entrepreneurship, Lessons Learned, startup

On Location Based Services

Painted in Waterlogue

Writing on the Wall: A Business Model Canvas, complete with festively colored Post-Its, Atherton, CA June 2013.

This post has been gather digital dust in private draft form since May 2013. I thought I’d finally publish it to share with anyone interested in location based services.

Preamble

In what now seems like eons ago, I founded a location based tech startup called “Gauss — The People Magnet”. It took me on a roller-coaster ride around the world — from the front page of The New York Times to near personal bankruptcy in the course of about two years. It folded before we got somewhere significant. If you’re interested in the background for founding ‘Gauss — The People Magnet’, there are a couple of old posts for that.

In this post I’m completely cleaning out the closet with my thoughts and experiences related to that startup, including potential revenue sources and business models. It’s a long and winding read — a very mixed bag, assembled from scattered notes.

Caveat Emptor in 2016: If any of this looks familiar or straight forward today, rest assured they weren’t when we started out back in early 2011. To wit: successful monetization of non-dating social discovery apps arguably still hasn’t happened yet.

tl;dr

In my experience with Gauss and doing customer development, B2B is the way to go for money if you are not doing a dating service. It’s all about relevance and context, about jobs to be done.

The Problem with Social Discovery

To sum up the biggest challenge with social discovery apps as I have learned to understand it, I’ll borrow an analogy from baseball — and dating;

The largest problem being getting from 1st base to 3rd base.

What do I mean by that?

First base: I now know you exist, you now know I exist.

Second base: I communicate with you, you communicate with me.

Third base: Our interactions will lead to valuable events / relationships in the real world (aka value is delivered and accepted, perceived or real) to the order of we keep on using this service again and again.

In the world of dating apps, this should be an obvious progression. And it is — for obvious biological reasons.

For anything else than dating — where the context is not mutually understood and accepted and relevance is not clear and high — getting to third base is a pipe dream.
gauss_pro

 ‘Gauss – The People Magnet’ – Basic Assumptions

The basic premise was the belief that:

  • There is significant value in providing proprietary location-based information RELEVANCE delivered just-in-time in CONTEXT
  • It is now possible to deliver RELEVANCE in CONTEXT in new and more efficient ways that was previously not avaible
  • A significant number of people and/or organizations will also recognize the value of delivering RELEVANCE in CONTEXT in these new ways and to the extent of paying for it

It looks a little something like this:

a venn diagram

The Problem

problem

The original framing of the problem went something like “We constantly miss out on great new opportunities all around us because we simply don’t know that they are here, right right now. We keep passing people like strangers in the night because we don’t even know that they’re there – let alone knowing how we are similar and why meeting up and connecting with them would be mutually beneficial.”

Yeah, that’s not going to win any pitch prize for specificity – but we were never particular oblivious to, nor coy about the fact that this was  going to be the starting point of a longer discovery process for us.

The Solution

solution

The solution pitch went something like “A mobile app that notifies you when opportunities are nearby and help pull people together, providing both context and pretext to meet up and connect. It’s like a People Magnet for your pocket.”

Yes. Abstract. But you’ve got to start somewhere.

The Concept

concept

The theoretical construct behind Gauss in one image, complete with lolcat typo.

Most people just saw the iOS consumer app, which was only natural as it was the vehicle we pimped actively in public. We needed an actual application to prove the abstract tech concept – or at least so the thinking went.

However, one of the core motivations behind Gauss was to build a cloud-based technology stack that would enable us to discover the most interesting markets or problem sets by being able to flexibly and quickly pipe in new relevance to test in the form of tapping into existing interesting APIs and looking to see if there would be value in looking at the aggregate across them to come up with new and perhaps previously hidden relevance – And to the point of also being able to offer these services per API, e.g. as a B2B SaaS.

One of the advantages of looking at a lot of data sources is that you can deduct or triangulate where a person is located at certain times without that person having to enable GPS tracking on their device or manually checking in to a very high level of probability.

Some services also allows you (or allowed you, as with the case of Foursquare who later cut this ability off) to look at other people’s data on their behalf – to a certain level – enabling you to mine even more data and doing even more interesting pattern matching.

An underreported ‘freaky’ feature of our early product was that we were already able to find people around you that you weren’t already connected to – and had an interesting amount in common with – without them having to use the app to be found. This was hard to grok for users – as well as journalists. And to be honest, I did a thoroughly shitty job of explaining it. I only much later learned that this is an actual concept called “forced liquidity” in a two-sided marketplace. At least we mastered that one without actually knowing what we were doing.

We actually ended up building most of this stack. And yeah, yeah, yeah – in hindsight, we should and could have done more and cleverer customer development before building most of it.  However, in our defense of building our own stack instead of using off-the-shelves cloud services in the validation phase, bear in mind that parse.com and similar platforms did not exist when we started out. It wasn’t really an option back then.  You take what you have at hand, what you know and you roll with it.

