Introducing a tool that will provide a new dimension of understanding when creating segments with machine-learning attributes.
The visual builder uses an interactive display to show the predicted reach of your audience segment according to the machine-learning model at work. Simply drag the cut-off slider to select the value that fits your objectives: do you want to create the smallest audience possible while retaining the majority of actual buyers? The visual builder allows you and your marketing team to make truly educated decisions.
Nice! But what exactly am I looking at?
An excellent question! The visual above shows a representation of the output our “likelihood to buy” predictive model will generate depending on how strict you tell it to be.
The X-axis of the bar graph shows a scale of numbers from 0 to 0.9. This is an index used to give a number value to how likely to buy each visitor is predicted to be. Closer to 1 means higher likelihood, closer to to 0 means lower.
The red bars represents the percentage of your total audience. The blue line represents the percentage of likely buyers captured within the audience at each point on the scale.
As you move the scale from left to right, narrowing the audience selection toward more likely buyers, you can see the size of your audience decreasing in the left-most pie chart above the bar graph. At the same time, the middle pie chart shows the percentage of likely buyers captured within the resulting segment.
In this case, you can see that just narrowing the audience to people with a likelihood to buy greater than 0.1 reduces the audience by over half, while still reaching 95% of likely buyers. It immediately gives you the ability to avoid wasting advertising dollars on non-converting visitors.
Ok, so what can I do with it?
We’re glad you asked!
Here is a use case for this exact feature:
Identifying Your Most Likely Buyers
Check out our machine learning use case, based on results from a DTC client.
We’re on a mission to take the guess-work out of marketing.
Machine learning might be complicated, but is doesn’t need to be hard to understand.
Schedule a conversation with us today to talk about how your brand can make actionable and practical use of machine learning.