A while ago I was listening to Kevin Systrom talk about how Instagram started on How I Built This, and I was struck by his assessment of what caused them to succeed. They weren’t the first to build a social network around photos, to do it on phones, nor to popularize filters. But their timing was still perfect — they launched when phone cameras started to catch up to the quality of point-and-click cameras, the exact moment that users started wanting to both easily enhance and show off their phone photography.
To his credit, Systrom doesn’t pretend that this was a calculated move — if anything he makes it sound like a complete fluke. But it did get me thinking: is is it possible to do intentionally? Where could you look for these perfectly-timed, just-about-to-take-off ideas?
Catching the Wave
An important distinction to make is that when I talk about perfect timing, I don’t mean being first. As humans we have a tendency to overvalue being first, and the startup world is no different. Startups tend to care so much about being first to market that they burn themselves out in order to do so, even going so far as to eschew marketing in order to stay in “stealth mode”. However, if you put your biases aside, the correlation between being first and success is pretty far from clear.
Think of a bunch of successful technology companies, and ask yourself whether they were the first into their market? Facebook certainly wasn’t. Apple didn’t make the first home computer, mp3 player, smartphone or tablet — they waited, picked their moment and dominated once they entered. It’s certainly not hard to think of products that were first to market, but either way ahead of their time or quickly pushed out of the way by competition — the Visicalcs, the Virtual Boys, the Altavistas.
Starting first is not the same as winning… and particularly in technology, vying to be the first into a market means overhyped expectations and VC-funded competition.
If you tried to catch a wave at the beach by swimming out as far as you could go and immediately paddling as soon as you saw one, you’d end up having a pathetic, slow moving mound of water pass under you just as exhaustion set in. The right way is to place yourself just behind where the waves are breaking, pick one that looks good, wait until exactly the right moment to start paddling, match its speed and let it propel you forward.
That’s what we’re trying to do here. We’ve just got to figure out how to look at markets as easily as we can look at waves.
The Hype Cycle
While I was pondering how you make a market look like a wave, I remembered the technology hype cycle… which pretty much looks exactly like one.
The hype cycle is a model that tracks the rise, fall and slow recovery that describes the life of many promising new technologies. It happens something like this:
- A technology starts as obscure research… until eventually it starts to look like maybe there might be something in it.
- As awareness increases, so does hype, and expectations rise far past any reasonable expectation.
- The hype around the technology reaches a fever pitch — your tech-illiterate relatives are asking you to explain it to them and you’re sick of hearing about it.
- Cracks appear: predictions don’t pan out, high-profile failures start happening, and bad press starts popping up
- Expectations fall until they hit rock bottom. The once-burgeoning startup ecosystem around the technology is littered with incredible journeys, press coverage about it is rare outside of The Onion, and conversations regarding it are inevitably prefixed with “hey, whatever happened to…”
- Freed from the suffocation of high expectations, the technology slowly starts to show its true value, sometimes in a different application than initially expected.
- Having climbed the slope, the technology stabilizes and continues to be useful in the long-term.
Putting Your Snout in the Trough
In my tortured wave-at-the-beach metaphor, the big peak at the left is the pathetic mound of water that we don’t want to catch. The hottest new technologies are cool to talk about at meetups, but they tend to result in a large number of startups fighting over a poorly understood market with a small pool of actual value.
Where we want to be is the middle of the graph, in the trough of disillusionment just before it starts rising again. At this point in the cycle most competitors within a space have died out and investors aren’t too excited about funding new ones, but those who’ve gone and failed before have left a nicely beaten path of open-source tooling, best practices and lessons learned — perfect for a bootstrapped technical founder to get started.
Naturally this means you’re trying to succeed where a lot of other people have failed, which doesn’t seem too wise. However, keep in mind that that startups working with bleeding edge technology tend to favor applying it in ways that might make a world-changing impact, but with a tiny chance of success. If you’re happy with merely making a comfortable profit, there are applications with much better chances of succeeding.
Here are a couple of suggestions for places to look:
Technologies attract hype when it’s easy for Techcrunch to tell you how your everyday life is going to change — machine learning will mean you never drive a car again, blockchain will replace every contract you’ve ever signed, etc. Mass-market applications like this are also where the biggest potential for massive returns are, which attracts venture capital, and that tends to shape how a technology is used.
If a technology might also enable a 7% efficiency gain in some boring industry sector, it doesn’t get clicks on articles nor 10x returns for VC firms, but it can still be the basis for a solid profit.
A classic example is beacons — little low-powered devices that can be used to very accurately determine location within a building. When Apple launched them in 2013, the dominant use case was marketing — tracking users around stores and sending them targeted offers based on their behavior.
It didn’t work. 60% of people don’t even have Bluetooth turned on, and the remaining 40% weren’t that eager to download a new app for every store just to give up their privacy and be bothered by push notifications. As the excitement cooled around beacons’ use in retail, one great yawner of a good use case emerged: asset tracking, the dull-but-vital corporate art of figuring out where your stuff is when you need it. At the height of the hype in 2014 this was a use case you “might not expect”, but by 2017, with the beacon industry struggling to find something that it was actually useful for, it was the next big thing.
