Recommender_E-Contenta

E-CONTENTA RECOMMENDER SYSTEM Product Description E-Contenta Recommender System in Brief 30% LTV +32% session time + 40% conversion to subscription + 240% CTR Decreased CAC 40% Decreased churn 10% Deployment SaaS, On-Premise Response time: Less than 300 milliseconds Scalability: By adding hardware (nodes) enabled by stack of technologies - Spark, Kafka, Aerospike Implementation terms: License price: depends on QPS 2-4 weeks Algorithms The algorithms recognize, differ and process recommendations for all content types At E-Contenta we analyze people's behavior online and can predict what content and ad each user would like. E-Contenta applies AI and machine learning algorithms to build user-centric walled garden where communication with each individual is relevant and personalized. We serve digital media companies and help them gain more from their existing company ecosystem (e.g. platforms and user base) by making personalized ads and content recommendations. E-Contenta provides a media customer with a full stack of software tools needed to build personalized communication in all touch points at all platforms: Data collection We will collect relevant data from the Client in the form of a database dump or/and with the help of pixel script about: Launch As usual it takes 2-4 weeks to monitor existing IT systems of our Client, create a roadmap and specify KPIs of the project, collect data, integrate systems via API and launch MVP to make a proof the concept. A/B testing & Trial period For one month after the launch we will have a trial period and A/B test. As usual users click 1,5 - 2,4 times more often to content recommendations made by AI compared to those made by editor. About E-Contenta The company operates since 2015 and serves IPTV and OTT providers, online radio, ebook retailers, publishers. Join the club of our honored partners and customers together with Ericsson Mediaroom, Google Double Click, Viasat, Beeline, Bookmate and many more. Contact Zoya Nikitina, CEO [email protected] e-contenta.com 781-215-25-77 33 W 17th St, New York, NY 10011 The recommendations can be applied at all touchpoints – website, mobile app, emails and push notiﬁcations. Recommender system SSP (Supply Side Platform) DSP (Demand Side Platform) E-Contenta recommender engine is based on two algorithmic approaches of content and behavioral similarity. The system works in real time and identiﬁes users’ mood and needs at the moment. Articles Videos Audio/music Pictures Ebooks users (ID, IP, platforms (mobile/web, iOS/Android/Windows), etc.) content/goods/products (ID, name, authors, date of the content’s release, tags, etc.) connections between the user and the content (clicks, views, subscriptions, registrations, purchases, sharing, likes) PROVEN KPIs

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E-CONTENTA RECOMMENDER SYSTEMProduct Description

E-Contenta Recommender System in Brief

30% LTV+32% session time+ 40% conversion to subscription+ 240% CTRDecreased CAC 40%Decreased churn 10%

DeploymentSaaS, On-Premise

Response time:Less than 300 milliseconds

Scalability:By adding hardware (nodes) enabled by stack of technologies - Spark, Kafka, Aerospike

Implementation terms:

License price:depends on QPS

2-4 weeks

Algorithms

The algorithms recognize, differ and process recommendations for all content types

At E-Contenta we analyze people's behavior online and can predict what content and ad each user would like. E-Contenta applies AI and machine learning algorithms to build user-centric walled garden where communication with each individual is relevant and personalized. We serve digital media companies and help them gain more from their existing company ecosystem (e.g. platforms and user base) by making personalized ads and content recommendations.

E-Contenta provides a media customer with a full stack of software tools needed to build personalized communication in all touch points at all platforms:

Data collectionWe will collect relevant data from the Client in the form of a database dump or/and with the help of pixel script about:

LaunchAs usual it takes 2-4 weeks to monitor existing IT systems of our Client, create a roadmap and specify KPIs of the project, collect data, integrate systems via API and launch MVP to make a proof the concept.

A/B testing & Trial periodFor one month after the launch we will have a trial period and A/B test. As usual users click 1,5 - 2,4 times more often to content recommendations made by AI compared to those made by editor.

About E-ContentaThe company operates since 2015 and serves IPTV and OTT providers,online radio, ebook retailers, publishers. Join the club of our honored partners and customers together with Ericsson Mediaroom, Google Double Click, Viasat, Beeline, Bookmate and many more.

ContactZoya Nikitina, CEO [email protected] W 17th St, New York, NY 10011

The recommendations can be applied at all touchpoints – website, mobile app, emails and push notifications.

Recommender systemSSP (Supply Side Platform)DSP (Demand Side Platform)

E-Contenta recommender engine is based on two algorithmic approaches of content and behavioral similarity.The system works in real time and identifies users’ mood and needs at the moment.

ArticlesVideosAudio/music

PicturesEbooks

users (ID, IP, platforms (mobile/web, iOS/Android/Windows), etc.)content/goods/products (ID, name, authors, date of the content’s release, tags, etc.)connections between the user and the content (clicks, views, subscriptions, registrations, purchases, sharing, likes)

PROVEN KPIs