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1) Over the last few years, investors realized the potential of SaaS and bid up valuations accordingly. New IPOs debut at ever-increasing valuations and mkt caps
However, some companies like $FSLY, $LVGO, and even $DDOG have seen significant multiple expansion since IPO - why?
However, some companies like $FSLY, $LVGO, and even $DDOG have seen significant multiple expansion since IPO - why?
2) With many SaaS companies at or near all-time highs amid one of the sharpest economic contractions in history, near-term risk-reward prospects can seem a bit unfavorable.
It's safe to say that the days of buying a $SHOP <10 EV/S are forever in the past
It's safe to say that the days of buying a $SHOP <10 EV/S are forever in the past
3) While over the long run revenue growth drives a far bigger share of returns than multiple expansion, the latter can greatly influence short-term returns.
That being said, how can we find undervalued SaaS companies outside of market crashes?
I can think of four types:
That being said, how can we find undervalued SaaS companies outside of market crashes?
I can think of four types:
A) Underperforming businesses with poor prospects
These are the type of companies I avoid. Cheap is cheap for a reason, whether it be due to a loss of mkt share, poor and declining margins, bad mgmt etc. These are very competitive markets and a stumble can turn into a freefall
These are the type of companies I avoid. Cheap is cheap for a reason, whether it be due to a loss of mkt share, poor and declining margins, bad mgmt etc. These are very competitive markets and a stumble can turn into a freefall
B) Businesses transitioning to a SaaS model
When $ADBE transitioned Creative Suite to SaaS, its net income fell by 35% the next year, but 4 years after, their stock price had nearly tripled.
Other companies like Autodesk or Splunk have opted to run licensing models in parallel
When $ADBE transitioned Creative Suite to SaaS, its net income fell by 35% the next year, but 4 years after, their stock price had nearly tripled.
Other companies like Autodesk or Splunk have opted to run licensing models in parallel
This can turn out very well in the long run but comes with considerable challenges such as adapting your sales force making it important that the company was in a position of strength before.
With these risks in mind, I generally do not seek out these types of companies either
With these risks in mind, I generally do not seek out these types of companies either
C) Small / Microcaps
These can seem appealing because they oftentimes fly under-the-radar while having a lot of growth potential.
However, I generally avoid these as well as they generally have limited coverage and market presence, making it hard to evaluate their prospects
These can seem appealing because they oftentimes fly under-the-radar while having a lot of growth potential.
However, I generally avoid these as well as they generally have limited coverage and market presence, making it hard to evaluate their prospects
D) Misunderstood / Unique Companies
These are hard to find but can yield amazing returns. The search often starts by looking for high and/or accelerating revenue growth.
Eg. I felt that $LVGO, being categorized under medical devices, fell under-the-radar of many SaaS investors
These are hard to find but can yield amazing returns. The search often starts by looking for high and/or accelerating revenue growth.
Eg. I felt that $LVGO, being categorized under medical devices, fell under-the-radar of many SaaS investors
The amazing numbers got me interested, but I needed to do deep qualitative research to understand it.
When you look at an established market like endpoint security, it’s easy to gauge the TAM and forecast the CAGR, look at industry reports, and refer to experts to find winners
When you look at an established market like endpoint security, it’s easy to gauge the TAM and forecast the CAGR, look at industry reports, and refer to experts to find winners
When you have a totally new category like Applied Health Signals, especially one at the intersection of two industries, it becomes much harder to estimate its potential.
That levels the playing field somewhat and results in big gains as institutions get comfortable with it.
That levels the playing field somewhat and results in big gains as institutions get comfortable with it.
Opportunities to invest in nascent, high-potential markets like observability, edge computing, or digital health don’t come along all too often but can pay off big time if you do your research and hold for the thesis to play out.
Chart from @KoyfinCharts
Chart from @KoyfinCharts