Using beacons for asset tracking is the most straightforward value proposition you could ever hope for. If a nurse spends 13% of their time looking for equipment, and gets paid $67,930 per year, then someone who’s built a system to find that equipment can justify charging up to $8830 per nurse per year. Get a hospital with 120 nurses on board and you’ve got yourself a 1000k ARR business.
Instead, the beacon industry spent three years sending coupons to customers who’d already come to the store.
Most people in the West already live incredibly convenient, technology-optimized lives in which they’re marketed to constantly. If a technology is novel enough to find any gap in this incredibly saturated market, there’s probably ten better uses hiding just out of sight in the doldrums of the B2B marketplace, and a lot of solid business plans hiding in those niches.
Have Some Fun With It
When a technology is ascending the hype cycle, amidst all shouting about how it’s going to change everything it’s easy to miss applications that are nothing more than amusing — but “amusing” still has value, especially if you’re not chasing unicorn-level returns.
In 2013 Google released the beta of Google Glass with an amazing concept video of how Augmented Reality would meaningfully enhance our lives by guiding us through public transit, making calendar entries from posters, letting us share what we were seeing with our friends and a bunch of other features that caught the imagination but no one actually needed. By 2015 it had been withdrawn for a redesign, and the word “Glasshole” had been coined to describe its early adopters and their always-on cameras.
AR’s true value turned out to be in applications that didn’t pretend to have any hope of changing our lives or the world, but were just fun. Snapchat’s lenses launched late in 2015 and have become the defining feature of the app and a viral phenomenon. In July 2016, Pokemon Go’s launch proved so popular that it created crowds big enough to draw complaints.
Sure, Silicon Valley made fun of it, and Snapchat and Pokemon aren’t the AR-assisted future that everyone dreamed of back in 2013, but just being amusing is still worth $268 million, and its shows you how an industry obsessed with making the world a better place can miss tech’s more fun applications… which might just leave a gap open for you.
What You Can Do Today
All of this is a bit pointless without me putting my money where my mouth is — here’s a few slightly passé technologies that I think still have a lot of life left in them.
The hype of a few years ago around chatbots has mostly faded now, perhaps because most companies went for the mass-market application and built robotic Customer Service Representatives that ended up with broken, uncanny valley AI. I think if you take a step back and realize that a chatbot doesn’t have to pass the Turing Test, there’s loads of potential left in the concept.
For instance, at a hackathon I went to recently an alcohol addiction charity built a chatbot for people who want to talk, but not to a real person — a context in which the artificiality of the chatbot works as an advantage. Unicef uses a chatbot to quickly conduct polls and gather data about what’s affecting developing nations, where the simple, text-driven interface works suits poor connections and old hardware. The chatbot interface is also easier for people less familiar with computers to grasp, so it’s used to remind older people about their medications.
These are simple but high-minded examples — there’s got to be some dull but lucrative use cases in the enterprise world. A great thing about building chatbots is that the concept’s been around long enough that there are some really great, easy to use tools out available — I saw the alcohol addiction chatbot above go from nothing to functional prototype within a single afternoon.
The Internet of Things
A lot of hyped technologies become the butt of jokes after a while, but few are quite so ridiculed as the Internet of Things — the internetofshit twitter account has gained nearly 300k followers with a neverending stream of poorly conceived and implemented products, and the Juicero saga has been the focal point of IoT’s sullied reputation.
IoT is a classic example of a technology with massive potential being applied to a narrow band of poorly-suited uses, and subsequently going from a hot trend to a punchline. Most attempts to turn mass-market objects into IoT devices — fridges, lightbulbs, especially juicers - don’t really add any real value at all, and in some cases actually make the overall device work worse than a dumb one would.
So where is there real value? Anywhere that a business could benefit from real-time information about something in the physical world. Farms, roads, waterways, public transport, nursing homes… there’s barely any industry that couldn’t benefit from low-cost, real-time data collection. The IoT boom has meant there’s a wealth of cheap, off the shelf components and open source tooling available, and this means that you can cheaply assemble a system that not too long ago would’ve required multi-year projects and budgets worth millions of dollars.
The high end of some sectors is already catching on, but there must be a plethora of opportunities left over for a small-time entrepreneur to thrive. Hospitals have a system of procedures and technology in place to monitor patients, but maybe now you can have that at home. Wire four buttons to an Arduino with a cellular shield, place them in some gas stations, gather the data in a central place and you’ve got yourself a multinational business. Precision agriculture was once the dream of big agribusiness, but it could be the domain of family farms if someone could set these systems up for them.
Catch that wave!
Admittedly not every technology fits the hype cycle model — AI is in the middle of its third historical climb, for instance, having failed to really catch on at all after either of its previous two declines.
The essential lesson of the hype cycle, however, isn’t that all technologies follow exactly the same path. The lesson is that you’re more likely to see success if you wait for a technology to mature and apply it to a problem where it shows real value than if you jump on board as soon as you can and chase the widest application you can think of. If anything, this rings even truer for an exception like AI… if you’d launched into the market with an AI company every time the hype started, you’d simply have failed twice before, and probably be about to do so for the third time.
So have a think… there’s a plethora of less-than-world-changing problems that could be solved by passé technologies, and solid, profitable businesses around many of them — they’re just waiting for you to found them!