Six marketing attribution models help you understand conversions. Various marketing attribution models assist in understanding conversion drivers. Last-click attribution credits the final touchpoint, while first-click highlights the initial engagement. Linear models distribute credit evenly across all touchpoints, and time-decay gives more credit to recent interactions. Advanced models like data-driven attribution use machine learning to allocate credit based on actual conversion impact, providing a comprehensive view of the customer journey.
Want to make sure you’re fully understanding your customer journey and making the most of your resources? Learn about six of the most common attribution models to use.
Why Attribution is Important to Marketers
A common challenge for many marketers is taking care of in-depth analytics. Chances are, you’re using several channels to market products or services. How do you know which channels are performing well and which ones aren’t?
Is the dramatic increase in traffic to your site from a piece of content you just published or a Facebook ad? Which of your marketing channels caused an increase in conversions that led to additional revenue?
Without proper attribution, you’re only looking at vanity metrics like the number of comments that are linked shares. To gauge the success of your marketing campaign, you have to go deeper and look at things such as how a lead first came in contact with your content, and what pushed them to make a purchase.
Proper marketing attribution allows you to study the entire customer journey of how a person went from a lead to a paying customer, which helps you determine what is working. Maybe your Facebook ads aren’t converting it all, so you’re better off pausing your campaign and reworking your strategy. Or perhaps you’re getting a high return on investment from email marketing, in which case you would want to do more email outreach because you know it works.
Without using marketing attribution to help you see the touchpoints that are contributing to your business growth, you’ll keep wasting time and energy on resources that are not providing a positive ROI.
Let’s take a look at some of the most common attribution models along with the pros and cons of each one so you can determine which model is best for your business and marketing channels.
Using a first touch attribution model, you give credit to the channel that first directed a lead to your product or sent a visitor to your website.
For instance, if a lead was first introduced to your website through a Facebook ad, and then clicked a link on your site that sent them to a webinar. At the end of the webinar, they subscribe to your email newsletter and then later converted to your email outreach. The credit for that conversion would be attributed to the first touchpoint, which is the Facebook ad rather than the email outreach.
The idea behind this attribution model is that many conversions occur at the end of the funnel, but they wouldn’t have been possible without the first touchpoint. This type of model is not usually the best option for B2B because there are generally a lot of touchpoints involved before a lead converts.
Last Touch Attribution
The last touch attribution model is similar to the first touch model, but in this instance, instead of measuring what the lead first came in contact with your business, it attributes the entire sales process to the last touch or the end of the marketing funnel. This is generally the default setting in the majority of attribution models. If you rely on Google Analytics, this is the default attribution model. This approach focuses on what drove the lead to convert and ignores everything before the conversion.
With linear attribution, you’ll get a more complete overview of everything that happened between the beginning of the funnel to the end where the lead converts. With this approach, the middle of the final is no more important than the beginning or the end of the funnel because it gives everything equal importance. This model is easy to set up and can be used to compare results from other data models because you don’t have to worry about which touchpoints should receive credit for a conversion. The only real issue with this approach is that, in reality, not all touchpoints are created equally.
Also known as the u-shaped attribution model, the position-based model gives credit to three main touchpoints. 40% goes to the first and last touch, while the remaining 20% goes to the middle touch. Emphasis is on the first touchpoint because it is the primary impact where the leads come in contact with your business and the last touchpoint because it is the point at which the lead converts.
In marketing, the first and last touchpoints are generally the most important, but this doesn’t mean you should neglect any middle touchpoints. The middle touchpoints may be having an impact that is necessary for conversion.
This model is a good approach because, unlike the first and last touch attribution models that place importance on just one aspect of the data, the u-shaped model provides equal significance for both values. This is not a good approach to use when the first or last touchpoint is not as important. As you do your analysis, you should always check if the first touchpoint is as crucial as the last.
If you have a long sales cycle or a campaign that has to nurture leads, you should avoid using this model. Instead, save it for when the lead engages with your content and decides almost immediately that they want to use the product or service you offer.
This method is the most accurate way to measure a customer journey from prospect all the way through to conversion. This model’s success rate is higher than the others because it’s uniquely created for the business. Depending on the tool you use, this process may be done quickly by manually entering the parameters or using machine learning.
In this approach, you can give credit to the touchpoints that matter most of your business instead of providing equal credit to the first, middle, and last touchpoints. It gives you the most accurate data from the customer journey. However, this process is complexed and involves a variety of calculations so you may need the skills of a data analyst along with more powerful and advanced tools. As such, the tools may not be available to smaller businesses since they are often pricey.
If you have a short and straightforward sales cycle, using the algorithmic attribution model is not ideal for you. If, on the other hand, you have a long and complicated sales process that involves both marketing qualified lead and sales qualified lead reporting, the algorithmic model is the perfect option for you because it allows you to conduct in-depth analysis at each stage of the funnel.
With the Time-Decay attribution model there is more significance to the touchpoints that are closer to where the conversion occurred then at the top of the funnel. This attribution model is similar to the linear model but is a multi-touch model that gives more credit to the middle and the bottom of the final. It represents them as being worth more because they are the points that drove the conversion.
Which ones do you use and why? I’d love to hear your thoughts.