Introducing Co-Pilot: Machine Learning-Powered Content Recommendations

By Peter Cassidy - June 20, 2017
1 mins read time
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Artificial Intelligence and machine learning technologies have been improving people’s everyday lives in a million ways. From beating traffic with Google Maps to improving personal health with wearables like Fitbit and Amazfit.

Now, we’re applying that deep learning technology to the challenges that have plagued marketers for years: delivering and continually optimizing personal content experiences at scale.

How Predictive Recommendations Can Help You Navigate a World of Content

Today, marketers are up against seemingly endless content demands. So leading brands are leveraging the billions of authentic, compelling customer stories people post online every day to help feed and drive their content strategies. But curating the right content, for the right audience can be challenging and time-consuming.

Co-Pilot, our machine learning-powered content recommendation engine, helps you navigate this world of content so you can discover, curate and publish better performing content with less effort.

Co-Pilot helps marketers navigate a world of content so you can publish better content with less effort.Click To Tweet

Using machine learning algorithms to observe patterns in the content you publish and how your audience interacts with it, Co-Pilot makes real-time recommendations on what content you should publish, discard, tag and rights manage.

So how does Co-Pilot work? It continually learns and improves – observing, measuring and evaluating hundreds of data points to build a profile of the content you like to publish and how it resonates with your audience.

Content IntelligenceContent Intelligence

Co-Pilot analyzes visual attributes within the content – like objects, scenes or emotions, and couples this with media metadata, location, language, sentiment and author profile data to gain a deep understanding of each piece of content.



AnalyzePerformance Insights

Every click, like, share, vote, view, play and buy is tracked to understand which content is engaging your audience and driving action.


Moderator Preferences

Co-Pilot observes as you curate content – publishing, discarding, tagging and requesting rights – to build a profile of your personal preferences.


Co-Pilot’s machine learning algorithm processes all of this data and applies its learnings to each new piece of content as it is aggregated, forming the predictive recommendations.

Continuously learning, measuring and evaluating the content that resonates best with your audiences, Co-Pilot helps you constantly improve content performance and reduce curation time.

The power of predictive intelligence will transform your ability to automate manual tasks, continually optimize the content you publish and create truly personalized experiences.

Fill out the form below to learn how Co-Pilot can help you continually deliver and optimize personal content marketing at scale.

See how you can start getting better content with less effort.

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