For the more technically inclined, the tech stack consisted of Python, Werkzeug, Gevent, ØMQ, Mongo db, Neo4j, Rexter, Objective C (native iOS app), Django (prototype/MVP + testing and debugging interface in production) HTML5 + JavaScript (the non-iOS-app users app part), Zepto, AWS S3 (MongoDB dump storage), Rackspace Cloud (which ran the back-end for free for one year thanks to Scoble) and for experimental future-proofing purposes I think we were starting to tinker with OrientDB and Titan.

Side-note

At the time, I had been deeply influenced by Tom Hanks’s Clay Shirky‘s account of Scott Heiferman’s approach to building meetup.com  in “Here Comes Everybody”. The key to the success of the social service was to give the product just enough features and to make it generic enough to enable users or customers to “discover” who they are and how they want to use your product for you on their own instead of building it and marketing it to spec for any one target group from day one.

Somewhere in the middle of it, I also became obsessed with how to actually and practically not having to build stuff in the early stages after discovering Cindy Alvarez.

Later, I became aware through Nicholas Nassim Taleb that there is a word for this (and a whole lot of interesting thinking around the subject):  optionality. Since reading his book “Antifragile” I have become seriously obsessed with “affording optionality” and how to build an anti-fragile startup.

Verticals, Markets & Customer Segments

So who could have this sort of problem set? Who is already trying to get jobs done that fall within this space? Who has the need or desire to meet up and connect with “strangers” around them? Who would be interested to the point of paying – and for what? And are there enough of them to scale this thing into interesting proportions?

Thinking hard about it – yes, and actually getting out in the field talking with people already looking to meet new people at conferences and meet-ups true Customer Development style – there were some signals about verticals that kept repeating.

And they related to (in no particular order):

  • CRM  (Sales / Marketing / PR)
  • Dating
  • Recruitment & HR
  • Conferences & Attendees

Sales Organizations and PR / Marketing Folks

markets2.001

I still vividly remember the words of the Co-Founder and President of a very well-known company telling me she was already stalking existing and potential new customers at SxSW 2012. It was a story I’d heard several times in Europe already (and a story that seems to still be repeating in 2014). And it’s a problem I know myself from my salary-man days.

I think you’ll agree that a significant number of business people are already investing a lot of time preparing for who to meet and adding background as to why at conferences, events and business trips. And I think you’ll also agree that even today most of us leave for home from business trips thinking that we didn’t get to talk to all the people we had planned, didn’t get all the leads we’d envisioned, feeling that we missed out on opportunities, that we didn’t get the most out of it.

What if all of this could be elegantly automated? What if even more business intelligence, more relevance could be mined and delivered – realtime, on-site, in context?

Side-note

Tackling this vertical or problem set today, I don’t see how facial recognition and a Google Glass-like component would not be one of the critical elements of the solution. Discussions of privacy aside, that cat is out of the bag and not going back. Augmenting human memory and knowledge is going to happen, freaky or not, wether you like it or not. Like William Gibson said, “The future is already here — it’s just not very evenly distributed.”.

There are scientific indications that we as humans are hardwired to or only capable of remember a finite number of people.

Read “Virtual Light” from 1993 and start dealing with it today. If you’re not convinced, consider why the world’s largest social graph bought Oculus.

Glass(es)-first will be the new mobile-first. Mark my words.

People Seeking Romance and  The Carnal Carnival

markets2.002

Ah, yes – the glaringly obvious and everlasting market. I fondly remember a famous VC telling me at LeWeb 2011 to call him for a cheque as soon as we switch to dating. And there was even an unsolicited call from the founder of Plenty of Fish (PoF) to that point. There was an actual line of investors queuing up for us to pursue this vertical.

But I didn’t found Gauss to join the online dating market. It was never a consideration. It’s just not something I’m passionate about. It wouldn’t get me out of bed each godawful morning.  And I’ve never even understood online dating and I’m not about to start pretending I have any unique insight or experience to bring to that table.

Contrary to Johnny Rotten and geek stereotype, I know what I want and I know how to get it – so I wouldn’t even be solving my own problem – and I sure as hell wasn’t keen on entering these heavily shark infested waters for a quick buck (yes, Badoo – I’m looking at you).

And I’m still not impressed with the market size of online dating. The numbers just don’t seem right to me. But it’s the figure that is still being used as reference – to the best of my knowledge.

These days, it seems Tinder et al has solved online / mobile dating so I couldn’t possibly care less about this vertical as a founder today.

Recruitment & HR

markets2.003

Another problem I still remember vividly from my own hire & fire salary-man days is how freaky broken recruitment still is. Most of the time you outsource it to some recruiter that most of the time gets paid whatever happens and most of the time never deliver any relevant and qualified talent to your doorstep. And when they bring you someone, you’re still left doing the interview face-to-face, either yourself or by in-house HR proxy. So you seek out events and conferences yourself to meet with and recruit talent in person, bypassing the costs and time it takes to apply the proxy of a recruitment agency.

