How to detect intent of your visitors?
Advanced detection mechanisms have been used for decades in medicine and psychophysics; with the first assessment of human signals dating back to the 1950’s. Data sets grew bigger and naturally called for more intelligent processing, which Machine Learning (and to some extent AI) can fulfill.
This is what we’re solving at Cauzal.ai: How can we apply some of this methodology in Marketing, and specifically in content management?
1st thing first, let’s put our scientist hats on and understand the concept of ROC Curve: Receiver Operating Characteristic. It looks like that:
In this example, we are looking at 3 detection predictors for the presence of a certain chemical compound.
Without getting into too much detail, these curves essentially tell us how good these 3 predictors are at identifying the Peptide in patients. True positive is another way of measuring: My predictor said it would be positive and it is! On the X-axis, we are looking at the total population (removing the positives ones as we find them to be exact).
Now, how do we apply this to Content Marketing?
We are obviously not dealing with the same impact medicine detection has on the world, but we can still draw some parallels.
Your content converts your visitors, but your visitors have different intents, sensitivities, and behaviors. So finding who converts to what is highly important.
And that’s what we do. Our engine detects the signals and scores visitors on their propensity to convert for multiple variations of content. We are then able to serve each visitor with their specific winning message, thus increasing the chances of them converting.
Give it a try, there’s no setup, no code required. Sign up at cauzal.ai
