Attribution modeling is the process of using different strategies (a.k.a. models) to measure how effective marketing campaigns are at driving conversions.
Attribution modeling is used in marketing attribution, which is the process of assigning credit for each conversion to the marketing activity that drove it. Different attribution models allow you to measure the effects of those activities in different ways so you get a clear picture of your campaign effectiveness.
Choosing which attribution model works best for your unique brand, client, or goal can be daunting. That’s why we're going to simplify things. Here, learn about the most common attribution models, what they’re best for, and the limitations of each to keep in mind.
Attribution modeling uses different strategies to measure the effects of marketing channels and campaigns on driving specific actions you want a customer to take, called conversions.
Customers interact with your brand on many different channels and at many different moments in time. These interactions are called touchpoints. Marketing attribution strives to assign credit to different touchpoints in the customer journey for a particular sale or conversion. So what is an attribution model? It’s a framework for assigning this credit.
There are many different attribution models your brand can use, depending on your business, product, and goals. We’ll explain the pros and cons of each below. But no matter which model you choose, the exercise will help you allocate marketing resources appropriately.
There are many benefits of using attribution models that can ultimately help propel users through your sales funnel and improve profit. Here are some examples of the purpose of attribution modeling.
From acquisition to retention, marketers need to understand the effects of each digital marketing channel. Attribution modeling helps you do this by evaluating which channels are most effective at driving desired customer outcomes.
And you can do this at a pretty granular level. For example, let’s say you run a fashion business. You can use ecommerce attribution models to identify which channels are most effective in driving conversions for each product you sell. This allows you to customize your marketing efforts for each product, resulting in a more effective overall strategy.
After you’ve identified which channels are working and which are not with your attribution model, you can allocate your resources more effectively. By analyzing the customer journey and which channels are driving conversions with different attribution models, marketers can determine which channels should receive the most budget and adjust their ad spend accordingly.
Continuously assessing the results of your attribution modeling means you’re always learning and always improving. As you apply your model to changes you’ve made to your creative and your strategy, you’ll get more feedback on how well those tweaks are working out. Then, you can adjust again, in a cycle of learning, implementing, analyzing, and improving.
The information you gather on your customer’s habits and behaviors as part of the attribution modeling process comes in handy when you’re creating personalized marketing campaigns to engage your customers and make them more likely to convert.
There are several different methods for attribution modeling, each of which assigns credit to different touchpoints in the customer journey in a different way. Let’s unpack some of the common digital marketing attribution models below.
Single-touch attribution models, also called single-source attribution, give credit for a conversion to just one touchpoint, either the first or the last.
Deciding to use one of these models often comes down to what you value more: the metaphorical salesperson who brought the customer into the store or the one who closed the deal.
Also known as first-click attribution, this model allocates all the credit for a conversion to a customer’s first touchpoint with your brand. Let’s say they first saw your ad on Facebook, then searched for your business on Google, and then made a purchase. A first-touch attribution model will give all the credit for that sale to Facebook.
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Sometimes also called last-click attribution, this is the opposite of first-click attribution: All of the credit for a conversion is given to a customer’s final touchpoint with your brand. If, like in the example above, your customer first saw your ad on Facebook, then searched for your business on Google, and then made a purchase, a last-touch attribution model will give all the credit for that sale to Google.
Last-touch attribution is the most common attribution model used in the marketing world. It focuses on the closer, so to speak. You can envision it as a game of soccer: It only credits the player who scored the goal, not the other players who set up the play.
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In contrast to single-touch attribution, multi-touch attribution (also called fractional attribution) gives credit to every touchpoint in the customer journey from first to conversion.
But there are different ways to assign or spread this credit across all these touchpoints.
A linear attribution model gives all the touchpoints on the customer journey the exact same credit for the purchase.
If your customer first saw your ad on Facebook, then read your email newsletter, then searched for your business on Google, and finally made a purchase, all of those interactions would be given equal weight for the conversion.
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The time decay attribution model gives more weight to touchpoints that happened closer to the conversion. In the example above, the customer’s Google search would get more credit for the ultimate purchase than the Facebook ad. This makes a certain amount of sense, as we all usually remember more recent events more vividly.
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These models assign different weights to specific touchpoints based on where they occur during the customer journey.
