All digital marketing efforts require customers to interact with digital touchpoints, like banner or social media ads and email marketing campaigns. These touchpoints are designed to carry these customers through the marketing funnel, beginning with customer attraction and ending with a conversion action, like the sale of a product or service. But how do you know if your ads or emails are reaching anyone? Or what if another channel you aren’t monitoring actually brings in the most leads? Marketing attribution models exist to answer these questions.
What is Marketing Attribution Modeling?
Marketing attribution modeling is a way to assign credit to a specific customer interaction. These models help to determine which touchpoints are attracting customers, driving conversions, and effectively nurturing customer interest along the way.
The Different Types of Marketing Attribution Models
1. First-Touch Attribution
Let’s say you’re in the market for a new bed frame. As you’re browsing through Facebook, you come across an ad for a stylish bed frame that looks like the one you’ve dreamt of. You click on the ad and read more about the product and the company on the site. Then you browse through the reviews, as any right-minded person would. You sit on it for a couple of days, and after some deliberation you decide to buy the bed frame, thus making a conversion for the company.
So how does a first-touch attribution model play into this scenario? Even though you started the buyer’s journey by clicking on a Facebook ad, a lot of subsequent touchpoints could have persuaded you to buy the product. But whether or not that original Facebook ad actually had a large influence on your decision, it gets all of the credit for the conversion.
This attribution model is useful when you want to know which of your marketing campaigns and channels are most effective at acquiring new leads and customers. You can use this information to increase your awareness stage spending for a chance to drive more leads and customer acquisition.
First-touch attribution can easily overemphasize the importance of the awareness stage. This makes it easier to overlook other touchpoints that are potentially more important for the buyer’s journey.
2. Last-Touch Attribution
Let’s go back to the bed frame example. After you sat on the idea for a couple of days, you went to your web browser and typed the website URL directly into it. This brings you immediately to the company’s page, and you buy the bed frame.
What gets the credit for conversion under last-touch attribution? Direct traffic, or the act of typing in the specific URL to navigate to the website.
This model is great for determining what channels are leading to the most conversions. You have a better understanding of where customers are exiting the sales funnel. If you know what channels are raking in the most engagement, focusing on them more could mean getting even more conversions.
As with first-touch attribution, this model can easily overemphasize the importance of a specific touchpoint. In our example, the bed frame company might assume a lot of people buy their product after simply typing in their exact URL, but there was a lot of exposure leading up to that point. For a conversion funnel to work properly, you need to know what leads people to take that next step.
3. Last Non-Direct Attribution
Last non-direct attribution is a solid attempt at solving the issue of direct URL conversions. Under this model, if the last touchpoint before a conversion was direct traffic, it does not get any of the credit. Instead, the last campaign or channel that the customer interacted with before typing the URL will get the credit.
Let’s look at an example. Say someone who has already interacted with your company clicks on a banner ad on YouTube and spends some time on the webpage. And then they leave, without making the conversion. The next day, they type in your URL and buy the product. The credit for the conversion will go to the YouTube banner ad.
This approach to attribution modeling is more inclusive than last-touch attribution, as it helps determine what inspires direct conversions. Knowing how many people know your web address isn’t very helpful from a marketing perspective. It helps show the marketing lynchpin that solidifies a customer’s decision to buy.
Even though last non-direct attribution has a little bit more of a holistic approach, it still gives all of the credit to a single point. There are still plenty of other variables that could have brought a customer to this point.
4. Last Marketing Channel-Touch Attribution
If you’re wondering how a specific marketing tool is performing, you can use this form of last-touch attribution to determine the ROI. This attribution model marketing approach can be applied to any specific channels you choose to use, like Facebook and Google Ads. And much like last-touch attribution, this model assigns all credit to the last marketing designated channel the customer interacted with before a conversion.
But why use this approach? To use Google Ads as an example, this model can help determine which of your targeted keywords are helping to drive conversions. From there you can determine which keywords you should focus on more.