And I know a lot of other SMB owners and executives who are doing their own recruiting, either in addition to employing a recruitment agency or completely replacing it, seeking out events and conferences to visit to put themselves in front of potential new employees. And it’s crazy time intensive and still mostly hit and miss. I know I would have thrown money at anyone who would have improved the process for me back when.

In further conversations with recruiters and recruitment agencies, I also found they have somewhat the same problem. They too go to events and  conferences to put themselves in front of prime talent, of top candidates before the competition get to them or before they sign with someone else. They’d easily pay for each new qualified leads and they are already paying hefty conversion/finder’s fees, often at the rate of 10% of the base salary before taxes.

Both professional recruiters and decision makers tasked with recruiting needs better tools to make their jobs easier and would pay you a lot of money if you can deliver improvements.

And there be serious gold in them there dinosaur mountains; It’s a huge stale industry overly ripe for disruption. And in this post-industrial age, recruitment is just going to be harder.

Conferences & Attendees

markets2.004

Recruiters and sales and marketing/pr people go to great lengths in both distance traveled, money and time spent to meet new people attending events and conferences. And they are far from alone. In this digital age conferences are still a formidable market consisting of all sorts of people. Both for business and for private interests. Meeting people face to face is still something we prefer for a variety of reasons, and chiefly biologically – it’s just how we’re wired.

And chances are that you yourself have probably been to more than one conference that you left feeling you hadn’t seen the people you were intending to meet and that you feel that there were opportunities you missed out on, that you didn’t get as much out of it as you had hoped.

It’s still hit and miss. Still a lot of random chance. And there’s still no single app that makes your conference experience 10x better even in 2016.

However, knowing the conference business intimately (previous customers please look away at this point – you’re all beautiful rainbow unicorns) I wouldn’t bet my future on a business model where the organizers are paying for my party. Their business model consist of squeezing everybody else for money – so I’d be fuck out of luck of getting a single cent.

And being a fan of automation and scalability and knowing how b2b software is sold, I’m not too hot  on white label solutions requiring adaptations and manual work for each and every conference nor the long, sad and predictable sales and support process it would require to actually to get, keep and grow the customers to collect the money – if any.

I think there should be potential here, but it is still not obvious to me how to massively tap or disrupt this market.

Side-note

For good or bad, FOMO is a real phenomenon. And as far as I am concerned, we’re not living in a knowledge economy but a network economy, a relationship economy. You and your worth are the sum of who you know, how many you know, how many types of people you know and how well you maintain those relationships.

I have been telling everybody who’ll listen for the last year or so to make a Tinder clone for B2B with LinkedIn and SalesForce using Apple’s Multipeer Connectivity Framework – and you’ll be golden. Seriously fuck-you-money golden. Some have since tried, none has yet truly succeeded.

Potential Revenue Streams & Business Models

Let’s take a look at some fairly typical revenue streams and business models that could apply to this hypothesis as a mobile app and cloud backend play. I’ll run you through them one by one on a theoretical level, complete with examples, just as a theoretical exercise for reference to any young impressionable minds aspiring founders googling for posterity. Just humor me, because back in 2011 things were not as clear as they may seem today.

  1. Paid app
    Or commerce as we used to know it before the Internet
  2. In-app advertising
    Or profiting from the power of large numbers, conversely annoying users for scraps
  3. In-app purchases
    Or additional Value-adds for one-time payment installments
  4. In-app subscriptions
    Or automagically recurring revenue FTW
  5. Commercial partnerships
    Or new targeted eyeballs for brands (AKA lose focus and traction while trying)
  6. Commercial API license
    Or selling your users user generated data
  7. Position yourself in the headlights
    Or be a nuisance or compliment relevant enough to get acquired by one of the big four (or #5)
  8. A combination of any of the above
    Or obvious is obvious

1. Paid app

This one is as straight forward as it gets: Pay to download my app. No pay, no play.

The general consensus seem to be that you have to have a free app on them app stores to enable mass-market adoption. And it seems the most successful model du jour is the “freemium” one where the app is free but value-adds are purchasable in the app. If you are going for b2b or niches and special interest groups, a paid app approach could also make sense, as your app would never have mass-market appeal anyway and the groups you are targeting feel the need or pain enough to spend money on solving it with your product.

However, much cleverer people than me recommend going for revenue first, growth later.  There is something compelling to be said for charging your very early adopters as a filter to repel the people who are not really feeling the problem you are trying to solve, to get insights from the people who really care – not just a bunch of noise from people who are just checking out the latest free thing and doesn’t know or feel the problem you are trying to solve.

The general advice seems to be to focus on revenue if you’re doing b2b and focus on user growth if you’re a b2c. The advice I have given myself for the future is to focus on b2b as that’s where the bulk of my experience is buried.

