Discovering Multi-Touch Attribution
The increasing demand for in depth-data analysis brings along an inevitable demand for a detailed data attribution model that allows marketers to credit all touch-points more precisely.
More marketers are becoming aware of the importance of attributing credit to all touch-points, rather than a single touch-point along the customer journey. Marketers want to have an understanding of their campaigns beyond the impact of one single touchpoint.
Choosing an attribution model requires a clear understanding about what attribution and functional data integration are. Both of which may provide insights into all multi channel data.
What is multi-touch attribution?
Multi-touch attribution is a marketing attribution model used to assign credit to all touch-points in the customer journey. However, any organization has different needs. This means that what you hear is working for one company may not work for another.
When your business needs to determine the next marketing strategy, it may suddenly bump into some of the simplest existing attribution models such as Last Click Attribution or First Click Attribution.
However, multi-touch attribution becomes important when your clients follow a multi-channel journey.
In few words, multi-touch attribution is an attribution model that assigns a value to each touch-point that contributed to a conversion.
This model defines the right weight to be assigned to every single channel or impression and helps you determine how to attain astounding insights for your marketing strategy: where exactly to allocate your investments in the future.
How many models exist?
Every attribution model has its own advantages and deciding which one to choose depends on a number of factors such as path length, number of impressions, type of industry business, ect. Let’s explore some of the available multi-touch attribution models.
- Linear
- Time Decay
- Custom
- Full path
- U-Shaped
- W-shaped
At this point, a question may come to your mind: Do any of these attribution models make a difference?
It is important to mention that the models above lead to better results in comparison to the First-touch and Last-touch attribution models. In fact, multi-touch attribution models deliver a more complex and realistic data attribution across all touch-points.
At this stage, a second key point to mention is how multi-touch attribution tracks these key touch-points. The answer lies behind data integration. An effective use of data integration can have a major impact on the success of any multi-touch models.
Tracking marketing activities across multiple channels can be done in a number of ways:
1. Javascript tracking code: this can be added on your company website to ensure full tracking of the user movements throughout your pages.
2. UTM parameters: they also track movements to obtain the origin of a session and assign credit to the related campaign or activity.
These are tags added to the URL.
3. Cookies: are a special method to track an anonymous user. Once the site assigns a cookie to that user, it remains until removed or expired. Over this period of time, the same user may complete an identifying action such as submitting a form on your website.
This matches the user with the touch point activity enabling data collection.
4. Application Program Interface (API integrations): this allows for multi-touch attribution to track and collect data from multiple channels and platforms. API allows for possible interactions between different software programs.
Having many options does not make your life easier. Having a deep understanding of your business and marketing data is a guarantee of success. At this stage you may want to consider options to achieve a detailed analysis and collect data from many different sources.
The key point here is to make possible a complex convergence of data into a unique funnel. Another possibility may be to find a customized solution that meets all of your business needs and requirements.
The fact is that integrating all of your data is the first step toward determining a concrete data-driven business strategy.