If the marketing definition of “attribution” confuses you, you’re not alone. While you may have a basic understanding of what attribution is — assigning credit to a marketing touchpoint for a conversion — the influx of marketing channels and devices has complicated the meaning. So, what does attribution really mean? To fully understand it, let's delve into why it matters to your business and explore how attribution has evolved from single-touch attribution.
For more from our attribution series:
Attribution Modeling 101: Finding the Source of Truth
Designing a Multi-Touch Attribution Model
A Beginner’s Guide to Data-Driven Attribution
How to Choose the Right Attribution Model for Your Business
Attribution is the process of assigning credit for conversions to various marketing touchpoints along the customers’ journey. It measures the impact each touchpoint has on your desired outcome—be it a sale, a download, or an account sign-up. The results provide vital insights into how customers are engaging with your brand, campaign trends, which channels you should invest in, and much more.
An attribution model is the set of rules that determine the value of a customer’s interaction with various brand touchpoints. It allocates credit for conversions between these touchpoints based on a number of factors. Some models, like the linear model, spread credit out evenly over time. Others assign the full or majority of credit to just one touch. Increasingly, the savvy marketer is using AI-driven attribution platforms to quickly identify touchpoints with a high potential for conversions and automatically adjust their budgets to mirror the findings. Attribution platforms will make it easy to report on campaign progress, enabling marketers to identify the return on investment (ROI) from each marketing channel.
The Fall of Marketing Mix Modeling and Rise of Attribution
Marketing mix modeling (MMM) used to be all the rage. It’s a technique that leverages regression analysis to provide a top-down view of the marketing landscape. It offers high-level insights and helps allocate budgets to several types of media such as digital channels, television, print, and radio.
However, there are many flaws with MMM — it’s slow to get results, fails to measure brand equity, and doesn’t optimize messaging or targeting. As the consumer landscape shifted toward digital-first, marketers saw a need for more than just high-level measurements. That’s when marketing attribution made its debut in the form of single-touch attribution.
The Problem with Single-Touch Attribution
Single-touch attribution models assign 100% of conversion credit to only one marketing touchpoint. Single-touch attribution models include first-touch, first-click, last-touch, and last-click. Here is an example of single-touch attribution:
A customer completes an inbound form, attends a webinar, and replies to an email campaign where they accept a sales meeting. If you’re using the last touch attribution model, the email campaign will get 100% of the credit. While these models were undoubtedly popular in the past, they no longer make sense for the modern consumer. Today’s shopper is exposed to many different touchpoints across every device and platform — social media ads, email marketing, Google ads, and even billboards (not every touchpoint is digital). Single-touch attribution ignores these middle points and focuses on just the first or last interaction.
The Difference Between Click and Touch in Attribution
Though many marketing resources will combine last-touch attribution with last-click and first touch attribution with first-click, they are not exactly the same. In practice, the attribution model looks at different actions for touch attribution vs. click attribution. Here is the breakdown:
- Last-touch: The last-touch attribution model assigns 100% of the credit to the last marketing touchpoint before conversion.
- Last-click: This model assigns 100% of the credit to the “last-click” before conversion.
- First-touch: The first touch attribution model assigns 100% of the credit to the first marketing touchpoint (the channel or activity that acquired the contact).
- First-click: This model assigns 100% of the credit to the “first-click.”
Why Last-Click and Last-Touch Attribution Don't Work
As mentioned in our other article on last-click attribution, optimizing for clicks does not optimize sales. Only 4% of internet users click on ads, which means that companies that focus their attention on last-click attribution are limited to a very narrow audience. Their marketing efforts are not optimized for the vast majority of consumers, which is a missed opportunity. To add salt to the wound, studies show that there is almost no correlation between click-through rates and purchasing behavior. So, marketing teams are spending more on expensive CPC campaigns for fewer results.
In the modern age of marketing across platforms, devices, and channels, the typical retail consumer requires an average of 56 touchpoints before making a purchase. The last click and last-touch attribution models fail to acknowledge this dramatic shift in the consumer journey, leaving 55 interactions uncredited. In today’s reality of omnichannel marketing, brands must view and analyze the complete marketing picture. Otherwise, they will miss significant opportunities for optimization and sales. The same goes for first touch attribution as well.
The customer journey is ever-changing. Today, it spans many devices and requires over 50 interactions before a conversion takes place. This is why it’s necessary to assign proper credit to each touchpoint so that marketers can determine where the budget should be spent — cue multi-touch attribution.
If your marketing mix extends beyond a single channel, multi-touch attribution is the only option that provides a complete view of the customer journey. This method assigns a value to each customer touchpoint and shows you which actions have the most impact on conversions.
Rule-Based vs. Data-Based Attribution Models
There are two types of attribution models available to marketing teams:
Examples of rule-based models include linear, time decay, w-shaped, and u-shaped, which represent different predefined rules of assigning credits to each touchpoint. In contrast, statistical models use algorithms to assign credits instead of rules.
If none of those models work for your business, you can even create a custom attribution model that combines various features of standard models. The possibilities are endless — there’s an attribution model for every stage of your business. You just need to do your research to discover which model works best for you.
Recognize That Attribution Is a Journey
Attribution is complicated, especially if you take into account all online and offline influences, various devices, and even brand awareness campaigns where display ads are measured by impressions instead of clicks. It’s essential to understand that attribution is a journey — often, one where a lot of flawed methodologies, rules, and data are introduced. However, any step towards better attribution modeling can have a meaningful impact on reducing wasted marketing spend.
The ideal approach to attribution is to leverage available technologies to save time, money, and resources. The automation built into these tools also delivers more accurate results than are otherwise possible. Rather than being based on human subjectivity, these platforms feed actual data into AI and machine learning technology to provide the most up-to-date and accurate information available.