Machine learning made easy with <intent> Scores

Machine learning is present in all industries. It works behind the scenes to influence the decisions we make every day. Whether it’s the new tv show we stream on Netflix, the articles we peruse via Google, or an interest rate we receive for a car loan – machine learning and real-time predictions is the powerhouse that transforms a massive amount of information that leads to a data-driven decision.

Prediction is just one example of an output a machine learning model can provide. Other machine learning examples include classification and anomaly detection. Predicting behavior is useful for choosing the best options to deliver to a user from a universe of possibilities. For Netflix, this means recommending content you’ll enjoy. For Google, it’s showing relevant links based on your search. And for a loan servicer, it’s offering you a competitive interest rate that matches your creditworthiness.  

Providing context to machine learning outputs

The power and flexibility of this predictive technology are impressive. However, a peek under the hood reveals that the raw output from a machine learning model isn’t that useful on its own. To understand the meaning of a prediction that’s outputted from a model, you need to add context to that prediction. That’s how it becomes useful in the real world. Without this context, we might spend our Friday nights mindlessly scrolling the Netflix tv catalog instead of actually watching our favorite content. 

Digestible real-time predictions with <intent> Scores


At <intent>, we make real-time predictions on user behavior for travel and ecommerce brands. We use <intent> Scores to turn complex predictions from our machine learning platform into easy-to-understand audiences you can treat differently. This enables our partners to optimize at the user level, using our predictions on each user’s likelihood to convert, bounce, view another page, comparison shop, and more. 

Companies of every size are using <intent> Scores to drive more profit from their users with our suite of applications

Learn more about <intent> Scores in our one-pager