The Big Picture
Data points and market trends
Why has there been no European VSaaS IPO yet?
Alexandre and Louis shared an excellent map and analysis of more than 450 European vertical SaaS companies. There are plenty of data points and interesting insights, so I definitely recommend reading the whole post.
🚧 What struck me is that, fifteen years into the VSaaS trend, I couldn't think of a single significant European VSaaS IPO.
As a reference, the VSaaS public index created by Fractal Software contains 18 public VSaaS companies, with 15 of them coming from the US and three from Canada (Constellation Software, Lightspeed POS, and Shopify).
I know that the EU market usually lags behind the US, but in this case, I think it illustrates two additional aspects inherent to the VSaaS model:
1️⃣ It shows that the EU is a fragmented market that makes it harder for VSaaS to scale. Since many Vertical SaaS companies are more “local” by definition, they often need to deal with the cultural specificities of each European country, which makes geo expansion hard. US-based VSaaS companies benefit from a much bigger market from day one.
2️⃣ It highlights how almost impossible it is for European VSaaS companies to target the US market. In comparison, most of the horizontal European SaaS companies that have IPOed (like Criteo or Talend in France) were first started in Europe and then later moved to the US, where most of their revenue comes from. This is not a playbook that VSaaS can adopt.
Will we see European VSaaS IPOs in the future? I’m pretty positive that it will happen. Given the constraints I just mentioned, it will take longer, but several of the unicorn VSaaS companies Alex and Louis listed will likely go public at some point.
Article of the week
Research and thoughts
The end of the collaborative SaaS era
2010 - 2022: The Collaborative SaaS era
If you were lucky like me to witness the rise of SaaS products in 2008 - 2015, you’ll probably remember how “collaboration” was at the heart of many new SaaS products (and how we were excited by it).
With the on-premise model, real time collaboration between users was much harder than with the SaaS model that brought B2B software in our web browsers.
Suddenly it became possible for software vendors to build features that enabled employees to collaborate in real time. And collaborative features were all the rage.
With real-time editing multiple users could edit documents, spreadsheets, presentations, and other files simultaneously with changes instantly visible to all collaborators. Thanks to commenting and annotation features users could leave comments, feedback, and suggestions directly on documents or projects. Version control and history tracking gave the ability for employees to track changes, view version history, and revert to previous versions. Notifications and alerts enabled people to see in real time new comments, edits, task updates, and other activities. etc.
This is why we ended up with collaborative SaaS in almost all software categories: From developer tools to HR software or marketing platforms many of them have user collaboration at their core.
2023: Is the pendulum swinging back?
What I find fascinating with the recent AI-native SaaS wave is how most of these products are not collaborative software products but rather “single player” type of software.
If you look at most AI-native SaaS, their strength is that they “kill collaboration” and the need to wait for another human action.
Instead of asking your colleagues to review your documents it’s an AI that can do it now. Instead of brainstorming with colleagues for new blog post ideas or for what visual to create for your ad, it’s an AI that will give you suggestions. Instead of asking (and waiting) your data analyst colleague for data or your developer colleague for code review, it’s an AI assistant that will do it.
Even designer tools can now recommend design ideas and improvements directly to designers. Another key feature of recent AI powered SaaS is their ability to summarize user activity: You don’t even need to read all the comments that your colleagues leave on Slack. An AI will surface the most important ones and give you a summary of the others. And same for your emails.
It seems that SaaS products are becoming less “collaborative” than before, but is it a bad thing?
Too much collaboration kills collaboration?
Another way to think about it is that maybe too much collaboration in SaaS products was a bug and not a feature. When you get too many notifications or are asked to edit and comment on too many documents, it just becomes noise. As almost all SaaS products offered such features there’s probably a collaboration fatigue that developed among people.
And instead of “killing” collaboration, maybe what AI will enable is to go toward less but higher quality collaboration. Instead of too much noise, thanks to AI we will be able to collaborate with our colleagues on important things and with more depth than before.
The 2020 decade: A new product zeitgeist
What I believe is that the B2B software zeitgeist is changing. I think that you can no longer be successful by adopting the same approach as before, with the same "user collaboration 1.0" features I listed above.
AI automation and assistants are probably the new zeitgeist, and a telling sign of this shift is that most of the platforms that dominated the "collaborative SaaS era" are now creating features that specifically reduce the need for human collaboration in their products. From GitHub with its Copilot to Slack with its AI-powered features to summarize and automate user interactions, we’re going toward “lower volume collaboration” products.
Business Breakdown of the Week
Interesting startups and products
What is Metris?
Metris is an AI-first SaaS platform that enables commercial real estate companies to discover the solar energy potential of their properties. Users simply upload their real estate portfolio, and the AI assesses each property's solar potential and assists with the installation process.
What I find interesting:
Metris illustrates well the “AI-powered opportunity discovery” model I discussed in my list of AI product archetypes. Here applied to solar energy.
The radical improvement brought by AI is to enable commercial real estate companies to quickly identify revenue opportunities through solar installations—a task traditionally requiring consultants and extensive manual labor.
They combine the discovery engine with a project management tool (to simplify the solar installation process) as well as features to automate energy contract management and billing. Great features to create recurring usage beyond the initial discovery phase.