| Website | plista.com |
| Category | Web |
| Phone | +49 30 275 77 670 |
| Employees | 17 |
| Founded | 2007 |
| Unattributed, 11/08 Peter Schuepbach Christophe Maire Draper Investment Company |
plista provides a recommendation and personalization platform based on collaborative filtering and social graph applications that allows to connect content, products, people and preferences to the benefit of publishers, users and marketers through the internet, mobile phones and other devices.
Market scope is applicable for all kind of content where individualized interest could be extrapolated to recommendations through collective interest (e.g. products, ads, people, etc.).
With plista end users can rate and discover new items in real-time.
plista is positioned as an end user-centric B2B-service and offered through diverse interfaces. It is currently in private beta.
The recommendations system works cross-site (items from one site are recommended on another), cross-domain (central preference aggregator) and inherits diverse social components.
Risk-free distribution (for users and publishers) is leveraged through a predictive targeting business model and a marketplace for onsite and cross-site recommendations.
The company which started to develop its core technology in 2006 was originally founded in Berlin is planing to move to the Silicon Valley in 2009.
| Website | plista.com |
| Stage | Private |
plista’s first product is a browser extension that personalizes existing web sites by overlaying and re-ordering existing content with one click. There is no integration need from the publisher site plista while plista anonymously follows what users like and don’t across sites. They receive personal web pages all over the web and individual recommendations based on their preferences. Users find related articles and products and are able to share this relevant content with people that really like it.
plista is an internet-based network that allows – by means of automated collaborative filtering (extrapolation of previous preferences), item-based filtering algorithm, and related data-mining techniques – for assigning of individualized recommendations to every possible item (content, product, services, advertising, etc.) on various channels (internet, mobile devices, VoD, etc.).
With plista social and personalized targeting methods as well as trusted referrals become applicable globally throughout the internet, mobile and other devices - marketers will be offered a service to target, personalize, localize and mine rich user data of prospective clients or customers with the customer controlling his recommendations (pull model) instead of receiving uncontrolled active advertisement (push model).
