Company type | Private |
---|---|
Industry | Telecommunications content services |
Founded | 2006 |
Headquarters | Tel-Aviv, Israel |
Products | Personalized media recommendations, personalized media discovery, ad personalization |
Website | www.meemix.biz |
MeeMix Ltd is a company specializing in personalizing media-related content recommendations, discovery and advertising for the telecommunication industry, founded in 2006.
On January 1, 2008, MeeMix launched meemix.com, a public personalized internet radio [1] [2] [3] serving as an online testbed for the development of music taste-prediction technologies. [4] Subsequently, MeeMix released in 2009 a line of Business-to-business commercial services intended to personalize media recommendations, discovery and advertising. [4] [ dead link ] MeeMix hybrid taste-prediction technology relies on integrating machine learning algorithms, digital signal processing, behavior analysis, metadata analysis and collaborative filtering, and is provided via API web service. [5]
In August 2009, MeeMix was announced as Innovator Nominee in the GSM Association’s Mobile Innovation Grand Prix worldwide contest. [6]
As of 2013, MeeMix no longer features internet radios on meemix.com. On Sep 28, 2014, meemix.com went offline.[ citation needed ]
Social software, also known as social apps or social platform includes communications and interactive tools that are often based on the Internet. Communication tools typically handle capturing, storing and presenting communication, usually written but increasingly including audio and video as well. Interactive tools handle mediated interactions between a pair or group of users. They focus on establishing and maintaining a connection among users, facilitating the mechanics of conversation and talk. Social software generally refers to software that makes collaborative behaviour, the organisation and moulding of communities, self-expression, social interaction and feedback possible for individuals. Another element of the existing definition of social software is that it allows for the structured mediation of opinion between people, in a centralized or self-regulating manner. The most improved area for social software is that Web 2.0 applications can all promote co-operation between people and the creation of online communities more than ever before. The opportunities offered by social software are instant connections and opportunities to learn. An additional defining feature of social software is that apart from interaction and collaboration, it aggregates the collective behaviour of its users, allowing not only crowds to learn from an individual but individuals to learn from the crowds as well. Hence, the interactions enabled by social software can be one-to-one, one-to-many, or many-to-many.
Personalized marketing, also known as one-to-one marketing or individual marketing, is a marketing strategy by which companies leverage data analysis and digital technology to deliver individualized messages and product offerings to current or prospective customers. Advancements in data collection methods, analytics, digital electronics, and digital economics, have enabled marketers to deploy more effective real-time and prolonged customer experience personalization tactics.
Collaborative filtering (CF) is a technique used by recommender systems. Collaborative filtering has two senses, a narrow one and a more general one.
A recommender system, or a recommendation system, is a subclass of information filtering system that provides suggestions for items that are most pertinent to a particular user. Recommender systems are particularly useful when an individual needs to choose an item from a potentially overwhelming number of items that a service may offer.
Personalization consists of tailoring a service or product to accommodate specific individuals. It is sometimes tied to groups or segments of individuals. Personalization involves collecting data on individuals, including web browsing history, web cookies, and location. Various organizations use personalization to improve customer satisfaction, digital sales conversion, marketing results, branding, and improved website metrics as well as for advertising. Personalization acts as a key element in social media and recommender systems. Personalization influences every sector of society — be it work, leisure, or citizenship.
Pandora is a subscription-based music streaming service owned by the broadcasting corporation Sirius XM that is presently based in Oakland, California inside of the United States. The service carries a focus on recommendations based on the "Music Genome Project", which is a means of classifying individual songs by musical traits such as genres and shared instrumentation. The service originally launched in the consumer market as an internet radio service that would generate personalized channels based on these traits as well as specific tracks liked by the user; this service is available in an advertising-supported tier and additionally a subscription-based version. In 2017, the service launched Pandora Premium, which is an on-demand version of the service more in line with contemporary competitors.
Firefly.com (1995–1999) was a community website featuring collaborative filtering.
Digital marketing is the component of marketing that uses the Internet and online-based digital technologies such as desktop computers, mobile phones, and other digital media and platforms to promote products and services. It has significantly transformed the way brands and businesses utilize technology for marketing since the 1990s and 2000s. As digital platforms became increasingly incorporated into marketing plans and everyday life, and as people increasingly used digital devices instead of visiting physical shops, digital marketing campaigns have become prevalent, employing combinations of search engine optimization (SEO), search engine marketing (SEM), content marketing, influencer marketing, content automation, campaign marketing, data-driven marketing, e-commerce marketing, social media marketing, social media optimization, e-mail direct marketing, display advertising, e-books, and optical disks and games have become commonplace. Digital marketing extends to non-Internet channels that provide digital media, such as television, mobile phones, callbacks, and on-hold mobile ringtones. The extension to non-Internet channels differentiates digital marketing from online marketing.
