However, brands will likely want to be more targeted with their money to hopefully see better results from music advertising. Typically eschewed as selling out, artists will undoubtedly continue to want to work with brands. Music data analysis company, Next Big SoundвЂ™s recent 2014 reportВ highlighted how brandsвЂ™ advertising dollar could be better spent.В In 2014, artists saw significant growth in their digital reach as a result of brand endorsements however, for brands their advertising reach did not extend their reach beyond the value associated with a traditional paid digital ad. If the listener prefers indie rock music when in their bedroom, the speaker will play that type of music once it realizes itвЂ™s within that room. One example is the Cone,В a speaker that learns a listenerвЂ™s music preferences based on where that person listens to the speaker. A different approach is accumulating data passively through smart audio devices. Within this paradigm, the best content will emerge because the crowd deems that the context provided around the programming meets their expectations. In the meantime, music programming that relies on crowdsourced curation, similar to TwitterВ or Reddit,В can surface highly contextual programming (e.g. It will take time to gain listenersвЂ™ trust to connect these types of data streams to music services. Finally, leveraging biometric data from fitness bands could enable internet radio providers to push music that reflects the perceived activity or mood of that listener. and reference those listenersвЂ™ music preferences. Listeners that arenвЂ™t generally music consumers could still receive personalized experiences if internet radio providers could draw from their social data to find people with similar tastes in other areas such as films, foods, books, etc. Within a hyperlocal context, internet radio services could push music reflective of microcultures in neighborhoods, parks, rooms of a house, etc. To date, location information has primarily served to provide music programming experiences reflective of the general tastes in those regions.

In particular, location, social, and biometric data streams will provide the most relevant inferences for personalized listening experiences. In the last three years, labels have signed deals that make their music libraries legally accessible on-demand, setting the stage for this transformation in digital discovery based on big data. Lastly, the vanguard (major record labels) are now willing to make this digital shift. With the decreasing costs of streaming, collecting and storing large sums of data, as well as growth of powerful tools to analyze it, our ability to explore and draw inferences from this wealth of information is seemingly endless. The swath of personal dataВ that comprise our tastes is growing, which in turn means we are also able to better understand the tastes of similar people. However, the barriers to this hyperpersonal internet radio are slowly being eliminated. This type of personalization has already begun in advertising, but hasnвЂ™t been well implemented in internet radio. Imagine passively being pushed the right music that helps you wake up, motivates you to run faster, work more productively, and more. Internet radio will need to match every part of your day. With Americans now spending more time on their phonesВ than watching television, there has never been a more opportune time to maximize internet radio experiences.ДЇor this potential to be realized, companies will need to provide highly personalized listening experiences that have yet to be fully optimized. Pandora and Youtube) are used for streaming music. Two of the top five most popular apps in America ( Young adults (18-24) listened to internet radioВ more than terrestrial. In 2014, one thirdВ of Americans used their phones to stream music. The majority of people prefer a lean back experience. Lean back listeners hear music programming via a playlist or radio station (think вЂњset it and forget itвЂќ), whereas lean forward listeners actively select individual songs. Before I go further, let me make an important distinction: there are two types of listeners, lean back and lean forward. This is because listening to music can be enjoyed while doing other activities. More commanding of your attention than film, television, or books. Internet radio has the potential to be the most ubiquitous form of media ever.

What program to use for internet radio