Bandsintown’s Technology Builds Community Between Artists And Fans


Fabrice Sergent is a serial entrepreneur. He heads Bandsintown and a team of 65 people working with a simple concept which is diabolically complicated to provide. Bands is the largest search engine for events in the world. They currently have approximately 70 million end users, mostly in North America and Europe. Bands’ email campaigns send about 10 million people monthly to ticketing companies. Half of them buy tickets for smaller shows. The company works with 43 ticketing companies and 44,000 promoters.

Here’s their core concept: you tell Bands which are your favorite performers, and they tell you when those acts are coming to your town.

Why is this important? Well, several reasons. Ticket distribution is messy. Often, fans never know an event is for sale until the day after it went off and they hear about it from their friends who went or read a review online. Alternately, there are few ways in which artists can maintain continuity with fans who appreciate their work but don’t maintain social media connections with them. And, finally and perhaps most importantly, there are massive servers filled with data related to who purchased tickets or who attended events, but that data lives behind gated access portals and it is no small undertaking to acquire, sort and utilize it in a cost-effective way.

Fabrice, his team and Bands have built a machine which acquires data from fans about acts they prefer, then matches the insights gained with data from others of similar tastes to power their own custom recommendation engine. As that engine learns more about the likelihood a particular fan might like an act which the fan has not yet identified as a favorite, it recommends to the fan this may be a show worth attending a show as the parameters align with what the fans already likes. They have also partnered with Shazam to further build tools of recognition into their systems.

Building and maintaining this ecosystem is complex. The idea sounds easy, but it’s not. To execute it, Bands must maintain a real time database of consumer preferences where the acts which everyone’s individual profile identifies must be tied to the most likely nearby venue stop. Then, when a tour is announced, Bands must sort the tour and match it to the consumers who follow the act. If all the tour information came from a single source this would still be daunting just because of the scale of the ask. But, with artists, venues, and theaters all as part of the mix, the information about where, when, and how much the tickets cost for each event come in from dozens of different providers. Big tours put out by a company like Live Nation still have stops in venues controlled by AEG. Small tours might only have listings on their own website for local rooms in each city. The more sources from which information is drawn enhances the possibility of getting the data wrong and adds to the complexity of the project.


Just to make this project even more intricate, Bands’ algorithms learn the music preferences of their consumers then apply a predictive model to suggest artists to fans who they may not know, but their musical taste as identified by their self-selected preferences suggest they should. This leverages the preferences which consumers provide to Bands so that consumers get alerted to other performers they might enjoy, and they performers get the benefit of organic growth in their fan base.

The scale at which Bands operates is impressive: with 70 million fans and average monthly user numbers of approximately 250 million. This powers both the ability for artists to sell tickets and for Bandsintown Amplify to monetize their advertising program for acts, labels, and consumer brands utilizing their 150 million average monthly users.

Bands is an artist facing company which has 560,000 artists, including 90% of the top 4,000 artists in the US who list their tour dates on the platform for free. Only those artists who register an account can get the benefit of the Bands recommendation engine. Once registered, artists get use of a full CRM suite at no charge. In addition, the artists can capture contact data about their fans including email addresses and telephone numbers. Bands is, in effect, an alternative selling arm for the artists. As Bands’ model expands, artists can use them for merchandise drops with NFT distribution soon to follow.

In our conversation Sergent did not directly spell out directly Bands’ revenue model, but it’s not any great secret. First, their execution is excellent, and their reach is broad. When you send 10 million people a month someplace where they spend money, you get some of that money in return. Likely every deal has some customization, but all of them are premised on the idea of traffic which converts only flows if you pay the company which delivered it. In addition, demand is strong from consumer brands trying to affiliate themselves with live entertainment, so those are the buyers of data about and access to the fans who make their preferences known to Bands.

While live entertainment was shut down due to the pandemic, Bands pivoted to helping distribute information about and links to artist livestreams. This is, in part, because of Sergent’s belief live music is the last resort for freedom of speech. By helping grow public awareness of performances, he in engaging and encouraging the audience to assemble.

The name Bandsintown is something of a misnomer. The platform also handles classical music performance, DJs and comedians, with podcasts to follow in the near future. Bands’ logic also helps manage fans’ calendars, reminding them 15 minutes before the start of a live stream and three days before an in-person performance. Finally, Bands recently launched community group webinars and training.

I found Fabrice Sergent to be a deep thinker and very well versed in all elements of live entertainment. Our conversation was fun and informative. Below are links to the podcast in both video and audio podcast format:

Data is a funny beast. It’s a puzzle which has to be constantly realigned and solved. The machine which is Bandsintown helps both ends of the equation: fan and artist alike see the benefits of being matched and information distributed so that the next time a favorite artist is in town the fan knows to buy a ticket and one more cookie drops into their file which may just lead them to something else next.

Fabrice Sergent and the Bandsintown team are pioneering new ways to employ data to bolster both demand and distribution about live performance while the artists on their platform also gather useful data to enhance that connection. This is technology in action navigating the endless variations of where and how event tickets are sold and building a clear path for both the artist and fan to follow where they wind up together at the performance space.


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