After Northbeam has completed the Learning Phase (2-4 weeks where our machine learning models ingest your data to stitch together customer journeys) of onboarding, our Clicks & Views Multi-Touch Model will be available for use. The goal of this model is to leverage our machine learning capabilities and strengths to help brands account for view-through data when analyzing attribution decisions. Clicks & Views provides directionality on which ads within a channel are driving the most results and which ones are ineffective. Although we cannot guarantee 100% accuracy, using the Clicks & Views model in conjunction with our Clicks Only model can help you fill in any “click-through” gaps.
The Clicks + Views Model Defined
The Clicks + Views model is Northbeam’s proprietary, machine-learning driven model that accounts for view-through data when making attribution decisions. This model looks to split attribution credit on a Multi-Touch basis, and gives no attribution credit to any direct, organic search, paid branded search, or email/ SMS channels if there are any other touchpoint source in the customer's journey. The C+V model will also give appropriate credit to Views at any point throughout the customer's journey.
We built this model because organic traffic is not helpful for marketers when trying to analyze customer journeys. Although our Clicks Only model is our most accurate because clicks are hard data, there are many conversions that won’t be captured because clicks are not the entire picture. We know that many customers eventually convert via direct visits after watching a TikTok, YouTube or Facebook ad, so our Clicks + Views model tries to assign proper credit to any ad views throughout a conversion path. This can help make your data more actionable by giving you a more complete picture of what’s going on with your campaigns.
How Does Clicks + Views Work?
At a high level, our model tracks engagement metrics (impressions, video views, etc.) and tries to find correlations between those metrics and any corresponding organic spikes. Our model then makes an educated guess using machine learning from your data to assign organic traffic and conversions to the ad campaign that prompted that behavior. Please note the attribution window for Clicks + Views is 1 day view only regardless of what option you select.
One of the most common questions we get is: which attribution model is the best one to use to make media buying decisions? We like to say that there isn’t a universally optimal one because attribution models are simply different ways to slice and organize your data depending on your opinion of which set of rules is most appropriate for your business. We generally recommend starting with Clicks Only because it’s our most conservative and accurate model that uses hard data, but if your business relies on view through data then the Clicks + Views model can provide some powerful insights.
To select the Clicks + Views model, go to the top of the Overview or Sales tab until you see the “Attribution model” toggle. Select the dropdown menu and pick Clicks + Views. You’ll notice that Organic, Organic Search, and Branded Search metrics are all zeroed out in this model.
In order to determine directionality of what views are driving incremental revenue, we need to compare the Clicks Only model to the Clicks + Views model. We’re essentially looking for big gaps between revenue reported in Clicks Only vs. Clicks + Views because that gives us a clue into what ultimately assisted the organic conversions. We recommend using the Model Comparison tool in Northbeam to do this:
Next, change the Attribution model toggles at the top to Clicks Only and Clicks + Views (the default is First touch vs Last touch). You can also choose a Breakdown to view your data in a specific way (by platform for example).
Let’s say you notice that Clicks + Views captures a bunch of revenue attributed to YouTube ads that weren’t captured in Clicks Only. This could mean that YouTube ads are driving revenue, but we should try and validate these results before dramatically scaling spend. One way to do that is to conduct post-purchase surveys and track where incremental revenue is coming from. You could also slowly ramp up spend in YouTube while keeping an eye on blended revenue numbers to see if they’re highly correlated. If post-purchase surveys are also indicating YouTube as a leading channel, then you can be reasonably confident that YouTube ads are having a positive and additive impact on your business.
Do you have further questions or need a little help? Email us at Northbeam Customer Success to set up time!