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 of those channels—but if you’re here, then you likely know that 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.
How important is attribution modeling in a marketing campaign?
Making a sale or having a positive interaction with a user is great, but businesses are not built off of single interactions. If you want to grow, then you’ll need to understand the series of events that led to the interaction, so you can replicate it.
The basic measurements to understand your customer’s journey are touchpoints, or interactions, between your brand and your customers. This is what an attribution model does for you.
You likely can think of a few touchpoints off the top of your head, like social media or Google ads. But they also include things like product reviews and interactions between customers and customer service.
When looked at in a sequence, touchpoints tell a story. For example, if several customers read a blog post, then subscribe to your service or buy your product, you know you should replicate whatever made the blog post successful.
Understanding what led to an interaction is especially important when planning and executing marketing. It helps you understand where your customers are coming from and the most effective ways to communicate with them.
What are the types of attribution models in marketing?
You can make your marketing even 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 what 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’re interacting. 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.
For example, 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 assigns 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 its focus is 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.
Knowing what the last event was before conversion is valuable for any marketing team. It narrows down the conversion to a specific interaction that 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 non-direct click attribution gives complete conversion credit to the last non-direct touchpoint so that 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 that are 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, then 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. Whereas 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%. There are also W-shaped models that 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 that is tailored to the company’s product and current marketing strategy. However, you need to have a large amount of data for custom attributions to be effective. And even then they can be difficult to create and optimize for your exact needs.
Pair your unique brand with the right attribution model
You’ve done your homework and understand the different types of attribution models, but do you know which one is right for you yet?
If you said no, then don’t worry. 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.
How Bitly can help with attribution modeling in marketing
Even at their simplest, attribution models take time to develop and use well. However, that means your valuable data sets and insights are going unnoticed and unused for longer.
But attribution modeling doesn’t have to be overwhelming—here’s how Bitly can help.
Link tracking
If your business has any type of digital component, then link tracking is a simple but vital tool to help you understand how customers are reaching it.
Bitly makes link tracking easy by attaching unique codes, also known as parameters, to the ends of links. So when someone is directed to your site, you can track which link sent them there. Then you can record which marketing channels are the most effective and which strategies need to be reworked for better performance.
Data analytics
Deciding which attribution model is right for you is just the first step to using them effectively. After all, once you have the data from your model, you’ll need to organize it, review it, and then pull out the most valuable information.
Bitly makes that easy by recording and reporting on engagement metrics and each step of your customers’ journeys—all in one place. With Bitly handling the creation and presentation of your data, you can spend more time acting on it and making your digital marketing even more effective.
Attribution insights
Bitly goes even further than just compiling and presenting your data. In fact, Bitly can help you fine-tune your attribution model by providing insights into how well it reflects your customers’ journeys, from first click to last interaction.
With Bitly short links, users get a wide range of analytics tools, helping businesses keep tabs on their digital marketing efforts across social media and other channels. Bitly also offers seamless integration with widely-used marketing tools like Khoros, Salesforce, and Twilio which enhances Bitly’s functionality even further.
No matter how well you know your current conversion path, as your business grows, your customers and how you reach them will change too. Bitly can help you stay on top of what’s working, as well as what your data is trending towards.
Campaign improvements
Bitly can also help improve your campaigns through A/B testing, backed by link tracking and analytics.
A/B testing is vital for optimizing your current and future marketing campaigns. But to do it effectively, you need an easy way to track and assemble the data you receive from the tests.
Bitly’s Link Management and analytics make it easy to do just that by tracking the responses to every iteration of your A/B tests. That means you can easily try out everything from minute iterations of your tone to different logos and banners to see what your customers respond to.
Elevate and optimize your marketing efforts with Bitly
Finding an attribution model that accurately measures each channel that contributes to your customers’ journeys is a challenge. But Bitly makes it simple to track each touchpoint that leads to conversion through our easy-to-use link tracking, so you get the full story behind each conversion.
Find your perfect Bitly plan to see how we can optimize your digital initiatives today!