J. Anthony Miguez (Jay)Founder/advisor for 18 years. Former VC/PE guy.

A seasoned strategy, product professional and serial entrepreneur, J. has spent his entire career driving growth for companies through innovative solutions. He has founded two successful startups, was an organizer of StartItUpDE a public-private partnership that launched the Delaware tech ecosystem and is an advisor to investors, founders and large corporations. He has taught entrepreneurship as part of the Social Entrepreneurship program at Tulane University and has also served as the Entrepreneur in Residence for the Idea Village, a non profit for New Orleans-based startups, for three consecutive years. Currently interim CEO for VL Group. Chi-city kid now residing in New Orleans.

Recent Answers

I currently run a SaaS in the music tech space (VL Group) and we are seeing an increased focus on curation. Existing curation services are owned/operated by either the labels or the streaming services. I believe the next wave will decouple curation from platform and content. This will allow tastemakers to monetize their value directly. This requires the existence of a playlist without the requirement of a platform that will allow creators to collect the data, drive new use cases and monetize. Spotify playlists are the key to driving their brand trust and I think that this tool will be sought out by other entities (brands, tastemakers, venues).

There is also a huge problem in new music discovery that needs to be addressed. Purely algorithmic and human solutions have been the two camps in this battle but I think the answer is somewhere in between. In addition to this blended approach I also think the we need to re-think what the basis of the recommendations are. Since there is a big problem with the meta data associated with tracks we will need to look at other sources for matching. A site like MusicBrainz is crowdsourcing a lot of data but that is just the first step. Songs can be matched based on any number of characteristics other then genre, artist, etc. In today’s music environment genre is increasingly meaningless and the reality is that I may have a match based on instrumentation, lyrics (all songs with the word rain in them on a day of downpours) with machine learning growing rapidly I think that understanding the listeners “intent” is a missing element.

Happy to talk more about what we are seeing in the industry or any of the thoughts above.

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