Check out Paul Graham‘s and Fred Wilson‘s respective seminal posts on metrics for further reference on growth and engagement metrics.

Side-note

Framing Gauss as a free b2c play from the start was probably not the smartest thing I’ve done. Starting over I would do experiments to find anything that would bring potential revenue on day one – and perhaps more importantly ask the market to vote with their wallet if the product is worth paying for, especially if it would be a b2b product. As a mass-market consumer based product, I’d probably be more hesitant with charging for the app – but then again, you can always go free later. The argument about early stage filtering with a pay gate still remains valid for b2c – that you’ll only get the first users who are experiencing the problem at a level to which they are ready to pay you for solving it – instead of having every early adopter and their friends storming in and only giving you noise as feedback (since they are not the people who’ll be paying for your product anyway).

2. In-app advertising

Make your app free and more people will download it, the theory goes. And one way to offset the free price tag is to add advertising networks to your app. In-app advertising would be an easy way to generate some revenue (or at least force you to constantly think about it and measure it) from day one. You could also play the freemium game and offer an ad-free version for a fee.

However, if your ambition is to make fuck-you-money, in-app advertising is only going to be interesting if you have a gazillion users and even then it’s probably not at a fuck-you-money level. And getting there could take some time – and money – if at all. In the meantime you risk annoying a lot of users for pennies and scraps – and potentially wasting a lot of time managing the ad relations instead of attention to customer and product.

This revenue source is super-simple: Have enough users, provide enough eyeballs to advertisers and they’ll pay you some money.  Oh, and good luck with finding your engine of growth and a sustainable engine of growth at that. If you’re paying to acquire users to grow and the users that come in don’t leave you enough value over time to keep sustaining your costs (reaching a CAC vs LTV of 1 to equal or higher than 3) you’re going to run out of money and fold. It’s like pissing your pants in winter, as the Norwegian saying goes: At first you’re warm. Then it freezes. Then you’re dead.

Over time – and if you are successful – you could start replacing the ad networks with your own advertising products and opportunities once you’d have the number of users, the leverage to cut out the middleman in favor of your own compelling placement products.

In the summer of 2013, I was showing some young hopeful entrepreneurs the usefulness of business model generation using my thoughts about my own business as  examples. Below is a rough first draft of what the business model would look like using the Business Model Canvas as drawn on the wall of the old blackbox mansion in Atherton, Silicon Valley.

photo-3

Example B2C Business Model, Advertising Revenue

3. In-app purchases

Offering a free app with either purchasable value-adding features or tiered subscription plans available within is also what is often referred to as the “freemium” model. The general thinking behind it is that it is easier to make you download and test a free app – and once you’ve downloaded and tested it, it’s easier to up-sell and cross-sell you from there.

In-app purchases should also be well known to anyone who’s ever played a “free” game on their phone or upgraded to a “pro” version of an app. They usually come in the form of unlocking or enabling certain features for pay, for a transaction. In many “freemium” apps it can be as simple as paying to remove the ads. Some purchases are one-off and some you have to keep purchasing if you want to be using them again.

You’ve also probably encountered the “in-app currency” model by now, where you earn or buy an app-internal currency to spend on value adds. In-app currency usually deplete itself in some way or form. It’s a clever and blunt way to force scarcity to keep you coming back to use the app to earn more currency or to generate more revenue by users skipping the earning mechanics by buying currency directly instead.

Combining a free app with in-app purchases and a in-app currency or subscription model attached to some of the in-app purchases seems to be a highly compelling way to drive users in and up-selling them all the way to automatically recurring revenue.

heatmaps

An example of a Gauss in-app purchase: Heat Maps

As an example of in-app purchasable features in Gauss – The People Magnet, say you pay one time to unlock a heat map feature in the app. It will provide a realtime heat map over the area I’m in or searching for with the ability to overlay different properties like showing where the startup entrepreneurs who also loves sailing (one of my more lofty goals in life are to actually sail over the Atlantic, but that’s a different story – apply within, crew 50% complete) are right now – and pay some more to also access the historical data of where that overlapping crowd usually hang out.

Now let’s switch to a B2B perspective. Wouldn’t it be very interesting to marketers, retail, brands, agencies, constructors, planners and realtors to have access to this kind of data – to the point of paying a pretty penny for it?

Let’s say that unlocking the heat map feature  gets you two interests to overlay and correlate. Want more? Pay to unlock more. Even more? Pay again. Oh, and you want these data overlays to work in realtime and in the background, when your phone is in your pocket and notify you when you’re entering interesting territories too instead of only when you open the app? There’s a subscription service for that. See below.

4. In-app subscriptions

Think of it as SaaS for apps. Think Salesforce, Zendesk or Google for Enterprise for B2B or Netflix, Spotify, Dropbox or Evernote for B2C. The general idea here is to provide running services at a fixed monthly/yearly fee, often offered in tiered plans, that is automatically recurring until canceled – and that only at the termination conditions stipulated in the contract.

