The Summit, Dublin

Engineering Serendipity: Why Web Summit hires Data Scientists to Help You Network

The Summit

Excitement is building in advance of Web Summit next week. In just four short years it has grown from just 400 attendees at the first event, to 20,000 who will throng the RDS next week.

In a post on the Web Summit Blog, founder Paddy Cosgrave admits that, by traditional wisdom, theirs is an unlikely success:

Arguably no technology conference in history has grown faster. Somehow we’ve achieved that growth with no background in the conference industry and no resources to speak of, and all from a pretty peripheral location called Dublin.

So what’s their secret?

Data.

Of course every conference has data. It’s what you do with it that matters. At Web Summit, they work the data to make sure that conference participants get the most out of the experience: especially when it comes to networking.

Why do we go to events like Web Summit? To make connections and build relationships; to meet people who can help us reach our goals.

As Paddy explains it, if you make good connections at Web Summit, it’s not by accident.

While traditional conference companies fret over manually curating seating plans, compiling speaker lists and handpicking invites for networking events, we approach the challenge from a technical and mathematical point of view. We build algorithms that take into account who you are and who you might benefit from being on a pub crawl with or at a table with or in a meeting with.

He calls this approach “engineering serendipity”, and he believes it’s the secret to their success.

… what we lacked in experience, funding and location, we’ve made up for by building software and using data

And as Web Summit expands to include other events around the world, such as the Collision Conference in Las Vegas, the algorithmic approach is at the heart of their strategy.

With over 100 people already employed, Paddy says they’re still hiring:

We’re always looking for talented people across a huge range of fields including computer vision, complex systems, network analysis, machine learning, data architecture and more. We also need PMs. Or if you’d just like to work on some interesting non-obvious challenges, you’ve got my email.

 

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