There are three kinds:
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This method is all about utilizing statistical algorithms to assign values to different touchpoints. Like all algorithms, it gets “smarter” the more data you feed it.
One common type of algorithmic attribution is incremental attribution, which strives to identify the conversions that wouldn’t have happened if it weren’t for specific touchpoints and credit those touchpoints accordingly.
If your customer first saw your ad on Facebook, then read your email newsletter, then searched for your business on Google, and finally made a purchase, you’d use machine learning to determine the credit to assign to each of those touchpoints.
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This is a specific type of algorithmic model you can find within Google Analytics. It’s supported by historical data to accurately attribute conversions to each channel.
Like with other algorithmic attribution models, machine learning helps assign credit to each touchpoint in a customer journey.
To find these reports, log into Google Analytics and select the “Attribution” tab. From there, you can view all of your attribution reports in one place.
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Your business can also create rules for credit distribution that work best for your unique business needs or customer journey. A custom attribution model is best for brands with specialized marketing approaches and unique considerations. Book a demo today to see how Triple Whale can help you personalize your attribution model.
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Imagine you're hosting a party, and each guest brings their unique vibe to the event. Instead of just focusing on individual guests, cross-channel attribution models look at everyone at the soirée.
In marketing, that means looking at how all your different marketing channels influence a customer’s chances of converting.
Marketing channels like email, social media, SEO, and pay-per-click are all VIP guests at your party, and together, they make the night a success.
Customers often interact with your brand across these and other channels. Each touchpoint plays a key part in their journey toward a conversion. By considering all these interactions across multiple channels, cross-channel attribution provides a more realistic and accurate picture of your customer's journey. It helps you understand how your marketing channels work together, so you can better allocate your resources and optimize your strategy.
Sometimes the time between touchpoints on a customer journey varies in ways that make your funnel a little less direct.
For example, imagine you’re at a party and you meet someone who tells you about a great new cafe in town. A few days later, you walk past a sign for the cafe and decide to pop in for a coffee. Would you give more credit for your purchase to the new friend’s recommendation or the sign?
In attribution language, the friend is the last non-direct click that led to a conversion, while the sign is a direct interaction.
This model takes into account all the touchpoints that a customer interacts with before making a purchase, not just the final click or interaction before buying. It recognizes that customers are often influenced by multiple marketing efforts along their journey toward making a purchase decision.
Direct interactions include typing your brand’s website URL directly into a browser or clicking on the site from a bookmark. Non-direct interactions include clicking through from a newsletter link, an ad, or a social media post.
In the cafe scenario above, if you only gave credit to the sign (the direct interaction), you'd miss out on understanding the whole story of how you ended up there. It's the same with marketing attribution.
This is why considering the last non-direct click is crucial for a comprehensive understanding of conversion paths. It helps to reveal the actual journey that leads to conversions, especially in scenarios where direct interactions are not the final touchpoint. The key is to understand how these channels work together, not in isolation, to drive conversions.
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So far, we haven’t accounted for offline channels that can drive conversions, such as billboards or radio ads. Marketing mix modeling or MMM assigns credit to every touchpoint, whether it’s digital or not. MMM typically also takes seasonality, economics, and other external factors into account.
For example, you might use MMM if your business relies on a wide range of marketing channels, like digital marketing, TV commercials, print media, discounts, social media campaigns, and in-person activations.
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With Triple Whale, you get access to what we like to think of as the all-inclusive package of marketing attribution. Our Total Impact Attribution Model gives you a crystal-clear picture of your ad investments and marketing performance through analysis of all sorts of data points across various channels. We use first-party data, zero-party data, and a proprietary algorithm in the new gold standard in attribution.
Some additional attribution models you might explore with Triple Whale include:
Triple attribution gives credit to the last ad the customer clicked through on the particular platform currently being viewed, like Facebook or Google. This model is sometimes referred to as “last platform click.” Each marketing channel’s final click-through for the particular customer receives credit for the purchase.
For example, let’s say your customer clicked on a Facebook ad, a second Facebook ad, and then a TikTok ad, before making a purchase. That second Facebook ad would receive credit when viewing Facebook data, and the TikTok ad would receive credit when viewing TikTok data. In this model, the final click a user makes within each ad platform is deemed the most significant.