This kind of attribution model is great for those looking to see the ROI on specific marketing tools. These metrics are also very easy to access, since Facebook and Google analytics use the last Facebook-touch and last Google Ads-touch attribution model, respectively.
These models, while useful, can be extremely biased and overvalue the worth of the channel. This is, of course, natural for any single-touch attribution. However, if you use both Facebook and Google Ads and a customer interacts with both before converting, each of those tools will claim 100 percent of the credit.
5. Linear Attribution
What if you don’t want to give all the credit to a single touchpoint? After all, most people won’t buy a product after seeing a single ad. It takes time to nurture their interest and convince them of the benefits. So if it feels wrong to equate the whole buyer’s journey to a single interaction, you’ll want to turn to a multi-touch marketing attribution model.
One of these models is called linear attribution. This gives equal credit to all of prospective customers' touchpoints before making the conversion. Facebook ads, organic searches, website visits, and anything else a customer runs into are equally important in the eyes of linear attribution.
With linear attribution, you’ll be able to invest your energy into channels that are backed with more holistic data. After some time with this approach, you’ll start to notice patterns of channels working well together, as well as which channels are performing better during a certain stage of the funnel. Likewise, you’ll see which are not interacting well with one another.
This model runs into a similar problem as the single-touchpoint methods: You may be giving too much (or too little) attribution to a certain touchpoint. While this helps to identify everything that went into a conversion, one channel may be more influential than another, and this model doesn’t account for that.
6. Time-Decay Attribution
For marketers who want a more holistic approach to discover what drives conversions, time-decay attribution might just be the right model for them. This attribution model gives more credit the closer the touchpoint is to conversion. It operates under the assumption that the closer a touchpoint is to the end of their journey, the more influence it has on the conversion.
To give an example, consider a customer who is first exposed to your company through a Facebook ad. Over the course of a week, they get an email notification about one of your company’s sales, see a banner ad on YouTube, and search your product or company on Google (in that order). With time-decay attribution, the original Facebook ad would get the least credit, and the organic search would get the most, since it’s going to be the last touchpoint before conversion.
Time-decay attribution is great for determining which channels consistently see conversions. It usually works best for determining effectiveness for short customer journeys, but can be applied to longer journeys as well.
The approach will never give significant credit to the top-of-the-funnel channels. While they aren’t great for driving conversions, time-decay attribution can make it easy to disregard things that drive new engagement.
7. Position-Based Attribution (U-Shaped)
Most of the marketing attribution models we’ve discussed heavily focus on either driving conversions or attracting website visitors. But both of these metrics are important, so maybe you want to prioritize them both. Fortunately, position-based attribution (or U-shaped attribution) is specifically designed with this strategy in mind.
The name “U-shaped” refers to the attribution spread of this model: The first and last touchpoints get the most credit, and the rest is spread out between the middle touchpoints. This way, marketers are able to observe and prioritize what acquires potential customers and what drives them to convert.
For companies that want to focus on how to attract visitors and direct them to a specific conversion, U-shaped attribution makes applicable touchpoints very clear.
This model is not ideal if you’re pursuing a nurturing campaign. Some marketing efforts require a steady stream of touchpoints and exposure opportunities. And for longer decision-makers, this model won’t account for online cookie expiration which can lead to using unreliable data.
8. W-Shaped Attribution
Similar to U-shaped, W-shaped attribution gives another large chunk of credit to another point of interest to the buyer’s journey—when the visitor becomes a lead.
So what’s the difference? A lead is a visitor who now has a clear interest in the product, service, or experience offered. This is a crucial step in the buyer’s journey; if they don’t show interest, then they won’t feel the need to take action. Visitors usually become leads when they subscribe to an email list, ask a question to a representative, or take some action to communicate directly with the company.
