bottom line.

1. 1. W-shaped attribution model. The W-shaped attribution model is more sophisticated and gives more credit to initial and final touchpoints while giving less credit to middle touchpoints. This means that the first and last touchpoints in the customer journey are given more weight than touchpoints in the middle of the journey. One of the benefits of this model is that it provides more insight into which touchpoints are driving conversions. This allows you to focus your resources on the touchpoints that actually impact your bottom line. However, the W-shaped attribution model can be more difficult to understand and implement than other models.

1. Time-decay attribution model. The time-decay attribution model gives more credit to recent marketing touchpoints than to older ones. So using our earlier example again, if a customer saw your ad 30 days ago, then clicked on a search engine result 10 days ago, then visited your website 5 days ago, and then finally made a purchase today, more credit would be given to the visitors to your website (5 days ago) than to the initial exposure to your ad (30 days ago).
2. Position-based attribution model. The position-based attribution model splits credit equally between two touchpoints: the very first one and the very last one. So using our earlier example once again, if a customer saw your ad first, then clicked on a search engine result second, then visited your website third, and then finally made a purchase fourth, each one of those touchpoints would get 25% credit for the conversion — the ad would get credit for being seen first. The purchase would get credit for being made last.
3. 
4. Custom attribution model. Suppose none of these existing attribution models seem quite right for your business. In that case, you can always create your own custom attribution model! This involves defining your own rules for how credit should be assigned — for example, you might give more weight to certain channels (such as paid ads) or periods (such as when somebody is close to making a purchase.) Creating a custom attribution model requires some technical expertise — you’ll need access to detailed data about every single step in the customer’s journey — but it can be well worth it if it helps you better understand which marketing channels are driving conversions for your business.

There are pros and cons to each type of attribution model. Last-touch attribution is often criticized for being too simplistic and not considering other touchpoints’ role in the conversion process. First-touch attribution has a similar problem: it doesn’t give credit to touchpoints later in the conversion path. Linear attribution is often seen as the most balanced approach, but it can be difficult to implement effectively. The bottom line is that there is no one-size-fits-all solution for attribution modeling; your business’s best approach will depend on your specific goals and objectives.

Data-Driven Attribution Model

We’ve already listed the most popular attribution models. However, we’d like to focus on the most widely used — data-driven attribution model. It relies on data from Google Analytics (or another similar platform) to determine which marketing channels deserve credit for driving conversions. To do this effectively, you need access to detailed data about every single step in the customer’s journey — including how long they spent on each page and what actions they took while there.

With this information, you can use algorithms or machine learning techniques to determine which channels deserve credit for driving conversions.

Data-driven attribution modeling is thought to be the future of marketing. This is because it has several advantages over other attribution methods, such as last-click or first-touch attribution. Perhaps the most important advantage is that data-driven attribution can consider a much wider range of factors than other methods. This means you can get a more accurate picture of which touchpoints are driving conversions.

Another advantage of data-driven attribution is that it can be used to attribute credit across multiple channels. This is important because customers nowadays engage with businesses across multiple channels (e.g., website, social media, email) before making a purchase. Finally, data-driven attribution can be used to attribute credit across multiple devices. This is important because customers may start their journey on one device (e.g., desktop) but then switch to another device (e.g., mobile) before making a purchase.

So if you’re looking for a more accurate way to measure your digital marketing efforts, consider using data-driven attribution modeling. This approach uses machine learning algorithms to analyze data from multiple touchpoints along the customer journey to identify the most important conversion drivers. This information can be incredibly valuable when it comes time to allocate your marketing budget or resources.

Data-Driven Attribution Model in GA4

If you’re using Google Analytics 4 (GA4), you’re lucky—data-driven attribution is built right into the platform! GA4 uses machine learning algorithms to automatically attribute conversions and other events to the channels that drove them.

There’re two main reports in Google Analytics 4 when getting started with data-driven attribution.

The first report in GA4 is the Model Comparison, which allows you to compare different attribution models. This helps determine what type of data would best suit your company’s needs and ensures that everything matches up accordingly.

Source: optimizesmart.com

The second report is the Conversion Path report, which visualizes early, mid and late touchpoints. This data will be used to create an engaging picture for you with cross-channel attribution model calculations at top display on your screen.

Source: support.google.com

This report is a colorful visual representation that will allow you to see which channels are bringing in new customers easily. The data visualization shows how many conversions occur per day and at what time during the sales process they happen; it also tells us about any assist windows or touchpoints where prospects may have been exposed for longer periods before making their purchase decision final – all based on our research into who clicks through those ads.

Attribution Modeling Tools

There’re a few tools that help marketing teams with attribution modeling.

1. 1. Google Analytics. The first and most obvious tool is Google Analytics. It provides great insights that could be used for attribution modeling. By default, Google Analytics has the last touch attribution model, but you can change it easily through the settings. Using Universal Analytics, you can go to the Attribution section on the left sidebar and create a new project.

      Source: Google Analytics

      If you use the updated version — Google Analytics 4 — you’ll take advantage of more advanced attribution features. All you need to do is go to Admin and Attribution Settings. Besides choosing one of the default attribution models from GA settings, you can also create custom attribution models. However, if you want an easier approach, you can also use multi-channel Google Data Studio dashboard templates.

Further reading: Why Migrate to Google Analytics 4 in 2023?

Source: searchengineland.com

1. 1. 1. Attribution.This is a multi-touch attribution tool that helps you understand the impact of each of your marketing touchpoints. The tool automated data collection using many integrations with ad software, marketing tools, and more. The attribution modeling process is also automated, and you can segment attribution results by touchpoint, channel, marketing campaign, and more.

1. 1. 1. Windsor.ai. This is an integrated marketing analytics platform that helps marketing specialists evaluate the effectiveness of their campaigns. The tool uses Google Analytics to provide a detailed report to its users. So if you use Windsor.ai, you automatically take advantage of Google Analytics.

1. 1. 1. Wicked Reports. This software for attribution modeling is predominantly used by eCommerce marketers. It can calculate ROI and LTV for every ad, campaign, and channel to understand the impact of each marketing touchpoint. Wicked Reports provides in-depth and accurate data across all business platforms, including eCommerce, marketing platforms, Google, and Facebook.

How to Choose the Right Marketing Attribution Model for Your Business?

Attribution models are designed to fit the needs of different companies regardless of the size and industry they belong to. The main question is how to select the right marketing attribution model. Here’re some things to consider and recommendations from us:

1. 1. • Company size and available resources. Take into account the size of your company and what technological and human resources you can allocate to attribution models. Since attribution modeling relies on data analysis, having an in-house analytics team or hiring a digital marketing agency to help you out is essential.
      • The length of the sales cycle. For long cycles, it’s recommended to use the first-touch attribution model. For a short one, it’s better to use the last-touch attribution model.
      • Consumer journey complexity. You should consider choosing a multi-touch attribution model for complex buyer journeys with multiple touchpoints, such as the W-shaped or U-shaped.
      • Offline marketing attribution. This is a complicated scenario common with businesses that have offline components (for example, a store).To use a marketing attribution model for the offline part of your buyer’s journey, you should have a CRM mechanism to identify the offline buyer with their online persona.

Boost Your Marketing Attribution Strategy

Attribution modeling is vital for understanding how marketing efforts impact business goals. There are many different attribution models, each with its advantages and disadvantages. The best approach for your business will depend on your specific goals and objectives. By following some simple best practices, you can ensure that your attribution model is as effective as possible.

Contact our data analytics team if you’re unsure where to start. We’ll get in touch with you as soon as possible and discover the best attribution model.