Customer engagement is an interaction between an external consumer/customer and an organization through various online or offline channels. According to Hollebeek, Srivastava and Chen, customer engagement is "a customer’s motivationally driven, volitional investment of operant resources, and operand resources into brand interactions," which applies to online and offline engagement.
The Filter's TV personalisation products increase viewing, loyalty and revenue. Their data science underpins the business decisions of the world's most forward thinking broadcasters. Founded in 2004, it has ties to musician Peter Gabriel and is based in Bath, UK. In March 2022, The Filter was acquired by the Amsterdam-headquartered end-to-end video streaming provider, 24i.
Artificial intelligence marketing (AIM) is a form of marketing that uses artificial intelligence concepts and models such as machine learning, Natural process Languages, and Bayesian Networks to achieve marketing goals. The main difference between AIM and traditional forms of marketing resides in the reasoning, which is performed by a computer algorithm rather than a human.
Musicovery is an interactive and customised French webradio service. Listeners rate songs, resulting in a personalized programme. Reviewers have commented that unlike services that are governed by the user's choice of artist or genre, this method results in more discovery of artists to which the user might not otherwise have been exposed; The Washington Post's reviewer gave the example of "segueing from a West Coast R&B band to a folk–rock group from Algeria".
GroupLens Research is a human–computer interaction research lab in the Department of Computer Science and Engineering at the University of Minnesota, Twin Cities specializing in recommender systems and online communities. GroupLens also works with mobile and ubiquitous technologies, digital libraries, and local geographic information systems.
Jinni was a website-based search engine and recommendation engine for movies, TV shows and short films. The service was powered by the Entertainment Genome, an approach to indexing titles based on attributes like mood, tone, plot, and structure. As of 2015, it was no longer available to the public, but is reportedly available via API and business-to-business licensing, where it reportedly impacts businesses like Comcast's Xfinity product, as well as other businesses using "smart" entertainment search.
The United States Federal Trade Commission (FTC) has been involved in oversight of the behavioral targeting techniques used by online advertisers since the mid-1990s. These techniques, initially called "online profiling", are now referred to as "behavioral targeting"; they are used to target online behavioral advertising (OBA) to consumers based on preferences inferred from their online behavior. During the period from the mid-1990s to the present, the FTC held a series of workshops, published a number of reports, and gave numerous recommendations regarding both industry self-regulation and Federal regulation of OBA. In late 2010, the FTC proposed a legislative framework for U.S. consumer data privacy including a proposal for a "Do Not Track" mechanism. In 2011, a number of bills were introduced into the United States Congress that would regulate OBA.
MovieLens is a web-based recommender system and virtual community that recommends movies for its users to watch, based on their film preferences using collaborative filtering of members' movie ratings and movie reviews. It contains about 11 million ratings for about 8500 movies. MovieLens was created in 1997 by GroupLens Research, a research lab in the Department of Computer Science and Engineering at the University of Minnesota, in order to gather research data on personalized recommendations.
Gary Robinson is an American software engineer and mathematician and inventor notable for his mathematical algorithms to fight spam. In addition, he patented a method to use web browser cookies to track consumers across different web sites, allowing marketers to better match advertisements with consumers. The patent was bought by DoubleClick, and then DoubleClick was bought by Google. He is credited as being one of the first to use automated collaborative filtering technologies to turn word-of-mouth recommendations into useful data.
A filter bubble or ideological frame is a state of intellectual isolation that can result from personalized searches, recommendation systems, and algorithmic curation. The search results are based on information about the user, such as their location, past click-behavior, and search history. Consequently, users become separated from information that disagrees with their viewpoints, effectively isolating them in their own cultural or ideological bubbles, resulting in a limited and customized view of the world. The choices made by these algorithms are only sometimes transparent. Prime examples include Google Personalized Search results and Facebook's personalized news-stream.
Behavioral analytics is a recent advancement in business analytics that reveals new insights into the behavior of consumers on eCommerce platforms, online games, web and mobile applications, and Internet of Things (IoT). The rapid increase in the volume of raw event data generated by the digital world enables methods that go beyond demographics and other traditional metrics that tell us what kind of people took what actions in the past. Behavioral analysis focuses on understanding how consumers act and why, enabling predictions about how they are likely to act in the future. It enables marketers to make the right offers to consumer segments at the right time.
Social media mining is the process of obtaining data from user-generated content on social media in order to extract actionable patterns, form conclusions about users, and act upon the information. Mining supports targeting advertising to users or academic research. The term is an analogy to the process of mining for minerals. Mining companies sift through raw ore to find the valuable minerals; likewise, social media mining sifts through social media data in order to discern patterns and trends about matters such as social media usage, online behaviour, content sharing, connections between individuals, buying behaviour. These patterns and trends are of interest to companies, governments and not-for-profit organizations, as such organizations can use the analyses for tasks such as design strategies, introduce programs, products, processes or services.