Most people think of the Amazon River as a single river that flows for 4,000 miles. In reality, it is the main channel of an even larger system, with hundreds of tributaries contributing to the flow.
Modern digital businesses are the same, but instead of tributaries adding water to a river, they are fed by digital channels that direct users toward their products.
Attribution modeling tracks the flow of each channel—but if you’re here, you likely know it’s a little more complicated than it sounds. To help, we’ve created this detailed breakdown of exactly what attribution modeling is, the different types of models, and why it matters for your business.
Note: The brands and examples discussed below were found during our online research for this article.
The role of attribution models in marketing
Attribution models are frameworks that help businesses measure the impact of various touchpoints in a customer’s buying journey. These models assign value to each interaction based on its contribution to a conversion.
Say your campaign includes a mix of inbound and outbound marketing strategies, like content marketing, social media posting, and direct mail. Attribution models allow you to pinpoint which channels are most effective in driving conversions rather than assigning equal credit across the board. These insights help you improve your overall campaign performance and optimize your budget by focusing on the touchpoints that deliver the highest returns.
In times of uncertainty, when marketing budgets are often on the chopping block, knowing where to focus your resources is crucial. That’s where marketing attribution steps in, providing the clarity you need to justify your ad spend.
Here are some key concepts related to attribution models:
- Customer journey: This encompasses the customer’s entire experience with your brand, from their first interaction to the final conversion.
- Conversion paths: Customers take these steps before completing desired actions, like making a purchase or signing up for a newsletter. They can include referrals, organic searches, and interactions with paid ads.
- Customer touchpoints: These are the various interactions between your brand and customers, like seeing Google ads, reading blog posts, and speaking with your sales team.
How important is attribution modeling in a marketing campaign?
If you want to grow your business, it’s crucial to understand the series of events that lead to a conversion so you can replicate that success. That’s exactly what an attribution model does for you.
Knowing what drives interactions is especially important when planning and executing your marketing strategy. It helps you grasp where your customers are coming from and the most effective ways to connect with them.
Attribution modeling can also enhance campaign optimization by revealing which channels and touchpoints contribute most to conversions. Do social media platforms have the highest conversion rates? Are email campaigns pulling their weight? Is your customer support driving results? Attribution modeling answers these questions by highlighting the impact of each investment.
You can even assess impact through cross-device attribution, optimizing your marketing activities by understanding customer preferences across different devices, such as smartphones, tablets, and desktops.
For instance, if you discover that most purchases occur on mobile, you can invest in push notifications to engage your audience where they’re most likely to convert. By tracking how users interact with your brand on various platforms, you can tailor your strategies to meet them at the right moment.
However, attribution modeling has challenges that can impact its accuracy and usefulness. To fully leverage these frameworks, consider the following:
- Data silos: These occur when systems or teams fail to share data, leading to fragmented customer journeys. Unify your data to avoid this pitfall.
- Attribution bias or inaccuracies: Models can sometimes overemphasize or underemphasize certain touchpoints due to inherent assumptions. For instance, if you use last-touch attribution, you might over-credit the final interaction while undervaluing earlier interactions, leading to skewed results. To avoid this, use a mix of attribution models to balance out these biases.
- Complexity in multi-touch attributions: It takes roughly eight touchpoints to close a sale, making it challenging to distribute credits accurately. Simplify this process by using tracking tools and breaking down the customer journey into manageable segments.
Different types of attribution models in marketing
You can make your marketing more precise by finding the specific type of attribution model that fits your product or service best. Here’s a quick list of the most popular models to get the ball rolling.
Cross-channel attribution modeling
Cross-channel attribution modeling assigns value to each of your marketing channels. This way, you get a high-level perspective on the role each channel plays in converting customers.
The benefit of this attribution model is that it gives you a clear picture of which channels are the most and least successful, as well as how they interact. However, cross-channel attribution can be difficult to implement. Some channels may not allow for easy data tracking due to privacy concerns or physical limitations.
Linear attribution modeling
Linear attribution modeling generates more specific data by assigning equal value to each touchpoint on a customer’s journey toward conversion.
Say a customer found your brand through a social media post and then read a blog post about your product before making a purchase. In that case, both the social media post and the blog post would receive 50% attribution toward the conversion.
Linear attribution models are useful to marketing teams who need to demonstrate where people are interacting with a brand. However, they don’t show which channels have the most impact on those journeys.
Multi-touch attribution modeling
Multi-touch attribution models assign value to each touchpoint that leads to a conversion. This is especially helpful if you’re interested in tracking through digital channels.
For example, Google Analytics makes it easy to record touchpoints and build a map that tells you if your SEO is bringing in people or if Facebook ads are doing the heavy lifting. Multi-touch attribution also shows how those channels interact based on touchpoints, which can make collaborating between channels easier.
However, multi-touch attribution is often easier said than done. It relies on data that may not be available due to website and platform data-gathering restrictions. Plus, like cross-channel attribution, multi-touch doesn’t account for traditional media, like print and TV, where metrics can’t be assigned to individuals.
First-touch attribution modeling
Unlike linear attribution, which assigns equal value to each touchpoint, first-touch assigns all value to the first touchpoint that leads to conversion.