For Facebook ad data specifically, you can try this unique attribution model that tracks both click-through and view-through data. We layer Facebook’s view-through attribution data on top of our Triple Pixel click-through attribution to see the effect of Facebook’s attribution.
For example, if your return on ad spend (ROAS) with Triple Whale’s Triple Pixel was 2.35 and Facebook’s view-through attribution added 0.5 ROAS, the triple attribution + views model will show 2.85 as your click-through ROAS.
As you can see, there are lots of different models for attribution in marketing. And there isn’t necessarily a standard attribution model to use. Instead, the key is figuring out which channels work best in your industry and for your organization, and tailoring your attribution model accordingly.
Your first decision should be between single-touch attribution and multi-touch attribution. With 52 percent of marketers using MTA, according to a 2024 MMA report, it’s fair to say it’s the most common attribution model. The report also found MTA users are more satisfied than marketers who don’t use MTA when it comes to tracking campaign spend and allocating marketing budget. That said, MTA is more complex and often more expensive than single-source attribution, so it’s not right for everyone.
Within either single-touch or multi-touch attribution, you’ll need to narrow your choices even further.
Considering the following factors can help you decide on an approach that makes the most sense for you:
Need some more support? Reach out to Triple Whale today for a demo of our attribution models and more information about how they can help you scale profitability.
Everyone faces bumps in the road to success, and there are some common pitfalls of attribution modeling you’ll want to avoid. Remember, it's all about understanding your customer's journey in its entirety, not just focusing on the final destination.
Putting all your faith in the last-click model seems easy: The last touchpoint gets all the credit, case closed! But it's not quite that simple. This model overlooks interactions your customer had on multiple other channels before converting. Multi-channel attribution modeling can more accurately capture this journey.
It's easy to forget some conversions might be influenced by IRL interactions in this very digital world we live in. But don’t discount billboards, radio ads, and other offline channels, as they contribute to your overall customer journey.
That said, keep in mind there isn’t a simple attribution model that captures 100 percent of every customer’s data, especially when it comes to cross-device tracking and offline channels.
Assisted conversions are the touchpoints that didn't directly lead to a conversion but played a vital role in the customer's journey. Undervalueing their role is like ignoring the supporting actors in a movie.
Attribution modeling isn't a “set it and forget it” kind of practice. You should regularly update and tweak your model as your audience, channels, and strategy evolve over time.
It's easy to focus on the glamour of paid search and forget about organic search. Remember, organic search efforts play a significant role in your customer’s journey, so make sure your attribution model reflects that.
Privacy concerns and regulatory pressures are driving more brands away from cookies and toward alternate tracking methods, including first- and zero-party data. If you’re not considering tracking methods that maintain customer privacy (like Triple Whale’s Pixel), you could have gaps in your data.
Attribution modeling can be easy to manipulate and different models deliver different results. Plus, without a trusty attribution modeling tool, you could introduce human error into the process. But inaccurate data will throw off your attribution, which can in turn affect how you allocate ad spend and how your business performs.
Attribution modeling isn’t static. Embracing the advancements in this dynamic field can give you a serious marketing edge. Artificial intelligence (AI), machine learning, and predictive analytics are all forms of advanced attribution modeling that we’re sure to see more of in the future.
AI can already be used to predict offline interactions your customers have with your brand that later lead to conversions using historical data and real-time signals, according to MarTech.
Machine learning-based attribution uses machine learning algorithms to dissect the customer journey, determining the importance of each touchpoint. It takes into account many variables and interactions that traditional models may overlook.
And predictive analytics use historical data to predict future outcomes, according to IBM, something that marketing attribution in general typically can’t do.
Attribution models give you a roadmap to follow when you’re carrying out the important exercise of marketing attribution so you can measure the success of your campaigns on various channels.
There is no right or wrong attribution model. The best attribution model is the one that gets you closest to the truth about your business’s success and the one that helps you make the best decisions with your resources going forward.
Armed with all this information, it’s worth comparing some attribution models that intrigue you to ensure you’re on the right path forward.
We’re here to help. Triple Whale offers attribution models for every strategy, total-impact attribution, pre-built analytics dashboards, and advanced tracking technology with Pixel. Book a demo today!
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