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What's 🔥 in Enterprise IT/VC #233
TAM matters but nail your product first and own it - most investors underestimate the size and growth of new markets
So why do some enterprise companies seem to raise significant 💰💰💰 again and again in a matter of months while others don’t? Yes, founders and team matters along with product and early momentum. However as each round goes by and the price continues to go 📈, it comes down to TAM or total addressable market. How big is the market you are going after and if you win that with a superior product, what is the ultimate opportunity.
Let’s look at Crowdstrike which initially went after the competitive endpoint security market first, a massive market in and of itself, and now since going public has added new products and expanded its TAM by 4x since its IPO. It’s no surprise that Crowdstrike is worth over $48 Billion today.
That being said, Crowdstrike went after an existing market that was already huge with a 10x better product. How should founders and investors think of new emerging market opportunities and how does TAM matter then?
In the chase for mega round funding (not a goal that should be pursued), I often see founders trying to expand their product line too quickly without owning and dominating their initial market first. This creates incredible stress on the organization from product to sales (learning how to sell, the motion, bundling), to the executive team. So a huge TAM is wonderful but time your product expansion carefully. Like Scale AI which just raised at a $7.3 billion valuation this week. From their blog:
At Scale, we’re building the foundation to enable organizations to manage the entire AI lifecycle. Whether they have an AI team in-house or need a fully managed models-as-a-service approach, we partner with our customers to build their strategy from the ground up and ensure they have the infrastructure in place to systematically deliver highly-performant models.
We set out to solve this problem by starting with an essential building block, data annotation. Building on our expertise in delivering high-quality training data to world-leading machine learning teams, we are now applying our technical expertise and understanding to close the loop on the ML development lifecycle.
"Data is so fundamental and critical to the building of these systems, the training, the testing," Wang continues. "Companies need to be able to utilize and manipulate data just as they have utilized and manipulated code in the past."
Scale has moved from just labeling data to a suite of software-based services. Its offerings help companies to gather, annotate, curate and clean-up their data as well as to build and monitor machine learning models trained on that data.
What Scale got right is the insertion point into a data science/engineer’s workflow - you can’t create and run models without annotating and having clean, labeled data.
With that insertion point at the earliest point of ML, they built a huge and loyal user base and only now, 5 years later, are expanding to cover the whole ML development lifecycle expanding its product line and its TAM by an order of magnitude. It’s no surprise that the company more than doubled its valuation since its Series D raise in 4 months ago.
So founders the moral of the story is TAM matters, but nail your first product first before expanding too quickly.
As always, 🙏🏼 for reading and please share with your friends and colleagues!
❤️ this - pivoted, stuck through hard times, and now worth $325M
My only comment on Coinbase, I promise 🤣 - yes, not an enterprise co but valuable lessons for all founders - stay the course, believe in yourself, find other true believers on day one, build from there
👇🏼Must read for founders
🧵 on some of best Jeff Bezos quotes as he steps down from CEO of Amazon this week"Anybody who doesn’t change their mind a lot is dramatically underestimating the complexity of the world we live in.” — Jeff Bezos In the thread below, you’ll find my favorite lessons from Amazon.With Jeff Bezos stepping down as CEO, here’s a thread of the best things I’ve learned from him. 1. Be willing to change your mind. As Bezos famously said: "Anybody who doesn’t change their mind a lot is dramatically underestimating the complexity of the world we live in.”David Perell @david_perell
Design is so important and amongst the first 5 hires in many an enterprise startup and Scott nails the difference between good and great…
One of best 🧵 on how venture firms operate and how Tiger is disrupting “traditional VC” - great for founders to read to understand mechanics, dynamics of some widely held beliefs which are being challenged."Playing Different Games, or why Tiger is eating your lunch" randle.substack.com/p/playing-diff… Feels like Tiger has been top-of-mind for everyone these last few months -- this is my attempt at an explanation for what's been going on, and why I'm very bullish on Tiger Global
RSA Innovation Sandbox has launched many an amazing security company - congrats to the 10 finalists and especially Cape Privacy (😃 a portfolio co) - excited to see cloud-based encrypted learning get it’s proper attention
Great read from Dharmesh at Battery (sorry ExtraCrunch) on Billion-dollar B2B - there you have it, massive TAMs again, combined with PLG/bottoms up models
Ecosystems matter as the Top SaaS Companies Have An Average of ~350 Integrations (Jason Lemkin/SaaStr)
👇🏼💯 yep!Coinbase, Airbnb Shopify, GitHub all initially built on Rails, two of them on Heroku Others like them: Groupon, ask.fm, Zendesk, Urban Dictionary (a fascinating story in itself given the traffic it does) all Rails & some HerokuCoinbase started as a @rubyonrails app hosted on @heroku. Developer productivity was the focus early on. Focus on functionality first, grow organically, scale as needed. https://t.co/ZsqUuyDLiaⒿohannes Ⓕahrenkrug @jfahrenkrug
Umm, glad developer experience getting attention: “Developer experience is the next major competitive front in enterprise tech (Protocol)” - IMO, it already is and so much more room for innovation moving forward, helping developers become more productive from onboarding to testing to not waiting for DevOps….
The 4 Definitions of Multicloud from Armon Dadgar Hashicorp - covering data, workflow, workload, traffic portability with this article diving deep into data
Customer ❤️ from Nuance which Microsoft is buying for almost $20 billion
The game-changing product is the Nuance Dragon Ambient eXperience, or DAX, which was released in February 2020. While prior offerings forced doctors to use devices to transcribe notes and then spend hours at the end of the day to file paperwork, DAX takes the administrative burden off their plate. During each visit, the system records voice conversations between doctors and patients, then leverages AI to find the proper context for the discussions and automatically creates detailed clinical documentation for review. All the doctor has to do is sign off. At least for physicians, it seems as if the AI-powered panacea is now here.
Hospitals love it. They get happier doctors, who can see more patients, and there’s a reduced risk of clinical mistakes. Citing a survey, Nuance notes the percentage of doctors feeling burnout and fatigue dropped to 17% from 72% with the use of DAX. Physicians say it also enables higher quality care because they can focus on treating patients instead of doing data entry. The excitement has reached investors. During Nuance’s most recent earnings call, nearly every question from Wall Street touched upon DAX’s prospects. While the use of DAX is still in the early stages, the financial future looks bright. Earlier this year, Nuance said revenue from DAX could rise to as much as $250 million by 2023 from an estimated $15 million or so this year, and it was seeing rising interest from current and new customers.
Sign of the times - cover of New York Magazine…time to run for the hills?