This is easily my favorite revenue source. It’s automatically recurring revenue until explicitly cancelled – what’s not to love about it? And all the while they are your paying customer, you have a direct channel, a direct relationship where you can cross-sell and up-sell them. Actually, there are a number of concerns like e.g. you have to have a more advanced solution with an actual problem-solution fit for anyone to actually pay like this, you’ll have a lower conversion rate vs free or one-time fees, the expectations and obligations towards your level of service and support, QoS and security is going to be that much higher – but I find those manageable and fair trade-offs. It’s also the model I have the most experience with professionally.

And of course, paying subscribing customers is a great base to build off of, leveraging tiered plans (A fancy way of saying that you offer different price plans at different costs for different needs. You might know as free, bronze, silver, gold or personal, small business, enterprise plans) to up-sell from the starting plan and to provide value-adds, either as an up-sell to a higher tier or cross-selling  additional products or services

Using the example from above, you could unlock additional features like  heat maps by an in-app purchase and then purchase an additional in-app subscription directly related to that feature, say to enable the data overlays to work in realtime and in the background when your phone is in your pocket, notifying you when you’re entering interesting territories instead of only at-a-glance when you open the app or to enable tracking over time, enabling an animated interactive timeline broken down in time of day, days, weeks, months, seasons and years.

For say recruitment or sales verticals, you could imagine professionals having to unlock certain people search features as in-app purchases and paying for an additional tiered subscription plan to enable their multitudes of real-time searches for candidates or leads to run in the background, complete with notifications and reporting as in-app subscriptions.

You could also envision a variation on the in-app subscription where the tiered plans consist of a combination of feature-unlocks and amount of monthly in-app currency allowances. The customer would then use the in-app currency to pay for running services, to unlock features and value-adds and perhaps to pay or transfer to other users for say conversion fees.

Side-note

Back when we were starting out, Apple was quite antsy about reserving the subscription option for publications and old media offering their content in their own Newsstand app. These days it seems to be a more viable option for a wider variety of iOS apps. And bear in mind that Apple wants 30% of this recurring revenue too. So if you want to circumvent the Apple tax, look to how e.g. Audible and Spotify circumvent this by not referring to nor offering their subscription service in the iOS app.

For further reference about SaaS dashboards and cohort analysis, it is imperative that you read and follow Christoph Janz and David Skok.

5. Commercial partnerships

During our days as a contender, I was approached by a number of global brands (or rather their agencies in some shape or form) for commercial partnerships. And I now wholeheartedly agree with Guy Kawasaki‘s straight forward advice about partnerships for early stage startups; “It’s BULLSHIT!” to be avoided. At this early stage, what leverage do you think you are going to have in this relationship? ZERO, that’s what. They are just placing a put on you at this point just in case you become successful in the future.

At this stage you are still searching for your business model and you risk stagnating and putting that search on hold when you become a vehicle or a “put” of sorts for someone else’s business model and agendas, chasing yourself down the wrong rabbit hole. Run for the hills if approached – It’s just too much of a hassle and effort to manage the partnership sideshow that will probably go nowhere slowly.

Thank them for their interest and tell them you’ll get back to them when you have more value to offer. Then ignore them until there is a real alignment that will directly benefit your goals. Optionally, ask them for an outrageously large sum of money and only proceed if they pay (and start to find more like them).

photo-2

Multi-Segmented Business Model, Commercial Partnerships

However, here’s an illustration about how I thought about how it could work, providing incentives for social interactions with tie-ins to commercial partners. In this case, using a Starbucks offer pushed to you based on your proximity, based on your affinity or affiliation to the brand and based on people similar to you that frequent this particular establishment near you.

Think of it as a sort of commercial flash-mob / flash-sale feature. It could be used to unlock special deals if you’d be able to bring enough people. It could also be used to offer free samples (and awareness of) of new products or deals.

Another example would be to provide discounts or special offers like 2-for-1 just-in-time with enough context and incentive to stimulate actual interaction, actual meet-ups at the point of sales, over say a cup of coffee, say when two or more people who know each other are nearby a Starbucks and both like Starbucks.

Screen Shot 2013-05-28 at 04.21.15

Left below, another way of thinking about commercial partnerships would be to help shape traffic, either to the point of sales like a coffee shop in the example above but also to help you shape your experiences by recommending locations just-in-time as you enter their proximity based on the kind of people you’d like to meet and mingle with. It could give you insights in real-time towards the locations around you that are frequented by your kind of people, both for business and for private interests.

There could also be a revenue potential in offering the locations the insights about their clientele and the potential to monetize conversions from a notification to an actual visit to the location, say a retail shop or a bar – and to actually be able to influence the kind of people you’d like to be alerted via notifications and who not.

Right below, it could also be used to help exhibitors and conference organizers lead traffic to points of interest, hyper-locally like to a booth at a trade show floor. E.g. by driving groups of similar people to the respective boots and talks of interests where the exhibitors or related brands would pay for the privilege.

