Glossary

Predictive Analytics

Predictive analytics uses big data and machine learning to identify future behavior based on customer data and historical behavior.

What is predictive analytics?

Predictive analytics uses technology to identify patterns in data. In marketing, with big data and machine learning, you can use predictive analytics to identify the most engaging and compelling actions your audience should take. For example, predictive analytics could identify that a certain audience segment engages the most with niche content and automatically suggest this niche content to this audience.

Why is predictive analytics important?

Predictive analytics is how your make sure you’re sending your readers the right message. With predictive analytics, you can recommend the most relevant content, improve reader engagement, and maximize the ROI of your content.

How does predictive analytics work?

Predictive analytics uses historical data to predict future events. That predictive model is then used on current data to predict what will happen next, or to suggest actions to take for optimal outcomes.

Predictive analytics and Parse.ly

Parse.ly content recommendations are powered by cutting-edge predictive analytics. Our content recommendation API shows your audience the content that will result in the best outcome for your business, whether it’s more leads, more page views, or more engagement.