Marketing attribution models are the key to unlocking the mysteries of online customer behavior. By understanding how customers interact with your website and marketing channels, you can fine-tune your strategies to improve your conversion rate and bring in more revenue.
This article will break down what marketing attribution modeling is and how it works. We'll then dive into one type of model: linear attribution. We'll cover the pros and cons of this type of marketing attribution model so that you can make a confident decision about how to best track your customers' interactions with your website.
What are marketing attribution models?
A marketing attribution model is a system that calculates the amount of credit for a conversion you should give to one or more marketing channels. Attribution models are important because they help businesses understand how customers interact with their brand. By understanding which channels are most effective at driving conversions and bringing the most revenue, businesses can focus their efforts on those channels and improve their conversion rate.
The are two main categories of attribution model: single-touch and multi-touch. Single-touch models give all the credit to a single marketing channel, while multi-touch models give credit to multiple channels. Credit is weighted differently across the channels, depending on a set of rules or algorithms determined by the model you use. Linear attribution is a type of multi-touch model.
How does the linear attribution model work?
At its core, linear attribution modeling is a way of assigning equal credit for conversions to different channels or marketing touchpoints. That means that all the credit for a conversion is given to each of the channels that were used before the conversion. For instance, if a customer clicks on a search ad, then an Instagram ad, and then visits your website several times before converting, linear attribution would give equal credit to each channel in this process.
Let's work through a few examples.
Customer journey A:
interacts with a PPC text ad on Google
interacts with a Google shopping ad
interacts with your website via a blog post and, from the blog post, signs up for your mailing list
receives a welcome email with a discount code, clicks to your online store, and makes a purchase with the code
In this instance, there are four touchpoints, so each one gets 25% of the credit for the sale.
Customer journey B:
interacts with an ad on Instagram and immediately makes a purchase
There's only one touchpoint in this journey, so it gets 100% of the credit for the sale.
Customer journey C:
interacts with an Instagram ad
interacts with a Google shopping ad and makes a purchase from the ad
In this case, both the Instagram ad and the Google shopping ad each get 50% of the credit for the conversion.
Pros and cons of linear attribution
The main advantages and drawbacks of linear attribution are linked to the fact that it's a multi-touch model. However, there are some nuances in linear attribution compared with other multi-touch models.
Linear attribution takes into account multiple touchpoints
Multi-touch attribution models are becoming increasingly popular because they offer a more accurate picture of how modern customers interact with your business. Now it's normal for potential customers to interact with a brand across several different channels. For instance, through the brand's owned channels like SMS, email, or website, as well as through organic search and social media.
A single-touch attribution model can be misleading because it gives all the credit to a single marketing channel that was used. This can lead businesses to mistakenly focus on only one channel when in reality, other channels may have played a role in the customer's purchase decision.
Linear attribution models take into account all of the channels that were used before a conversion occurred. This gives businesses a complete picture of which channels are most effective at driving conversions and allows them to allocate their resources more effectively.
However, there are some drawbacks.
It's hard to track the customer journey across multiple marketing channels
First of all, as with all multi-touch models, it's difficult to actually know which channels a customer has interacted with. New privacy laws and the advent of the "cookieless future" make it even more difficult to track and target users. This makes linear attribution more difficult to implement than a single-touch model like last-click attribution.
That said, just because it's difficult to track the touchpoints a customer goes through, it doesn't change the fact that data on the customer journey is highly valuable. Even though it’s complicated, multi-touch attribution is still a great way to get insights into your marketing performance so you can improve your marketing strategy.
Linear attribution assumes all touchpoints have the same level of impact
Another limitation of linear attribution is that it assumes all touchpoints are equally influential, but this might not be the case. For many businesses, the ads and channels customers interact with directly before making the purchase have the biggest impact.
Let's say blog posts explaining the different use cases of your product play a role in influencing potential customers. However, it's the bottom-of-the-funnel PPC ad campaign showing a discounted price is what finally pushes people to buy. In this kind of situation, a brand might opt to use a time decay model or last-click attribution (the standard model in Google analytics) over a linear model. That’s because, in this case, models that emphasize the touchpoints closer to conversion better reflect their sales funnel.
When should you use linear attribution?
There is no definitive answer to this question, as linear attribution may be a good fit for some businesses but not others. Overall, linear attribution models offer some key advantages in terms of tracking the customer conversion path and understanding where your marketing efforts are paying off. It's useful if you want to get a balanced overview of how all your channels are performing.
However, if your advertising is more narrowly focused on one specific part of the funnel, it might be better to use a single-touch model like first-click or last-click attribution. There are also other multi-touch models to consider, for instance:
U-shaped or position-based attribution model. The u-shaped attribution model takes into account all the channels that were used before a conversion occurred, but it gives more weight to the channels at the start and the end of the journey.
Time decay attribution model. This model focuses more on the touchpoints that happen close to the conversion and gives them greater weight.
Data-driven attribution. This is the most advanced model, as it uses machine learning to give each touchpoint a weight based on how well it performed.
Custom attribution model. As the name suggests, this model allows you to set your own weights for each touchpoint based on your own business goals and how you want to allocate your marketing resources.
Regardless of which model you choose, the key is to remain data-driven and continuously iterate your marketing strategy based on the insights you get from your attribution data.
Try out more than one model to find what works for you
Ultimately, linear attribution is just one of many multi-touch attribution models out there. It's a great starting point for businesses that want to get more insights into how their marketing channels perform, but in the end, it might not be the perfect fit for your business.
So if you're looking for a better way to track your customer journey and get insights into how you can improve your marketing strategy, consider experimenting with some of the other attribution models out there. Read our guide to all the different types of attribution models that includes advice about when to use which model.