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Understanding Digital Advertising Data Modeling

When it comes to marketing, understanding and analyzing your data is one of the most important things you can do, and digital advertising is no different. It’s important to track how your ads and digital efforts affect your bottom line, as it can make a huge difference in the success or failure of your campaigns. One of the great things about digital advertising is that you can get your data in close to real-time, allowing you to optimize or change things quickly. The big question though is how do you attribute data for your digital efforts? There are so many different models and touchpoints…is there a right way?

When it comes to attribution, there are several different widely accepted models. Let’s say you advertise on Google Ads, send emails, utilize META advertising, and also implement SEO. A user may visit your website and convert after engaging with one, a few, or all of your digital efforts. How do you know which channel deserves the most “credit?” Should all of the touchpoints be credited equally? What about those ads that a user sees but does not click? These are very legitimate questions that analysts have been struggling with for years. 

What is Data-Drive Attribution?

Recently, all of the Google properties switched to the “data-driven” attribution model, which uses an algorithm to help provide you with an accurate representation of which channels deserve credit for conversions. Google defines data-driven attribution as something that “distributes credit for the conversion based on data for each conversion event. It’s different from the other models because it uses your account’s data to calculate the actual contribution of each click interaction.”

It relies on machine learning AI to better understand your website and your advertising efforts and how users are engaging with them. From there, when a conversion happens, it assigns “credit” to the appropriate channels. It incorporates many factors such as the type of device, the number of interactions with ads, the order of ads seen by channel, creative assets, and more.

Other Data Attribution Models

If you’re looking for a model that is easier to understand, you have the ability within your analytics and advertising software to adjust the modeling. Some other popular models include first touch, last touch, linear, time decay, U-shaped, and W-shaped. Each of these is a powerful model that can help you understand your data and help you make informed decisions. There is no one-size-fits-all model and you need to find the model that meets your specific needs.

Here, at Waybetter we take all things into account when analyzing our data to ensure that credit is appropriately applied to our multi-channel approach. We take this information and adapt our strategy to ensure that the most beneficial campaigns are most prevalent. If you are unsure about your data, reach out to us and we can set up a time to meet and understand your goals.

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