You could also imagine a value potential for exhibitors being able to identify interested parties and use that information to their advantage when they later appear at the booth and there could also be value in the ability to create spontaneous group “bird-of-a-feather” chats or presentations based on actual demand whereas there was previously no available channel to identify the demand and communicate the supply ad-hoc.

traffic

Left, drive traffic based on relevance to a location. Right, drive and direct conference floor traffic.

6. Commercial API licenses

Now let’s forget for a moment that this one rests on a Tower of Babel’s worth of untested assumptions and let’s imagine for a second that we have a gazillion users and imagine we are now able to aggregate an astronomical amount of data about you across all kinds of different social graphs, like graphs, affiliations graphs, trust graphs and your whereabouts at any given time of the day at any given time of the year.

aggregation

Wouldn’t it be interesting to be able to tap into that firehose of huge data in real time for your own commercial purposes – something akin to that of twitter’s realtime api? Twitter’s customers certainly thinks (or thought?) so. And wouldn’t this would be potentially exponentially more interesting since it would contain an aggregate of all kinds of datasets? And wouldn’t the other services hate it? Certainly, but what’s from stopping it once a user has allowed us access to their data and we continue to do no evil and only acting on their users demand?

Now consider us releasing a personal API where you would be free to use your own aggregated data in any which way you chose. And consider enabling you to allow other services to use this data in new and interesting ways.

I seems to be a highly interesting avenue to be exploring somewhere, albeit perhaps a long way, down the road and I think in one shape or form, it’s an inevitable future.

Screen Shot 2014-02-13 at 04.22.07

Hypothesis: Graph analysis of large aggregate data will enable identifying bridging social capital

One of the things that I was highly motivated to explore after reading Putnam’s “Bowling Alone” and Christakis‘ “Connected” was using graph analysis of large aggregate data to enable identifying previously hidden potential bridging social capital across multiple networks and patterns – to identify the influential people on the edges of your network that you are not already connected with. The kind of people that would enable you a bridge to new clusters or networks of people, opinions, power, position, skills, interests. The hypothesis being, the more people like these you know, the more opportunity (or optionality) you will have in life.

And also take a moment to think about the potential for marketers and other strategic planners to be able to identify previously hidden chief influencers and target them or their network. Think about also being able to identify bridging interests or affiliations –  and you’d be able to identify new crossovers that could actually work (as opposed to horribly fail) not unlike coming up with new food receipts.

Cue tinfoil hats & profit!

7. Position yourself in the headlights of The Big Four

Some people will tell you to position yourself for acquisition from day one. I, however, subscribe to the get-get-the-fuck-out-of-here school of thinking on this particular point with regards to early stage startups. Just forget it. You shouldn’t be thinking about exit partners at the discovery stage. Unless you have an insanely unique insight and a huge bunch of luck it will not work. And what will keep one of the big four from just doing it themselves once they see you’re doing something successfully?

Transactional Models

A-B Business Model

A Direct A-B Transactional Model

So how do we actually provide value in the recruitment space for fun and profit in new and interestingly productive ways?

Let’s tell the story of Lucy who’s a professional recruiter. She’s already traveling to exclusive events and conferences to get in front of new potential clients and more importantly, to get a personal facetime moment with high potential recruits. In addition to the known meetings and the leads she’s already planning to pursue, she uses the Gauss app to discover, approach and get facetime with high-potential recruits.

In the app, she can enter simple search criteria for candidates or she can develop elaborate profiles as a in-app feature to unlock. Either way, the searches will run in real-time around her person wherever she goes. Depending on the amount, complexity or the duration of her searches, she might be subscribed to one of the tiered price plans to have them running in continuously running in real-time.

Now let’s break it down in single steps.

Legend: A = Recruiter, B = Target lead, $ = money (in the form of in-app currency or credits)

  • A is looking for lead with the criteria B and is ready to pay $ when Gauss can find it.
  • A pays Gauss for a subscription, account tops up with monthly credits ($).
  • Optionally, A doesn’t first pay Gauss for a subscription, can enter search criteria, service will run for 30 days or perhaps better yet forcing A to buy a subscription when a lead is found.
  • Gauss finds a sales lead with the criteria B and presents it in an anonymized form to A.
  • $ is deducted from A’s account.
  • Gauss gets a % commission.
  • A likes what she sees. Tells Gauss she wants to know who it is.
  • Optionally, if B is a Gauss user, he is notified if he wants to allow it, reminding of what’s in it for him if he does.
  • Gauss gets another % commission on the value-add.
  • Thus B is revealed to A.
  • In the case of finding a recruitment lead, an option to contact for meeting in real life, together with an explanation of why and what would be in it for them, e.g. an iPad, if they meet for 2 minutes with A.
  • If B is not a Gauss user, they get a LinkedIn or Facebook message with the value proposition.
  • If B is a Gauss user, he can agree and plan to meet A within the app.
  • Gauss validates that B actually met with A, that the lead converted.
  • Gauss gets another % commission.
  • Optionally, Gauss converts $ deposited into perk fulfillment or topping up in-app currency for B, if user.
  • A tops up $ with Gauss to be able to act on more future leads on a monthly subscription basis.
  • Optionally, A buys additional $ with Gauss to keep playing if the monthly amount allowed by their current tier plan has been depleted before end of the cycle, preferably automated like Skype credits securing never to run out of services accidentally.
  • Profit.