Effectively, W-shaped attribution is an enhanced version of the U-shaped model. It focuses on the beginning (visitor attraction), middle (lead generation), and end (conversion) of the customer’s journey. It lets you focus on the touchpoints that result in action, rather than passive exposure.
If your journey cycle is short and simple, W-shaped attribution might be overly complicated. For example, it’s possible for a company’s customer journey to not have a defined lead generation step. Additionally, this model may put too much emphasis on lead generation if you’re more interested in conversions.
9. Full-Path Attribution (Z-Shaped)
Taking it one step further from W-shaped, Z-shaped attribution focuses on four touchpoints:
- First touch
- Lead generation
- Conversion (opportunity creation)
- Customer close
Many people use the word “conversion” as a synonym for closing a customer. While many times this is the case, conversion actually just refers to goal completion. That means the desired conversion may not be purchasing a product, but rather downloading a newsletter or a PDF from a website.
Customer close, on the other hand, always refers to a customer paying for a service, product, or experience, and therefore bringing the journey to a close.
And Z-shaped attribution may seem similar to linear, but that is not the case. Linear attribution will give equal credit to every touchpoint a customer interacts with. While four touchpoints seem like a complete journey, there are still others the customer potentially interacts with. And rather than giving everything equal credit, Z-shaped attribution will split 90 percent of the credit between the four points, and divide the remaining 10 percent among the rest.
This approach encompasses nearly everything that would directly lead a customer through the marketing funnel. It will also give you a comprehensive look at the customer journey.
Like with W-shaped attribution, this attribution model won’t be very effective for simple customer journeys. Also, if you have a sales team that you rely on to close on opportunities rather than a marketing campaign, you won’t be able to see that data using this model.
10. Machine-led Data-Driven Attribution
While we’ve discussed a wide range of attribution models that encompass a lot of in-depth approaches to analyzing a marketing campaign, they all rely on some form of extreme assumption.
But what if you don’t want to assume? What if you want to know exactly how much a specific marketing effort is contributing to your success?
Enter machine-led data-driven attribution.
Machine-led (or algorithmic) attribution models, such as the Shapley Value or Markov Model, differ in a few key ways from simple attribution models. First, machine-led models will conduct thousands of simulations to analyze every touchpoint, alongside the attributes and metadata (such as publisher, frequency, time of ebay, etc.) that lead to a conversion or not.
Second, while simple models only analyze conversion paths, machine-led models look at all customer journeys, regardless of whether or not they end in conversion. By evaluating both conversion and non-conversion paths, machine-led models will note when a touchpoint frequently participated in a conversion (or not) and give that touchpoint more credit (or not).
A good example of this is ObservePoint’s marketing attribution solution, Prism, which uses algorithmic and rule-based attribution models to visualize attribution across all customer experience efforts. Prism is a comprehensive, multi-touch attribution solution built on complete and unified data that enables you to show your contribution to revenue, prove the value of marketing efforts, and justify investments across all channels and content.
This model, without a doubt, gives the most accurate representation of how well your efforts are faring and contributing to overall marketing efforts. You’ll know for certain which channels are actually helping and which are just wasting your money.
There aren’t really any downsides to data-driven attribution. Since the model is tailored to the needs and goals of your organization, you won’t see any discrepancies in your data or give too much credit to a certain touchpoint.
However, there are logistical downsides to this model. It takes a lot of time to create and manage data-driven attribution models, not to mention you’ll need to hire data analysts to interpret key findings to make data-driven decisions in time to most effectively execute them.
Finding the Right Attribution Model
Every company needs attribution models to determine the success of their marketing efforts. Otherwise, you could be throwing money at a tactic that isn’t seeing any return on investment.
There is no single answer to which of these attribution models will work best for your company, but you should always be on the lookout for methods that help improve your strategy and increase your ROI.
ObservePoint offers attribution solutions to help you achieve better ROI visibility across all your channels. Visit our attribution webpage to find out more about what machine-led marketing attribution solutions can do for you.
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