What is a Wholesome Attribution Model?

When first learning about attribution, the phrase “wholesome attribution” can be a little confusing. This doesn’t refer to the moral or physical quality of the marketing attribution strategy, like you might think about a wholesome bit of fun. Instead, the wholesome attribution model is one of two high-level approaches to marketing attribution. 

What are the Two Types of Attribution?

Marketing attribution models are one of two types, functioning through either wholesome attribution or fractional attribution. 

• Wholesome Marketing Attribution assigns credit for revenue to either the first touch or the last touch that got a customer interested in your brand. This is also known as single-source attribution.  
• Fractional Marketing Attribution distributes credit for a customer’s buying decision across all the pieces of marketing content that a customer interacted with. This is also known as multi-touch attribution.

Within these two categories, there are multiple different strategies that can be used. 

• Wholesome Attribution Strategies include first click attribution and last click attribution, where credit is given to either the first or last piece of marketing content a customer interacted with before they made a purchase decision. 
• Fractional Attribution Strategies of multi-touch attribution include linear attribution, w-shaped attribution, u-shaped attribution, and custom models. 

Which Attribution Model to Use

With this basic information in hand, the question of which model to use comes up. What are the benefits of wholesome attribution like last touch vs multi touch attribution? Which form of multi-touch attribution will reveal the insights you need? In fact, the attribution model you should use depends on the kind of questions you are trying to answer. 

• First touch attribution helps you know which pieces of content are getting the attention of new or existing customers.
• Last touch attribution helps you know which pieces of content are your closers, viewed most often right before a buying decision.
• U-Shaped attribution shows you the first and last touch points while also revealing the content along the path between.
• Linear attribution gives equal weight to all the marketing touch points and gives you a better look at the customer journey.
• W-shaped attribution creates a distinction between lead conversion and last click, which can be useful for organizations with a lead waterfall.
• Time decay attribution gives more credit to the more recent marketing touch points, while still showing the earlier content that got a customer interested. 

An organization’s larger marketing strategy may benefit from one attribution model, while a specific campaign might have different goals that should be tracked through a different model. On the other hand, switching back and forth between models may lead to the same lead being counted twice. While you can learn a lot from looking at data from different models, it’s also important not to add them together, since they will all be pulling from the same data.

Actionable Marketing Attribution Analytics 

Ultimately, marketers have a lot of work to do extracting actionable insights from the data provided by either kind of marketing attribution model. Even an approach as simple as first click or last click will generate a lot of information about the performance of your content. 

But what to do next? Will it be more beneficial to expand on your top-performing content, or try to pivot and improve the low-performing content? Should you strategize how to relate certain messaging earlier in the funnel, or instead experiment with new content forms like video, graphics, or long-form content?

We created the DemandJump platform to bridge the gap between analytics data and the actionable steps that will make good on the findings. With built-in marketing attribution functionality, the platform collects and unifies your disparate data sources. DemandJump also collects consumer insights and search trends that are relevant to your industry at large, to give perspective on how your existing library of content is aligning with customer expectations and your competitors’ online presence. 

Try it for free and take action on the insights already living in your data.