Personalizing the viewer journey to maximize engagement and retention
The global leader in personalized content discovery, our intelligent platform draws on over a decade’s worth of expertise in data and information science.
It helps you deliver meaningful personalization proven to boost viewer engagement and retention.
We apply a blend of behavioral AI and deep-learning algorithms, aligned with best practice techniques, to help you meet business objectives and KPIs.
ThinkAnalytics customers typically find that viewing time per subscriber increases by up to 60% and the number of channels watched increases by up to 30%.
A World of Content
In today’s content-rich world, consumers are overwhelmed by the choice available to them on TV, Video on Demand, etc. Initially this is exciting for the new consumer, but it rapidly becomes an irritating experience as, each time, they click through channel-after-channel on the EPG or wander through the VOD library.
The result – people stick to watching what they already know, and after a while begin to question whether they are getting value for their subscription money. In this situation customer retention becomes a problem, and raising ARPU similarly challenging. The fact is consumers cannot select what they don’t know. Intelligent Navigation powered by personalized Recommendations solves this problem, thereby improving retention and raising ARPU.
The ThinkAnalytics Search and Recommendations Engine uses proprietary advanced Artificial Intelligence and Machine Learning techniques to provide a powerful, scalable, real-time and comprehensive multi-content/multi-platform Recommendations Engine supporting across content delivery of recommendations and search to multiple platforms such as the set top box, mobile, web, smart TV, games consoles, and others.
Enabling Discovery & Broadening Taste
Exposing customers to a wider range of content allows you to improve customer retention and grow ARPU. ThinkAnalytics engine powers content discovery and recommendation personalization – providing measurable impact on viewing behaviour. Results reveal that after deploying ThinkAnalytics across millions of households, the amount of viewing time per subscriber increases by up to 50%. In parallel, the number of channels the average subscriber watched increased by up to 35%
Harnessing The Power Of Search
Intelligent Search complements the ThinkAnalytics recommendations platform. By adding Search to Recommendations the viewer gets the best of both worlds with fully personalized and appropriate recommendations plus the ability to search for specific items of interest and content, again with added personalization and multi-language support.
Metadata Enrichment to Understand Content
ThinkAnalytics has considerable experience working with major and regional metadata providers worldwide. Our Recommendations Engine metadata enrichment process supports 43 languages and enables automatic classification of your content, meaning that you can benefit from no ongoing fees for external manual classification services. Syndicated programs can be automatically classified in a consistent manner and one-off programs are also easily classified, in addition to your ability to retain editorial control of the automated classifications.
Business Rules control Marketing Bias
Flexible Business Rules give you control over your operational analytics environment, allowing business and consumer centric rules to be captured, managed and applied both online and in batch. This ensures the system can balance strong consumer centric objectives with those of the business’s marketing objectives. The ThinkAnalytics Recommendations engine provides prioritization of content through the use of the fully flexible Business Rules Management System. The flexible business rules engine can be used to define a variety of rules to filter, prioritize, and promote as required.
Editorial and Marketing Tools
Complementing our content discovery platform, the ThinkComposer UX engine gives editorial and marketing teams the ability to create, test, manage and modify use cases and campaigns in minutes. You can combine different recommendation types to find the perfect blend of personalization, popular content, trends, and editorial control.
ThinkComposer is a unified UX engine giving you the controls to manage, modify & configure and add multiple recommendation APIs and use cases to enable powerful new user experiences through an easy-to-use Use Case Builder interface. These use cases may be made up of individual recommendation types or combinations of types including algorithmic recommendations, search and editorial recommendations.
Through the use of ThinkComposer publishing process there is no need to redeploy the software to make changes to use cases, add use cases, modify algorithm parameters, update editorial campaigns, A/B test, etc. – these can be published to development/test/production environments without the need for new software builds to be deployed.
ThinkEditorial is an intuitive editorial curation tool that gives editorial and marketing teams complete control over editorial and curated carousels, campaigns and lists.
ThinkEditorial provides an easy to use interface for campaign control allowing editorial, content and marketing teams to create, modify, manage and publish editorial/curated carousels, campaigns and list via an easy to use search, drag and drop interface.
Content discovery and recommendations is seen by many as purely the domain of algorithms with the creative input of editorial teams often neglected. ThinkEditorial redresses this balance allowing editorial and marketing teams to harness the power of the technology and apply their own unique insights, controlling the content the recommendations can be generated from, promotional offers and the techniques to be used all from a user-friendly drag and drop interface.
It lets you apply your own insights and techniques and insert specific featured content and promotional offers to the pool of content recommended by the content discovery engine.
This is ideal for promoting new TV series and movies, for example, to different audience segments.