Imagine a weighted or tiered model where the first commission is small, the next medium and on conversion larger. And even if conversion into meeting up doesn’t occur, Gauss has already taken at least one or two rounds of commission.

Now this model doesn’t assume that both A and B are both using the app. As mentioned above, our somewhat proven assumption was that we’d be able to data mine and infer who’s where and what their social profiles look like without requiring both A and B to use the app for value to be delivered to A.

But now let’s do assume that both A and B are using the app. How do we get B to use it? One of the obvious ways to get people on the supply side to participate would be to reward them for participating. By letting them participate in a revenue share, receiving a cut when an actual interaction with A takes place and by rewarding them for playing by providing them additional visibility, additional channels to receive highly targeted, highly desirable job offers for free.

You could also imagine the rev share being paid back in in-app currency and that the in-app currency could be accrued and be converted into prizes or gifts in tiers, say an Amazon discount voucher, an iPad Mini or a weekend retreat.

You could also imagine in-app purchases and subscriptions available to B to use his in-app credits and real money on. For example, one in-app purchase would be the ability for Gauss to first ask if his identity should be revealed to A. Another would be to pay to be featured, to place and ad for yourself – anonymously – and get paid on conversion to revealed and again if an interaction takes place. A pro subscription could also be imagined, where you’d be able to see who the recruiters are before answering, the recruiters would be able to see your “pro” badge on your profile, get stats, a preferential ranking in search in swarm conditions and so on.

To assure fair play, a trust or credibility rank based on app engagement patterns and mutual Uber-style evaluations would most likely be beneficial.

With regards to assuring a meet-up actually took place, we already had a simple yet pretty tamper-proof physical public-private key security scheme requiring a simple user interaction IRL correlated with passive data gathered on the back-end to identify and thwart potential fraud – which I’ll deliberately shroud in some secrecy to reserve optionality towards future patent(s) and competitive advantage.

In addition, you could imagine providing the recruitment industry with a commercial API license for fun & profit. Heck, even throw in 1-800 telephone support at an on-shore call center if needed and if and when scale is reached.

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A Potential B2B Business Model for the Recruitment Vertical

CRM

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B2B Business Model, CRM / Sales Vertical

The Man-in-the-Middle or A Leveraged Introduction Variation

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Intermediary / Leverage or Man-in-the-Middle Transactional Model

Now let’s explore a couple of variations to a direct A-B transactional model and mix it up a little. In a network economy, it’s only fair and square that we get to use our own networks to help do our biddings – to leverage our best connections, right?

Disregarding the direct motivation that you’d have in wanting to get introduced to – and getting some facetime with – a person that you don’t know for the sake of the argument since I believe we’d agree that between recruitment, sales, marketing and dating there’s a large demand, a huge amount of people engaged in trying to get this type of job done already.

So how do we go from an unknown to getting the attention or even a meeting with our person of desire?

One old trick that seems to work is to get an introduction from a person that you both know. And as the theory goes, the more of a peer to your person of interest, the more respect they command with your object of desire, the more likely it is that the introduction is going to be acknowledged and convert into something meaningful for you.

So how can we create value by automating this process for fun and profit?

Say you’re at SxSW in Austin, TX and you’re just dying to meet Robert Scoble to pitch him your new startup. You don’t know Scoble and you’re not connected directly anywhere. And even if you were, chances are that you wouldn’t get a reply as an unknown as people like Scoble is already drowning in noise from strangers and can’t possibly reply to everyone, always.

But you do know Dave McClure that you’ve met and pitched several times around the world. And Scoble sure knows Dave, which you can verify by looking in the app at the connections available to you that you and Scoble share.

So let’s ask Dave to ask Scoble to give us 5 minutes of his time to listen to our pitch. We can see in the app that we are all three within short walking distance from the Hilton. So you offer Dave a treat (e.g a perk, IOU., return favor, cash or in-app currency promise) if he’ll do it.

Basically, you deposit a bribe with Gauss as escrow to have someone reach out to your target on your behalf and facilitate an introduction.

The example assumes that you are a Gauss user. Dave and Scoble don’t have to be users. They will be notified on the common denominating communication channel found and transactions and compensations will also be available to non-Gauss users through a web app component (although there’s also an argument for forcing at least Dave to use the app to receive his bribe compensation and compelling Scoble to use the app for more convenience).

