How to Build a Custom Marketing Attribution Model
by Frankie Karrer
6 Min Read
8 Min Read
When you know how a customer found out about your brand, you can determine which of your marketing channels are most successful. And when you know that, you can more effectively allocate your marketing budget toward channels that are performing well and develop strategies to strengthen weaker ones.
With an omnichannel digital approach, however, it can be tricky to figure out the first part: exactly which channel ultimately led to a sale? Many customers may have seen multiple ads on different platforms before deciding to do business with you. A multi-channel attribution model, on the other hand, can give you a better sense of which marketing efforts are responsible for converting customers.
Multi-channel attribution is a marketing model that more accurately pinpoints which touchpoints ultimately lead to a conversion.
Many attribution models typically assign all of the credit to one channel, such as the customer’s first interaction or their last. The reality is more complicated, as it takes 6-8 messages to convert the average lead. Multi-channel attribution accounts for this and allows you to give credit to more than one marketing channel for each customer’s purchase.
Multi-channel attribution modeling works by assigning credit for a sale to multiple channels.
There are several different types of multi-channel attribution models that weight touchpoints differently depending on where they fall in the customer journey. But while types of multi-channel attribution models vary, there are a few important differences between multi-channel as a category and other varieties of attribution modeling.
The first-touch attribution model gives all credit for a sale to the first method in which a customer interacts with a brand. If a customer first became aware of your brand by seeing a banner ad on a website but also interacted with your pay-per-click ads and social media posts, this model would simply determine that the banner ad prompted the sale.
With multi-channel attribution, you might assign more credit for the sale to your banner ad while acknowledging that your social media posts and pay-per-click ads also contributed to the sale. The first-touch attribution model ignores other campaigns that may have influenced a customer and doesn’t always serve as an accurate assessment of your marketing success.
Like the first-touch attribution model, the last-touch model assigns full credit for a conversion or a sale to one marketing channel — in this case, the last point of contact. If the person in the example above had seen a banner ad on a website, clicked on one of your pay-per-click ads, interacted with your social media, and then saw an ad on Connected TV (CTV) before purchasing, the last-touch model would give full credit to the CTV ad.
If you’re only interested in conversions, last-touch attribution is just fine for measuring campaign success. However, it ignores other channels your customers have interacted with along their path to purchase and leaves out useful data that can give you a better view of your brand’s buyer journey.
Multi-channel attribution and multi-touch attribution are often mistaken for one another, but there are key differences between the two.
Multi-channel attribution offers a big-picture assessment of how marketing channels impact a customer’s choice to purchase. Multi-touch attribution, on the other hand, focuses on specific ad campaigns and where they fell in the sequence of touchpoints. While a multi-channel attribution model credits the channel itself (such as social media, paid searches, or video ads) for a sale, a multi-touch model would evaluate specific posts and ads (i.e. the “touch” points in “multi-touch”) within those channels.
Unlike many other attribution models, multi-channel attribution lets you assess your marketing efforts across platforms. Instead of measuring success in terms of conversions, this model helps you understand how your marketing efforts work together as a whole.
For example, a multi-channel attribution model may show you that your video ads aren’t driving conversions, but they are effectively driving engagement on your website. With this information, you might tweak your video ads to focus on building brand awareness and reputation.
Multi-channel attribution gives you clear insights into your marketing efforts, allowing you to set marketing budgets effectively and develop more successful campaigns.
There are six common multi-channel attribution models you can use to credit different marketing channels; each model is defined by how it weights/credits various channels in your overall mix.
Linear attribution assumes that every potential customer interaction with your brand is equally responsible for making the sale. With this model, you credit each channel evenly. For example, if a customer saw five ad campaigns through various channels, this model would assign 20% credit to each.
The U-shaped attribution model assumes that a customer’s first and last interactions are most responsible for guiding a sale. With this model, you would give 40% credit to a customer’s first touchpoint, 40% to the last, and allocate the remaining 20% to all touchpoints in the middle.
This attribution model assumes that a customer’s final few interactions with your company drive their decision to buy. With this model, you would allocate more credit to a channel the more recently the customer viewed it (with the first touchpoint getting the least credit). For this model to be accurate, you need to understand the sequence in which a customer has interacted with your ads.
The W-shaped model gives equal credit to the first touch a customer has with your company, the last touch, and their main lead generation activity. Lead generation is the point in the customer journey where they actively express an interest in your company, such as signing up for a newsletter, scheduling a sales call with a representative, or ordering an informational brochure. In this model, the first, last, and lead generation points each get 30% of the credit for the sale, while the remaining 10% is divided among the other touchpoints.
Full path attribution measures the entire customer journey, including each time they interact with your company. Instead of assuming which parts of their journey are most responsible for a sale, this method allocates credit with actual data. With this model, you would measure key performance indicators at every step of the customer’s journey and give credit based on the data.
This method is a more robust and accurate method of measurement, but it is complex and can take a lot of time to master.
The custom attribution model allows you to allocate weight to various marketing channels however you see fit. You might choose this model if you have a good understanding of your customers and their behavior, or if you have a lot of analytical data.
Follow these steps to implement your chosen multi-channel attribution model.
Before you can decide which attribution model is best for you, you need to understand your customers. Start by measuring how individuals interact with your website. Collect information about how users find your website, how long they stay on the site, which pages they visit, and more. Use multiple sources to collect data by tracking individual campaigns.
After you’ve been tracking data for a while, compile and categorize it. Figure out which touchpoints are serving as your customers’ first introduction. This stage is more likely to include paid ads, search engine optimization, and other brand-building campaigns. Next, measure lead-generating activities such as webinars, case studies, and interaction with your content. Finally, measure end-stage touchpoints including sales pitches or people who signed up for a demonstration.
Analyzing your data will give you a better sense of which touchpoints deserve more credit for converting your customers. Once you’ve seen the results, you can more successfully allocate credit across your marketing channels.
Multi-channel attribution is most effective if you consistently use an omnichannel marketing approach. This model works well with digital media because you can look at marketing metrics based on how people are interacting with your brand online. It can be trickier with more on offline ad strategies, such as print ads and linear television ads.
Multi-channel attribution does have its drawbacks. You can’t account for offline marketing strategies because there is no accurate way to measure them (who knows how many people see your bus shelter poster in a given day?).
With increased data privacy regulations, it’s harder to track how customers are interacting with your brand, as well. It’s also difficult to measure the success rate of CTV and other video ads, because people don’t normally click through an ad while they’re watching a show.
MNTN’s Verified Visits™ technology eliminates many of these challenges. With Verified Visits™, you can track customers who visit your website after viewing your MNTN ad within a set window, the length of which you determine. It also ensures that no other channel was responsible for the site visit before giving credit to your MNTN ad.
Since a customer has to meet strict criteria to be considered a Verified Visit, you get a better idea of how many people are visiting your website because they saw your CTV ad. Learn more by requesting a demo, and see what Verified Visits™ can do to improve your CTV attribution strategy.
While multi-channel attribution has its challenges, this model is a more effective way to measure marketing success. Because multi-channel attribution considers multiple touchpoints in a customer journey, it gives you a realistic idea of how your marketing efforts are influencing sales.
There are multiple types of multi-channel attribution models you can use based on your specific customers, each with their own benefits and use cases. Compare each with your business needs and you’ll see the difference that more accurate, dynamic attribution modeling can make in your marketing efforts.
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