One of the top objectives of advertisers has always been to increase the relevance<\/strong> of a particular ad to the specific consumer who is receiving the ad.<\/p>\n\n
Zample<\/strong> is a new start-up that is helping brands increase the relevance of their advertising by listening to – and automatically recognizing – the media which surrounds a consumer. This information can have great value for mobile app publishers, and may spawn some interesting new marketing services. \n How it works<\/strong><\/p>\n \n For over a year now, Zample’s servers have been “listening” to many many TV shows, movies, songs, etc in order to build up their media database. Here’s how their system would work from the viewpoint of an app developer:<\/p>\n At a macro level, a publisher could learn a lot about their user base, for example the “Top 5” TV shows that have been watched by their users, or the “Top 5” TV networks, or the “Top 5” ads that have been seen. In other words, it’s a bit like having a private Nielsen system monitoring the media habits of the app’s userbase.<\/p>\n This sort of information can be very beneficial for publishers, as it lets them provide better audience profile data to prospective advertisers, and therefore can increase the value of their ad inventory.<\/p>\n \n Images too<\/strong><\/p>\n \n The Zample system has also been designed to work with images, and there is a separate image SDK available to app and web developers. <\/p>\n This lets them analyze the images contained in any app that features an image feed, for example Twitter. <\/p>\n \n More to come…<\/strong><\/p>\n \n The Zample service is still very young, and one can see there are a number of additional ways they might exploit this technology.<\/p>\n In the simplest case, the same system with a somewhat more sophisticated backend could allow for more individual targeting as well. For example, a brand could request: “display this ad only to the subset<\/em> of users that usually watch Monday Night Football.” <\/p>\n Another option would be to support actual time-synchronizing of advertising with consumer activities. This would enable an advertiser to request, for example: “display this ad, but only at the moment when the consumer is actually watching <\/em>Monday Night Football.” There are certainly some potential consumer privacy concerns that may have to be addressed with this, but the company is aware of them and seems to be working to avoid any of these issues.<\/p>\n Zample might also be incorporated with some app primarily for “content discovery”, where the user them self wants to know the identity of a particular show or song, perhaps linked to an m-commerce site to purchase it.<\/p>\n Finally, if Zample becomes widely adopted, there would be the possibility of providing information back to the brands. They would be able to provide information about the profile of the people who hear their ads, for example what media they consume, what apps they use, what other ads they are exposed to, etc.<\/p>\n Additional monitization options such as these will certainly take some work and undoubtably there will be hurdles to overcome. However, given a fundamental media recognition technology such as this plus a detailed knowledge of the advertising ecosystem, and combined with an open, developer-friendly approach to productization and monitization, I’m sure over the next couple of years we’ll see some interesting new services coming from Zample.<\/p>\n
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\nZample’s service is based on ACR: Automated Content Recognition. Using patented and patent-pending technology, Zample automatically recognizes a wide range of the media that surrounds us all, including live TV, images, video streams, movies, and national broadcast advertisements. <\/p>\n\n