How do you assign value to your channels and touch points? There are a variety of attribution model methods. For example, do you attribute more weight to the first touch (such as clicking on a digital ad) than the webinar that generated an online demo of offline conversation? Or do you give equal weight across all the touch points? Maybe you use a graduated scale where you give touch points closer to the end of the buying journey more value than touches earlier in the process?
Your approach will impact the decisions regarding which touches and channels affect customer behavior and deserve investment. The leadership team expects Marketing to understand which channels, touches and content have the greatest impact on generating conversations, consideration and ultimately consumption. To do this you must enter the realm of optimization and attribution modeling.
Build Your Attribution Model to Account for a Multitude of Touches, Content and Channels
A study by MMAGlobal found there is almost no correlation between click-through rate and sales. Why? Because their understanding of the role of various touch points, channels and content along the journey was too narrow focusing on a limited channel and touch. Attribution modeling is about understanding the multitude of your touches and channels and the variation among these across the entire buying process and then assigning and measuring attribution to improve and optimize your multi-touch marketing campaigns.
Let’s take an example. You have data that represents the following: prospect name, request for proposal date, deal size, deal status (won or lost), marketing channel (website, trade shows, digital, etc.), marketing touches (demo, phone calls, online chats, email, etc.), and marketing content (white papers, customer testimonials, thought leadership articles). Now you want to know which channels, touches, and content are having the greatest impact on driving customer opportunities and wins.
To answer this question you need an attribution model that encompasses the entire ecosystem of touch points and assigns a quantifiable value to each element within the context of the experience. The goal is to understand how each touch point is performing and which combination of touches, channels, and content produces the best results. Data is the essential ingredient for any attribution model.
It’s All About the Mix
A brief tutorial on the topic of optimization and attribution modeling might be helpful before we launch into a conversation about various attribution models. There are a number of sources and tools available today to help create your model. Both attribution and optimization modeling are about improving mix and understanding the impact of Marketing investments on customer behavior. Both approaches are important for measuring and improving the performance of multi-channel, multi-touch campaigns. Let’s begin by reviewing what these models are, the pros and cons of each model, and when to use them.
- Optimization relies on predictive models that track non-linear relationships between specific goals and spend levels in order to “predict” the incremental changes in conversions based on the relationship between the variables. Many organizations attempt to “optimize” campaigns via A/B testing, a form of scenario analysis. Unfortunately, A/B testing doesn’t address the complex non-linear interactions. An algorithmic approach that simultaneously analyzes all possible scenarios is needed to see which combinations produce the best incremental results.
- Attribution is based on capturing touch point data over a historical period to determine which touch points are the most effective at which stages in the buying process to support investment allocations and produce higher aggregate results.
Three Approaches for Creating an Attribution Model
The approach you take in building your attribution model has significant implications into the insights you’ll gain from your campaigns and investments. There’s no one-size-fits-all answer here. There are various approaches to attribution. Most Marketing organizations have moved beyond first-touch attribution, where 100% of the credit goes to the first touch point in the journey. While this model is simple – and suggests that no sale is ever made without some type of Marketing – the first touch is often very far away from the final deal and only tells a partial story, especially in complex consultative B2B solutions.
As a result, last-touch, equal, and fractional attribution approaches emerged:
- Last-Touch Attribution: The opposite idea to first-touch attribution. This is based on the idea that the last touch has the greatest impact on the buying process. It shifts the majority or all of the credit for the entire sale to the final step in the conversion path. It focuses on the last thing that triggered the conversion, while ignoring the path up to that point. This approach ignores all the steps that were taken up until the point of conversion, such as your nurturing campaigns, your SEO and content Marketing, any social media or digital ads, any events, etc. – even if they are part of the customer journey. Like the first-touch model, this approach does not reflect how and what the customer consumes and uses as they make their buying decision. Despite the problems inherent in this approach, people use it because the model is relatively easy to create and works fairly well for products with a short buying cycle.
- Equal Attribution: This approach is one way to overcome last-touch attribution issues. Just like it sounds, it assigns an equal value to each touch. The downside is that you may end up unnecessarily duplicating some efforts because you aren’t sure which touches have the greatest impact. With this approach you may end up investing more than you need to – because it doesn’t provide insight into which touches perform best. That takes us to the concept of Fractional Attribution.
- Fractional Attribution: This approach assigns a calculated “weight” to each marketing touch throughout the buyer’s purchase journey. Typically, this weight is determined by the corresponding relative impact that particular touch will have on producing the desired business outcome, such as purchase. This approach enables marketers to take multiple prior exposures into consideration. Determining the weights requires understanding which touches perform best. Using fractional attribution requires understanding of the statistical significance of the various touches in order to quantify their contributing effect. When building this type of model and assigning weights it is important to keep in mind that there are touches other than marketing touches that drive the desired outcome.
To Crack the Code, You Need to Know the Key
Most attribution experts agree that fractional attribution is better than last-touch or first-touch attribution. These experts typically recommend that marketers assign weights to touches based on their type and position in the buying process (at the beginning vs. closer to the end) to create the model. Marketers can then use this model to make touch point and investment decisions.
The key challenge to address with the fractional attribution approach is that buying decisions are not serial or linear. Rather, often a combination of touches impacts behavior. This is why some experts have created incremental attribution models, which attempt to calculate the change in revenue resulting from a particular touch. With this technique, touches are classified by the buying stage they support, and buyers are tracked as they move through the stages. Marketers use this structure to compare the effectiveness of different touches (messages and media) in moving buyers from one stage to the next in order to determine the incremental impact on cost and revenue of the different touches.
As we move from first or last touch to fractional attribution there is increased complexity and sophistication. Attribution models are typically framed in terms of assigning credit for a particular purchase. Marketers know that one touch has ripples that can affect multiple purchases and behaviors. If you decide to tackle attribution, the need to combine online and offline quality data will become increasingly apparent.
Make Better Decisions with Your Attribution Model
The ultimate goal of an attribution model is to better understand customer behavior. Attribution modeling serves as an important decision-making tool. Attribution focuses on evaluating the performance of each touch point in the buying process. We believe that any attribution model must in some way account for ALL the touches that impact the buying process.
To create any type of attribution model you need data related to both converting and non-converting opportunities. We recommend a phased approach to marketing attribution, so you can take advantage of test and learn. Starting small allows you to refine the model and build momentum as the model becomes more stable.
If you’re just beginning the process, create a road map for how you plan to approach model development, including defining the data sources and methodology. If you’re further along in your efforts, by all means dive in. Regardless of how you decide to proceed, good data will be essential. Turning data into insights is table stakes in today’s environment. Looking for more on this topic? Check out the free white paper, Intuition To Wisdom: Transforming Data Into Models and Actionable Insights.