Ranker, the leading source for crowdsourced rankings with over 1 billion consumer votes on a variety of M&E topics, and ContentWise, the AI-powered experience automation and personalization company, announced a partnership that combines Ranker’s rich movie and TV correlation data models with the ContentWise UX Engine. This interface allows operators to directly use the strength of fan-based rankings and aggregate consumer opinion on their platforms, expanding viewership signals beyond their client base and dramatically improving suggestion precision.
“Ranker Insights,” Ranker’s unique consumer sentiment and affinity data, generates correlation statistics based on over 1.3 billion fan votes. In the entertainment sector, Ranker’s comprehensive picture of consumer preferences encompasses over 52,000 editorially moderated polls that create rankings for tens of thousands of TV episodes, films, characters, casts, and celebrities. Ranker’s psychographic engine discovers insights into consumer viewing habits across the entertainment ecosystem, including the walled gardens of major streaming platforms, by gathering enormous amounts of post-consumption opinion data.
The collaborative correlation data models provided by Ranker may now be performed within the UX Engine platform, thanks to “Pluggability,” a new feature ContentWise formally revealed last month for its UX personalization and content discovery platform. This new functionality, based on ContentWise Open Connector, enables operators to incorporate any external, bespoke recommendation model into the UX Engine. Operators now have the freedom and power to deploy any AI personalization model with UX Engine thanks to Pluggability, which represents a substantial improvement in content personalization.
Pluggability and Ranker Insights offer previously unheard-of levels of recommendation accuracy and one-of-a-kind content discovery paths. More specifically:
1) Operators will be able to access Ranker’s enormous catalogue of editorially-curated lists organised by votable rankings to power home screen carousels directly within ContentWise’s UX Engine. These carousels display topical material recommendations tailored to the user’s preferences. Examples of Ranker lists include:
- The Totally Hilarious Movies of All Time Movies with the Best Soundtracks
- Comedy Sequels That Might Outperform the Originals
- Great Comedy Shows About Coworkers and the Workplace
- 100+ of the Best Adult Animated Shows
- The 50+ Best TV Talent Shows, According to Fans
2) “Fans May Also Like” Carousels: Ranker’s data will fuel “Fans Also Like” carousels on movie and TV show description pages. These carousels combine Ranker’s affinity correlations data and ContentWise machine learning capabilities to expose title-based suggestions based on shared user sentiment rather than program-level metadata. This benefit enables operators to distribute a broader range of their catalogue while keeping relevancy.
“We are thrilled to be partnering with ContentWise to provide adaptable, data-driven solutions to their impressive clientele of video operators, digital publishers, and online retailers,” says David Yon, SVP and GM of Ranker Insights. “Over the last few years, our Ranker Insights platform has made extraordinary strides towards solving the problems associated with targeted marketing, editorial, and merchandising practises, and we are confident we can help make ContentWise’s already successful CX solutions perform even stronger.”
“The combined power of Ranker’s consumer sentiment data and ContentWise’s personalization technology brings fresh new discovery and recommendations use cases to our partner operators,” says Renato Bonomini, VP of Sales Engineering and Ecosystem at ContentWise. “On the editorial side, topics from Ranker Insights are directly available within UX Engine to support content curation.” Ranker Insights evaluations improve the computational quality of our recommendation algorithms.”