  • As in the recruitment example, Gauss takes a commission on your bribe placement.
  • If Dave accepts and actually does introduce you to Scoble, Dave gets paid half of the bribe in escrow.
  • And Gauss takes another commission.
  • If Scoble actually responds, Dave gets paid the other half of the bribe held in escrow.
  • And Gauss takes yet another commission.
  • Optionally, Gauss pays 50% to Dave, 50% to Scoble on conversion

For you, it would be a new way of directly leveraging your network for new connections.

For Dave, it would be a new way of facilitating his network for fun, profit & karma.

For Scoble, it would be a new convenient way of dealing with inbound opportunities (or deal flow) as they are peer filtered and presented with full context of who they are and what they want for fun, profit & karma.

Obviously, the guys in the example aren’t the best examples of the target group but serve as colorful placeholders. And obviously the whole model is also completely disregarding pay-it-forward Karma – to the point of flying directly into its face. But bear with me as we explore another variation to restore faith in a relationship economy.

And there’s no need to become an esoteric to take Karma in this context seriously.  If you ask Dan Ariely, professor of psychology and behavioral economics at Duke, there’s scientific merit to be highly skeptical of mixing social capital with financial capital. Because once mixed, the relationship will forever revert to financial capital. In other words, it will forever change relationships – for the worse.

So how do we potentially avoid some of the downside of mixing social capital with financial capital? One would be to offer gifts or return favors definable by the person who’s asking his direct connection to give an introduction. But that one doesn’t seem like a fun business case for the app mediator, aka Gauss.

Another would be to defer actual monetary payment to a third party of your desired target’s choice on conversion. For a small transactional commission, of course.

In the above example, Scoble’s (or optionally Dave’s in lieu of Robert not being a Gauss user) favorite cause would receive the monetary bribe (sans a small commission fee to Gauss, optionally growing by each step) as a donation is his name on conversion.

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Intermediary, Deferred Transactional Model

As we’re starting to get seriously into frivolous speculation territory, let’s not hold back and imagine there would also be a whole range of alternative ways to convert and interact, complete with their own price differentiations depending on mode of contact and complete with surge and automatic pricing based on availability, in-app rank and quality scores.

Instead of just offering a physical meet-up as the goal, you’d also offer a phone call, a video conference, an email or message or smoke signals. Basically anything – complete with their own prices. e.g. An in real life meeting would be much more worth than a phone call or an email.

You could also imagine utilizing your social graph to crowd source and auction off your contacts to the highest (or optionally the lowest, depending on the type of auction game and side you’d want to play) bidders.

For the supply side, it would be a new way of making money on things they are already doing for free, and perhaps more interestingly making money on things they are currently not doing because it wouldn’t be otherwise worth their time to take a cold call.

You could imagine unlocking different contact modes as in-app purchases, the whole system running on virtual in-app currency bought as in-app subscriptions and Gauss would of course take a small fee on each conversion additionally.

Will this work? Most likely not as humans are not rational econs.

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Frivolous fun: Discover who’s around and leverage your connections to get introduced – and leave it to free market dynamics to figure out how and at which cost

One more thing

BMC

This could work

One of the most interesting utilities for a location based service that I still haven’t seen successfully executed is as a B2B service for people who work in the field and need to get advice or help from other field colleagues or HQ. These markets include craftspeople, security, utilities, maintenance, IT services, facilities managers, quality control and so on.

If I would build a Minimum Viable Product (MVP) of such a concept, it would only do one thing: Identify other people of my company or organization near me and the ability to message them and maybe even send them a picture or video.

Later, a number of value adding features that could be added. Like Apple’s Multipeer Connectivity Framework for creating local networks among peers in situations with no connectivity (e.g. underground, inside facilities) reaching all the way to Internet connectivity by hopping from peer to peer. One could also easily imagine an “ask HQ” feature that could be connected to a web panel where HQ could access questions and even connect to their knowledge management systems and logistics systems – all for an added fee.

To onboard users, I would enable signup / registration with only a confirmed email address. On confirmation, I would ask the newly signed up user to invite colleagues (as to make the service valuable for them) using their work email addresses. When enough people with the same domain has joined, say 5 people, I could ask for an upgrade subscription to the bronze plan on trying to add the 6th person and so on.

This way, at least in theory, I would afford optionality in discovering which markets and industries, which niches, who would need my product the most (by looking at the domains registering), a group of users motivated by the problems the app solves and thus great to run experiments on to learn which features to build next, and I would have the potential for a viral engine of growth where users are much better off the more people join and will have enough motivation to invite their colleagues.

This MVP could also be made almost completely without a backend today. I’d let the app do most of the work. You could have a super-simple registration process only consisting of a Mailchimp mailing list where you’d manually pick out the emails with the same domains and manually adding them to a super simple database or lookup table for peer group definitions, that is to say defining which user should see and be able to message which user.

Do you want to build it with me? ;)

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