A quick question: do you know which part of your marketing investment generates the most revenue? Is it even possible to know the answer?
While this may feel like a philosophical experiment about the nature of reality, it’s actually what goes through the minds of most daily. Being able to tie a specific tactic or ad (and its costs) directly to revenue is the Holy Grail for most marketers.
Doing so, however, may actually be impossible. Think about it, advertising campaigns are often assembled to shift consumer behavior over time through repetition and exposure to multiple messages that build on each other. How can you be sure which message (or combination thereof) was most successful?
In order to divine these answers, marketers employ various techniques, including attribution, multi-touch attribution, contribution, incrementality, and more. But what do these terms mean, and how are they different?
Today, we’ll break it all down for you.
What is marketing attribution?
Let’s kick things off with the basics: attribution. Put simply, this is the act of attributing revenue figures (or any other core KPI) to your various marketing activities. The goal is to understand which tactics are the most successful, and should garner more of your marketing budget.
In other words, attribution attempts to answer which marketing efforts drive the most ROI.
The challenge of attribution
While attributing every marketing touchpoint to end revenue may be an ideal goal, it often pushes up against reality (and quite quickly). Imagine your own business. It probably runs several, even hundreds or thousands, of ads throughout the year. These ads are part of different campaigns, use other creatives, appear on vastly different platforms, and more.
This is a time-tested strategy for many marketers to reach as many potential customers as possible. Those customers, however, don’t interact with all of these ads in a linear and predefined order.
Instead, they bounce in and out of your marketing environment at random points. So, how do you apply attribution to a marketing campaign with multiple touchpoints?
What is multi-touch attribution?
As we’ve previously covered, multi-touch attribution (or MTA) examines all touch points within a customer journey in an effort to determine which were most effective. This is a more modern way to examine marketing effectiveness than straight attribution, since it attempts to account for your broader marketing efforts.
There are a few ways to tackle this mode of attribution, and each method has its pros and cons. Some of the more popular methods include linear, time-decay, and data-driven attribution.
What is linear attribution?
For the sake of simplicity, imagine that your customer journey involves 10 touchpoints. Linear attribution assigns equal credit (so 10%) to each touchpoint.
What is time-decay attribution?
Imagining the same 10-point customer journey, time-decay attribution emphasizes the tactics at the journey's end. This often makes logical sense to many marketers. While early points of the customer journey may have grabbed a customer’s attention or lightly influenced brand affinity, those touchpoints at the end often “close the deal.”
What is data-driven attribution?
The most complex of these three MTA methods, data-driven attribution, relies on machine learning to analyze vast performance data from across the customer journey. These technical models then assign credit to each touchpoint based on its estimated overall impact.
Yet, while many methods exist to track down reasonable attribution, many marketers still see it as a fool’s errand. These skeptical marketers claim that true attribution is impossible. They claim that there is, in fact, a better way.
What is contribution?
Many marketers like to think of their customer journey as a tidy and logical path from discovery to sale, as evidenced in the graphic below.
The reality, however, is a bit messier:
To account for this messier customer journey, some marketers utilize “contribution.” They are less interested in which specific tactic leads to the final sale and instead focus on how much each tactic contributed to their overall success.
While this may seem like splitting semantic hairs, just give us a second to explain.
Imagine that you run advertising across Google Ads, Facebook Ads, and TikTok Shop. You may see that the performance on each platform generally runs parallel to the others. For instance, you can see similar seasonal spikes in sales, though each platform’s total revenue and performance figures may be at different levels.
However, what would happen if you slashed budgets for both Facebook and Google? Facebook performance may not change, while Google’s performance begins to drop off. While that may not necessarily help you attribute Facebook or Google Ads to your end sales, it can tell you which platform contributes more performance to your sales regardless of investment.
Which brings us, finally, to incrementality…
What is incrementality?
Incrementality aims to measure the true impact of your marketing campaign based on a specific outcome. This outcome would be conversions, creation of sales-qualified leads, website traffic, and more. Specifically, incrementality measures the difference between how often these goals would be achieved without any marketing and what occurred as a result of your marketing.
Think of it like this: a small river is flowing downhill. Eventually, it hits level ground and begins to form a pond. This pond occurred naturally, without an intervention. The water was always going to hit the pond eventually.
Now, imagine that there is a fire hydrant near the head of the river. You connect a firehose to the hydrant and begin to stream city water into the small river. All that water flows downhill and hits the pond — though now the pond has more water.
The increased volume of water in the pond is the incremental value of your firehouse at the top of the river. It’s the same premise for the incrementality of your marketing: some sales would always happen, but your marketing efforts created more volume.
Many modern marketers love to use incrementality over attribution, since it quantifies the impact of their overall investment. Rather than trying to pinpoint the effectiveness of each tactic, they can view the overall return on ad spend.
Then, if they want to experiment with adjusting budget levels, they can employ tactics like marketing mix modeling to predict how spending increases or decreases may affect performance.
Read More: https://funnel.io/blog/incrementality
Whether attribution or incrementality, it’s all about data
Today, with advances in artificial intelligence and machine learning, some marketers are still chasing the dream of directly attributing revenue goals to marketing tactics and invested dollars. However, other marketers have given up on this wild goose chase and, instead, opted to employ incrementality to more effectively measure the true impact of their campaigns.
Regardless of your preferred approach, you’ll need solid data skills and tools to truly understand your past performance. Then, with all of your data united from every corner of your campaigns, you can begin to gain a holistic view of how the entire marketing ecosystem functions.
Disclaimer: The featured image for this article was created using generative AI.