Startup #3: Bringing useful strangers together

Startup #3: Bringing useful strangers together

Ever wished that who you could discover the most relevant people at a coworking space? πŸ”

Done with leaving meeting people to random chance? 🎲

One of the main reasons coworking exists is to facilitate useful connection between people – each person sat in a coworking space is surrounded by dozens or more of potentially useful connections (and generally some pretty cool people).

But how many potential opportunities are lost due to people not being aware of the background, skills and experience of others around them? The perfect cofounder or the person holding the answer to that problem you've been stuck on might be just a few desks away... but it's effectively luck whether you actually meet and whether your overlapping interests are exposed to each other.

It's kind of fascinating to think of all the opportunities that could've been, had those 2 people who were sat just 3 metres apart actually discussed what they have in common.

In reality, professional connection comes in just two main formats:

πŸ” Online to offline: Unlimited 'search' space – in effect you can reach out to anyone on the internet. Now, whilst you can attempt to open a dialogue with anyone, in reality it filters down by:

  • Who is open to having a conversation with you
  • The trials of meeting for a real life coffee or conversation (which is typically the best format for an introduction). Take the example of LinkedIn: how often does a new LinkedIn connection result in a useful or meaningful connection? From what I can tell, it's beyond rare.

🎲 Offline, left to random chance: Very limited 'search' space – it effectively comes down to random chance; either crossing paths with someone, or having a contact that knows someone. That said, it is obviously much easier to meet up with someone who is geographically co-located than someone that is far away. So the filters at play for offline are:

  • Geographic – who happens to cross your path in a professional context
  • Informational – somehow finding out information about the person
  • Relevance to your project/work
  • The person's interest in engaging with you

Where am I going with this?

Well, my main hypothesis is that it would be useful to expose people's backgrounds and skills to each other based on close proximity (e.g. being close enough to grab a coffee/within a few minutes walk).

Is the problem real?

I conducted a bunch of couch interviews with people from my coworking space, Dojo Bali to understand how others currently meet people to collaborate, gain knowledge and work with. πŸ’¬

What I learnt was:

People trying to meet in a coworking space would ask the community manager or a friend to connect them up with a relevant contact... they seek a referral of some kind. Otherwise they can use the community noticeboard or Facebook group, but these tend to have limited impressions and an item be easily missed/buried under other content.

Content is a big part of how people collect signal on if someone would be useful – "you can tell if someone really knows their stuff when they're giving a talk." Much in the same way that people use Twitter to find relevant people via the work/content they are putting out there.

Whilst I'm keen to make the network function without so much emphasis on people's appearance (versus Bumble Biz, which is bizarrely centred on appearance), it seems that appearance does still form some element of signal about whether someone would be worth/safe to meet with.

Activity is important – how active is someone with their business/in the network? It's not worth reaching out to someone who's moved on to new projects or won't respond.

Another important aspect was around how real is someone's work (versus LinkedIn's posturing). I.e. have they done the things they've said? Do they actually know what they are talking about?

What's out there right now?

Shapr & Bumble Biz – These use a Tinder-style swipe UI to show connections which are within a distance radius. This has a strangely high emphasis on aesthetics, with weak profile info (skills are vague and background unclear). Distance can still be large (100km) so doesn't really reduce proximity enough to reduce barrier between 'discovering someone' digitally and meeting them physically.

Nexedus – this is the software that lots of coworking spaces use to manage their spaces. The social aspect is a job for the coworking space to implement, and is buried deep inside a billing web interface, inside the coworking space's site. This means that the social section is rarely accessed by coworking space members (if they know about it at all). Further, users' details are vague and high level... so not that useful anyway.

LinkedIn – exists to facilitate connection but in reality is high-spam, information is self-declared (mixed accuracy), and the 'distance' from online to offline is substantial (very few things make the leap from a digital connection request to an actual chat).

A possible solution

βœ… Hyper-local discovery for meeting nomad coworkers around you 🀝

Let users discover other people in the same space who have worked on similar things or have a background that relates to what you're working on at that given moment.


First test – a landing page to gage initial understanding and interest ...Assuming it does, then I'll go on to build it more fully.