Imagine you were marketing laundry detergent. Buying laundry detergent isn’t a large investment that requires extensive research before making a purchase. So, first-touch attribution would be helpful to understand how customers are finding the product.
However, for other products, first-touch attribution can give an incomplete picture of the buyer’s journey since it focuses completely on that first touchpoint.
Last-touch attribution modeling
Last-touch attribution modeling addresses the opposite end of the buyer’s journey by giving all credit to the last touchpoint before conversion. This approach is often referred to as ‘last interaction’ or ‘last click’ attribution, emphasizing the significance of the final customer interaction.
Knowing what the last event was before conversion is valuable for any marketing team. It narrows down the conversion to a specific interaction they can invest in and build a marketing strategy around. However, last-touch attribution only gives a snapshot of the full story.
While knowing what the customer did before buying is important, if you want a holistic look at a conversion path, you’ll need more data than last-touch attribution can provide.
Last non-direct click attribution modeling
Imagine that you’re receiving plenty of conversions, but your data is telling you that customers are going directly to your website and making a purchase immediately.
That’s where last non-direct click modeling would be most helpful. Last-click attribution gives complete conversion credit to the last non-direct touchpoint, so you know which channel is most responsible.
For example, if the customer interacted with a Facebook ad, then came back to your website days later and made a purchase, then all the credit would go to the Facebook ad.
This model allows you to focus on the events leading to conversion. However, many buyers’ journeys are more complicated than the last non-direct touchpoint, so if you rely only on this model, then you won’t get the complete picture.
Time-decay attribution modeling
If your product requires research and relationship building before conversion due to high cost or commitment, then time-decay attribution may be the best choice for you.
Think of someone buying a sports car. Their initial search will be broad as they learn more about each model and narrow down their choices. As they focus on a specific make and model, they’ll start looking for information specifically about that car before they decide to buy.
Time decay accounts for that by contributing more credit to the touchpoints later in the process rather than spreading it out equally or giving more credit to the early touchpoints.
Time decay works well for products that require a longer buying cycle. But if that’s not your product, you may miss out on key marketing touchpoints early in the process since they don’t receive as much credit.
Position-based attribution modeling
Position-based attribution, also known as U-shaped attribution, gives the majority of the focus to the first and last touchpoints while still attributing some credit to those in between.
Specifically, in position-based attribution, the first and last touchpoints both receive 40% of the credit for a conversion. Meanwhile, each touchpoint in between splits the remaining 20%. This model is a great way to apply balance to your attribution since it focuses on the first and last touchpoints while still representing those in the middle.
However, it may not work as well if there are several touchpoints between the first and last. That remaining 20% can be spread so thin that you don’t get an accurate picture of what happens between the beginning and end of the customer journey.
W-shaped attribution modeling
A W-shaped attribution model is a great alternative to a U-shaped model since it gives equal attribution to the middle touchpoint.
In a W-shaped attribution model, the first, middle, and last touchpoints each receive 25% attribution, while the remaining touchpoints split the last 25%. Some W-shaped models assign 30% to each of the three key touchpoints, with 10% left for the remaining points.
Just like a story with a beginning, middle, and end, a W-shaped attribution model tells you the complete journey from discovery to conversion. However, like the U-shaped model, key touchpoints in between the main events can receive too little attention, which means you don’t get the complete story.
Plus, W-shaped models can be complicated to create and execute, especially if your customer journeys don’t typically consist of three touchpoints.
Custom-made attribution modeling
Still haven’t found a marketing attribution model that appropriately addresses all your channels? You can always make a custom attribution.
Custom attributions work best when a business has a long conversion path that yields large amounts of data. That data is especially valuable for long buying cycles since there are more touchpoints and channels to fine-tune marketing toward.
The benefit is detailed data tailored to the company’s product and current marketing strategy. However, you need a large amount of data for custom attributions to be effective. Even then, they can be difficult to create and optimize for your exact needs.
Pair your unique brand with the right attribution model
Finding the right model for your brand takes time since each business is as unique as its products. Don’t be afraid to test different models to see how they mesh with your typical conversion path before settling on one.
While doing so, consider a few of the different factors that can influence the effectiveness of a particular model. For example:
- Are you focused on growth, or are you already at the enterprise scale?
- How much data do you have access to, and are you using marketing channels that don’t give data, like a walled-off website or traditional print/TV media?
- Lastly, consider how many steps your customers take before conversion. That number will have a significant effect on which model best suits your needs.
Elevate and optimize your marketing efforts with Bitly
Attribution models help identify the most impactful customer touchpoints, enabling businesses to replicate what works and maximize ROI. However, finding an attribution model that accurately measures each channel’s contribution to your customers’ journeys can be a challenge. To get a clear picture, investing in a reliable tracking tool is essential.
Bitly makes it simple to track each touchpoint that leads to conversion through our easy-to-use link tracking. We provide real-time data on each Bitly link and QR Code with Bitly Analytics, showing you not only how many clicks and scans they receive but also their geographic locations, operating systems, and browsers. This can give you the full story behind each conversion.
Find your perfect Bitly plan to see how we can optimize your digital initiatives today!
