The “Full-Stack Startup” and Jiro’s Dreams of Sushi
Edit: I wrote a follow-up to this post called “Should you build a full-stack startup? 7 factors for consider”
Five years ago, Chris Dixon coined the “Full-Stack Startup” to describe the new wave of companies like Uber looking to upend entire industries through building a new, vertically-integrated stack.
The basic idea is this. Traditionally, as startup founders we see ourselves as toolmakers because we build software and that’s what software is best suited for. If we thought the experience of hailing taxis were broken, we’d build a better taxi dispatch software and sell that to taxi companies. Software can solve the dispatch problem elegantly because it’s relatively close-ended. Running a taxi company, on the other hand, seemed extremely under-leveraged in terms of technology and a terrible business.
However, Uber not only built dispatch software but also hired drivers to offer rides, allowing them to control the entire production function and eat the taxi industry altogether. That’s a much more expansive role for software, but a truly exciting one because the experiences are much more magical when it works.
Since then, venture capital has poured into all kinds of full-stack startups. Opendoor, Compass, WeWork, Shift, Triplebyte, Gigster, Pilot, Honor, Forward, Atrium, just to name few. At the same time, we’ve seen spectacular failures like Homejoy, Sprig, Munchery, Luxe, HomeHero, and to a lesser extent, Zenefits and Altschool. What explains the differences in outcome?
I think the two most important questions to ask are 1) how variable are the customers expectations and 2) to what extent can software help deliver on those expectations.
A lesson from Jiro
Jiro Ono is a three-Michelin sushi chef in Japan and the subject of the documentary, Jiro Dreams of Sushi. At 85, Jiro has mastered every facet of his craft. From knowing the perfect length of time to massage an octopus (40 minutes) to developing a technique to preserve sushi rice at its optimal temperature (body temperature) to only serving each ingredient at “its ideal moment of deliciousness,” Jiro has explored, refined and practiced every painstaking detail to perfection. In a way, Jiro has done to sushi-making what software has done to many human tasks — eliminated variability and refined the quality of the output.
However, here’s the kicker. Three-Michelin Sukiyabashi Jiro has only 4 out of 5 stars after 71 reviews on Yelp. The problem? Even though Jiro has the best sushi-making software, he’s in the full-stack restaurant business where software does not provide enough leverage in providing a consistently positive customer experience.
First, Jiro’s customers come with a wide variety of expectations beyond great sushi. Some expect a certain level of service for the price while others care more about comfort and ambience. Some may even be looking for the meaning of life in Jiro’s sushi. Obviously, Jiro promises none of these things, but customers expect them nonetheless.
Second, even if Jiro has the most refined process for making sushi, customers are eating the sushi, not the process, and sushi tastes are highly subjective[1]. So in a way, Jiro’s software failed to deliver against even the singular goal of great sushi.
Traditional startups sell sushi-making software. Full-stack startups operate restaurants. Operating a full-stack startup, you live and die by your ability to manage your customer’s expectations while consistently delivering against the expectations leveraging software. Sounds basic but anyone in the service industry would tell you that it’s hard to execute on let alone having to do it at scale.
The bane of variable customer expectations and why services offer “Free Consultation”
When I built Crowdbooster, a social marketing software-as-a-service startup, we would often talk about “landing pages” because our customers knew roughly what they wanted and the landing pages together with a free trial were mostly sufficient in helping them figure out if Crowdbooster was right for them.
My second startup, Upbeat, was a full-stack, tech-enabled public relations agency. Our product was not something you used, but a service to help you garner media coverage. Our customers did not know how public relations worked nor did they care to. All they knew was that they desired media coverage, and they paid us to help achieve that outcome. However, even when we delivered great media coverage, some of our customers were still dissatisfied.
The problem is that full-stack customers don’t really know what they want beyond the fact that they have a problem, and when the outcome is delivered, that’s when they begin to realize what they were looking for. This is why consultants have offered “free consultation” for ages — it’s the service industry equivalent of a free trial. The free consultation is an opportunity to explore the nature of the customers’ problem, educate them on what to look for, and set expectations on what they can and cannot expect from an engagement. Many full-stack startups like Honor, Atrium, and Pilot take this approach and force you to talk with an expert agent during the sign-up process.
However, a free consultation, like any human conversation, is a lossy process at best. To avoid dealing with the fickleness of humans, you can instead choose a more bounded problem by constraining the customer segment to only customers you know you can deliver for (as long as it doesn’t constrain your market long-term). This is the like running a fast food chain as opposed to Jiro’s restaurant. For example, OpenDoor targets only customers who want to sell their home fast (and fit their many other criteria). If the customer is not in a rush or they prefer to be serviced by a real estate agent for the experience or to feel like they got the best price, then they are not for OpenDoor.
How much leverage can you get from software?
Assuming you figured out how to manage your customers’ expectations and filter for the right segment, full-stack startups still have to consistently deliver a great customer experience with a production function that they don’t fully control. Uber, for example, went as far as calling human drivers their existential dependency and the final barrier to a perfectly-controlled customer experience. This is despite having built one of the most successful marketplaces in the history of startups. Traditional marketplace tactics like user ratings, apps to manage workers, offering different levels of service to different customer segments, insurance, etc. will eventually be insufficient for Uber because when you sell the outcome of a ride, any problems caused by drivers along the way is your fault, so you’d want to ultimately subsume that variable.
For a better framework on how to properly leverage software to tackle full-stack opportunities, I’d send you to Andrew Chen’s brilliant essay, “What’s next for marketplace startups? Reinventing the $10 trillion service economy, that’s what.” Notice in his essay that as we move fuller-stack, the leverage you gain from software begin to diminish. This is something to watch out for and you can use the strategies in his essay to mitigate.
As Arthur C. Clarke once said, “any sufficiently advanced technology is indistinguishable from magic.” To me, full-stack startups are the ultimate magical feat, especially when you can appreciate the complexity of their production functions. As software continues to “eat the world,” full-stack startups will become more of the norm. I’d love to see more discussion from operators about how full-stack startups can better improve their odds of success. Let’s continue the discussion in the comments below or with me on Twitter @rickyyean.
[1] The documentary probably did more to align customer expectations and their subject taste to Jiro’s favor than anything else he’s done.