So I built the 1st landing page in a one-day sprint:

The initial response was good, so I spent some time validating and getting to understand the problems of 'professional connections' by interviewing coworking space users πŸŽ™

This was SO USEFUL – especially finding out the workarounds ↩️ that people were currently using and where it just was not working for them.

I spent the next week quickly designing the first version of the app in Sketch:

The week after, testing with friends from my coworking space:

And gave it a big sharing push on 2 FB posts and amongst some friends, getting to 120 email signups in 4 days – a good first sign of interest!

From this point, I started building a proper product implementation of the design to test. By far the most complex thing I'd ever tried to build, it incorporates in-app chat, search, geolocation, push notifications, email notifications, a Chrome extension (for off-site location updates), pass-through database tables and more 🀯

MVP summary:

Some pretty neat things about Skillmap:

🀯 It's a crowd-sourced geographic search engine for people

πŸ™ˆ It's appearance-blind – no visuals until you connect with someone, it's just about skills & interests

🀝 It's invite and referral-only – ensuring a high quality network

From the ground up, Skillmap has been designed to cut out the fluff that LinkedIn is filled with:

Instead of users writing verbose bio paragraphs which get parsed into keywords, Skillmap acts as a human search engine, and users simply choose the keywords they will be indexed by.

This means more accurate ranking of results πŸ”’, easier match-making πŸ‘­ and there's fundamentally no space for bullshit πŸ™…β€β™‚οΈ At a later stage, I hope to add verification of user attributes.

At its core, Skillmap aims to be a new kind of bias-free search engine for local talent.

How do we remove bias?

Well, we only use first names, you choose an emoji to represent yourself, and there's no sense of gender or physical appearance – it’s just about your skills and proximity.

They say all social networks end up becoming dating apps... ❀️ But as Skillmap is a collaboration network, we are sidestepping that by removing appearance from the equation altogether. Instead, we're building from the ground up with nothing but skills and professional attributes.

In Skillmap, users share their location with each other. Because of this, we have a number of privacy measures, including:

  • Ghost Mode πŸ‘». Anytime that a user wants to disappear from view, they can toggle Ghost Mode on, and simply drop off the Skillmap radar.

  • Pseudonymous profiles. User's full names aren't revealed without an accepted meet request.

  • Invite-only – users effectively recommend their friends into the circle, ensuring some minimum threshold of quality.

  • Locations aren't shown at full precision on the map.

Another key part of the MVP is the Chrome extension. Why?

Skillmap is a web app, so to accurately connect a user with those around them, we need to check their location, but (sadly) they aren't always going to be on our webpage. Adding a Chrome extension means that we can keep locations fresh. For total privacy control, users can also toggle Ghost Mode straight from the extension, making themselves drop off the map and stopping location updates.

Soft launch

Skillmap has been soft-launched! I did this by slowly inviting those on the email list within a single city, Budapest (to ensure a minimum density of users).

With a social, location-based app, the biggest challenge is having enough density in any area that a user will have enough others nearby to interact with. Without this, a user will find no value for them in the product and never pick it up again – a ruined first impression.

So how to tackle this?

A key part of Skillmap is its launch mechanism. In the 'Discover' view, where users can see others at a broader geographic scale, we also showcase coworking spaces (and soon, which users are at them). By teaming-up with coworking spaces for promote each other, we are able to reach a bigger pool of users in the same geographic region. All at a very low marketing cost.

Another component is passive design. By designing Skillmap so that only one party needs to be active to engage the other, there isn't a burden on anyone to regularly visit in order to still get value. However, once a user does get re-engaged, they are then more likely to remain active and engage others.

Update: now has users in 5 continents! πŸ’₯

Even in the short period that users have been on the app, they've taught me a lot. Just a few of Β the things that I've added based on user feedback:

πŸŒͺ️Map data filtering (show & hide specific skills) – the map view can have a lot of information, so I added the ability to filter what is currently within view. This makes it faster and easier for an intent-driven user to complete their search task.

🀼Interests – users also want to meet others socially. When a digital nomad arrives into a new city, they are also seeking potential friends, so I added the concept of interests to the app. This also makes profiles a little more human, which is a key part of the IRL meet-ups that Skillmap is really all about.

πŸ””Email msg notifications – users don't miss new messages, so we catch and send updates at a set time interval (to avoid overload).

Try it and let me know what you think:

Full launch

Coming soon... ⏳


In progress... ⏳