Featured Article

From surviving to thriving as a hardware startup

Six strategies from Minut CEO Nils Mattisson

Comment

Young woman standing on top of tall green bar graph against white background
Image Credits: Klaus Vedfelt (opens in a new window) / Getty Images

Nils Mattisson

Contributor

Formerly at Apple, Nils Mattisson is now CEO and co-founder of smart home tech company Minut.

More posts from Nils Mattisson

When a friend forwarded this tweet from Paul Graham, it hit close to home:

Startups are subject to something like infant mortality: before they’re established, one thing going wrong can kill the company. Hardware companies seem to be subject to infant mortality their whole lives.
I think the reason is that the evolution of the product is so discontinuous. The company has to keep shipping, and customers to keep buying, new products. Which in practice is like relaunching the company each time.
I don’t know if there is an answer to this, but if there were a way for hardware companies to evolve more the way software companies do, they’d be a lot more resilient.

Looking back on our startup journey at Minut, I remember several moments when we could have died. However, surviving several near misses we learned to tackle these challenges and have become more resilient over time. While there will never be one fully exhaustive answer, here are some of the lessons we learned over the years:

Subscription revenue is the only revenue that counts

While you can sell hardware with a margin and make important early revenue, it’s not a sustainable business model for a company that requires both software and hardware. You can’t cover an indefinite commitment with a finite amount of money.

Many hardware companies don’t consider subscriptions early enough. While it can be hard to command a subscription from the start (if you can, you might have waited too long to launch), it needs to be in the plan from the beginning. Look for markets where paying subscriptions is the norm rather than markets that operate on a one-time sale model.

Set high margins and earn them over time

It’s tempting to set low prices for hardware to attract customers, but in the beginning you should do the opposite. Margins allow for mistakes to be rectified. A missed deadline might mean you have to opt for freight by air rather than boat. You might have to scrap components or buy them expensively in a supply crunch. Surprises are seldom positive, and you don’t want to use your venture capital to pay for them.

Healthy margins can also be used to cover marketing costs while you learn what kind of messaging works and what channels you can sell through. If that wasn’t enough reason, starting with relatively high prices will help you avoid another common mistake, selling too much at launch.

This might seem counterintuitive — why wouldn’t you want great success out of the gate? The reason is that you will inevitably make mistakes with your early launches, and the bigger the launch, the bigger the blow. There are plenty of companies who achieved amazing crowdfunding success and then failed to deliver even the first units. Startups tend to chase growth at all costs, but for hardware startups in the first few years there is such a thing as too much of a good thing.

Choose your customers wisely

Customers with long decision cycles or many stakeholders are bad initial targets for hardware startups. Start at the lower end, with smaller businesses or even consumers. You can move upstream or sideways later.

Each iteration toward product-market fit requires feedback from customers. You can get fast feedback from fake ads, landing pages and interviews, but no feedback is more valuable than that coming from someone paying money for your product and relying on it daily. That’s why you need to pick a target customer that can make fast decisions so you can get to market quickly.

Having customers capable of making fast decisions counteracts the inevitably slower speed of developing hardware. After all, what really matters is not just how quickly you can release new features, but how fast you can complete a full cycle of customer feedback and product iteration.

Avoid the launch trap

Airbnb famously launched seven times. If no one notices the first few times, why not try again? For a software startup it can seem like a no-brainer, but for hardware startups each launch is a potential trap. The revenue generated by a crowdfunding campaign or pre-launch of a shiny new product can be addictive, but it forces you to deliver on promises even if the result isn’t what you hoped for.

Worse still, since it’s easier to sell new features to existing customers via crowdfunding than winning customers in the regular market, you can become reliant on selling hit after hit to crowdfunding enthusiasts. Learnings from this group don’t transfer well to the broader market. Minut fell in this trap.

Instead, iterate on the core functionality of the product in order to reach the customers you didn’t convince the first time. Focus on the real pain and not the feature requests. Your product should ideally never go through a revolutionary change — much like the iPhone gets better each year but never startlingly so.

The road to recurring revenue for hardware startups

Decouple the customer experience from the hardware

Your product is not the hardware it requires to run. While hardware iterations take time, you can iterate on customer experience just as fast as software startups do. The whole system will have higher complexity, but you can architect it so that each part can be improved independently. Treat interfaces as if they were external (one day they might be) and make hardware versatile enough that it can support multiple product iterations.

At Minut, our hardware platform is versatile enough that it’s being used as a home alarm, a sensor for office management, in elderly care and (of course) with Airbnb in hospitality. Versatility, platform thinking and flexibility are imperative on the journey to product-market fit. There is plenty of time to focus narrowly once you’ve found it.

Innovate on the product, not in the supply chain

When you hear hardware startup founders talk about close encounters with bankruptcy, their stories frequently involve the supply chain. While most startup decisions are reversible and bear modest consequences, almost every supply chain decision can be fatal. Whether it’s choosing a supplier that turns out to promise a bit too much, or a fancy new chipset that didn’t really live up to the data sheet, you can lose a lot of time and money if you’re not paying attention.

The good news is that you don’t need to outperform. Winning at supply chain for startups simply means not losing, and best practices are well known, so pay attention and stick to them. Don’t be tempted to shave off a few dollars by using unknown components. Pick suppliers that are the right match for you. Test every feature of every unit in manufacturing and never ever try to rush to production without a proper process.

When running a business, you need to focus on making a few bets that have substantial upside with relatively low downside risk. Innovation in supply chain management usually gives you the inverse: limited upside with serious risk at every turn.

In short, Paul Graham is right — there’s a staggering amount of ways a hardware startup can die. Fortunately, the most common mistakes are well-known and if you learn about them from others, there are also numerous ways to avoid the pitfalls.

If you’re a hardware startup founder and want to connect, please reach out at nils@minut.com!

Who’s building the grocery store of the future?

 

More TechCrunch

Blue Origin’s New Shepard rocket will take a crew to suborbital space for the first time in nearly two years later this month, the company announced on Tuesday.  The NS-25…

Blue Origin to resume crewed New Shepard launches on May 19

This will enable developers to use the on-device model to power their own AI features.

Google is building its Gemini Nano AI model into Chrome on the desktop

It ran 110 minutes, but Google managed to reference AI a whopping 121 times during Google I/O 2024 (by its own count). CEO Sundar Pichai referenced the figure to wrap…

Google mentioned ‘AI’ 120+ times during its I/O keynote

Firebase Genkit is an open source framework that enables developers to quickly build AI into new and existing applications.

Google launches Firebase Genkit, a new open source framework for building AI-powered apps

In the coming months, Google says it will open up the Gemini Nano model to more developers.

Patreon and Grammarly are already experimenting with Gemini Nano, says Google

As part of the update, Reddit also launched a dedicated AMA tab within the web post composer.

Reddit introduces new tools for ‘Ask Me Anything,’ its Q&A feature

Here are quick hits of the biggest news from the keynote as they are announced.

Google I/O 2024: Here’s everything Google just announced

LearnLM is already powering features across Google products, including in YouTube, Google’s Gemini apps, Google Search and Google Classroom.

LearnLM is Google’s new family of AI models for education

The official launch comes almost a year after YouTube began experimenting with AI-generated quizzes on its mobile app. 

Google is bringing AI-generated quizzes to academic videos on YouTube

Around 550 employees across autonomous vehicle company Motional have been laid off, according to information taken from WARN notice filings and sources at the company.  Earlier this week, TechCrunch reported…

Motional cut about 550 employees, around 40%, in recent restructuring, sources say

The keynote kicks off at 10 a.m. PT on Tuesday and will offer glimpses into the latest versions of Android, Wear OS and Android TV.

Google I/O 2024: Watch all of the AI, Android reveals

Google Play has a new discovery feature for apps, new ways to acquire users, updates to Play Points, and other enhancements to developer-facing tools.

Google Play preps a new full-screen app discovery feature and adds more developer tools

Soon, Android users will be able to drag and drop AI-generated images directly into their Gmail, Google Messages and other apps.

Gemini on Android becomes more capable and works with Gmail, Messages, YouTube and more

Veo can capture different visual and cinematic styles, including shots of landscapes and timelapses, and make edits and adjustments to already-generated footage.

Google Veo, a serious swing at AI-generated video, debuts at Google I/O 2024

In addition to the body of the emails themselves, the feature will also be able to analyze attachments, like PDFs.

Gemini comes to Gmail to summarize, draft emails, and more

The summaries are created based on Gemini’s analysis of insights from Google Maps’ community of more than 300 million contributors.

Google is bringing Gemini capabilities to Google Maps Platform

Google says that over 100,000 developers already tried the service.

Project IDX, Google’s next-gen IDE, is now in open beta

The system effectively listens for “conversation patterns commonly associated with scams” in-real time. 

Google will use Gemini to detect scams during calls

The standard Gemma models were only available in 2 billion and 7 billion parameter versions, making this quite a step up.

Google announces Gemma 2, a 27B-parameter version of its open model, launching in June

This is a great example of a company using generative AI to open its software to more users.

Google TalkBack will use Gemini to describe images for blind people

Google’s Circle to Search feature will now be able to solve more complex problems across psychics and math word problems. 

Circle to Search is now a better homework helper

People can now search using a video they upload combined with a text query to get an AI overview of the answers they need.

Google experiments with using video to search, thanks to Gemini AI

A search results page based on generative AI as its ranking mechanism will have wide-reaching consequences for online publishers.

Google will soon start using GenAI to organize some search results pages

Google has built a custom Gemini model for search to combine real-time information, Google’s ranking, long context and multimodal features.

Google is adding more AI to its search results

At its Google I/O developer conference, Google on Tuesday announced the next generation of its Tensor Processing Units (TPU) AI chips.

Google’s next-gen TPUs promise a 4.7x performance boost

Google is upgrading Gemini, its AI-powered chatbot, with features aimed at making the experience more ambient and contextually useful.

Google’s Gemini updates: How Project Astra is powering some of I/O’s big reveals

Veo can generate few-seconds-long 1080p video clips given a text prompt.

Google’s image-generating AI gets an upgrade

At Google I/O, Google announced upgrades to Gemini 1.5 Pro, including a bigger context window. .

Google’s generative AI can now analyze hours of video

The AI upgrade will make finding the right content more intuitive and less of a manual search process.

Google Photos introduces an AI search feature, Ask Photos

Apple released new data about anti-fraud measures related to its operation of the iOS App Store on Tuesday morning, trumpeting a claim that it stopped over $7 billion in “potentially…

Apple touts stopping $1.8B in App Store fraud last year in latest pitch to developers