Last 5-Qtr of Growth: -10% > 13% > 11% > now 13%.
Guide implies 28% QoQ
3/3: Full Year Revenue:
o FY 2022 Revenue of $886M, implies 46% YoY. If they beat around 5%, if you come to 51% YoY for Full Year. This is down from 81% in the last fiscal year.
Seasonally, they have a strong Q3 to Q4.
Overall, they seem to have do "ok" but growth is slowing.
4/4: ARR: $PATH wants us to focus on ARR.
+ My expectation was 3Q ARR of 57%. They beat slightly, hit 818M ARR which was 58% YoY.
This was 3.2% beat and QoQ of 13%.
+ Q4 2022 ARR Guide was $903M, >55% (Met). but down from:
- FY 2020 OF 109%
- FY 21 which was 66%.
Not good.
5/5: Net New ARR was the bright side!
+ $92M Net new ARR accelerated to 42% this Q3. This is up from 33% in Q2!
It sequential grew from 14% > 11% and now, 25%.
There must have been a huge deal they won... Hope they discuss it on the CC.
6/6: Bottom-line operating margins look good!
+ Gross margins decelerated to 80%
+ SBC declined from 100% > 47% > now, 43%
+ FCF margins around -3% (similar to last Qtr -2%)
+ N-GAAP Losses: -4%
7/ They announced new partnerships with $SNOW, $CRWD, $AYC. and big channel partnership with $PWC. Most seem like fluff.
$PATH's partner ecosystem has always been their strongest strength but unfortunately, its not yet showing in the numbers the way I want.
8/ $PATH is a leader within their industry
I highlighted in my tweet last month. Across all the leading market researchers, $PATH is still the leader. However, $MSFT Low-Code/NC CEO (Chris Lamana) taking share. See @AznWeng:
I added well into my $ZS Scaler position today. Couple of reasons below:
+ Leader within the fastest-growing segments of enterprise security. (ZTA, SASE, ZIA)
+ Clearly differentiated, cloud-native moat
+ 71% billings growth and 62% YoY on $1B ARR on 30% FCF
Short thread (1/4)
2/2: Brief overview of last earnings:
+ They've CAGR over 50%+ growth over the past 5-years.
+QoQ accel to 17%
+ They could easily CAGR 60%+ growth into 2022 due to new Govt contracts
+ 87% in >$1million customers
+ RPO grew 97%
+ FCF✅
+ Obsessed with computers from a young age
+ He graduated from MIT with a Computer science degree
+ Worked for Mckinsey in Europe
+ Came back to New York to work for Tiger Global for 3+ yrs until 1999 when Tiger returned capital.
The internet has not broken yet.
Some quick thoughts 1/
2/ My priority is to focus on companies that can sustain 30-40% growth rates for a 3-5yr.
The market is looking for companies that have growth PLUS (optionality, product-lock-in, switching costs, mission-critical) to deduce the durability of a 3-yr CAGR to decide its multiple.
3/ Other things is looking for 30%+ CAGR Rev growth combined with lock-in, high land & expand DBNRR?
Alternatively, for non-SaaS companies. I'm looking for companies that are still relatively early in capturing their TAM and are showing qualities that they are market leaders?
Let's begin w/ positives:
• Current Q3, 70% YoY growth
• 50k Customer growth was 132% (highest since 2020)
• 5k & 50k Customers are sticky, spending more: DBNRR of 130% and 145% respectively to last Qtr
Where were the negatives? 1/6
2/ Reason the stock is down:
• Revenue of 70% YoY, slight deceleration
• Q4 Guide: 54% YoY, 5% sequential slowdown from 12% QoQ from Q1-Q2
• FY Guide: 64%, light
• FCF: -29% & high S&M/Operating exps remaining the same
+ This is unacceptable when yu trade for EV/S of 60+ :(
3/ $ASAN: It turns out this indicator in my thread came true.
Enterprise customers were more likely to Decrease their spending on $ASAN over the next couple of months which is why $ASAN likely had a slow guide.
This is a phenomenal breakdown of today's Enterprise AI/ML stack (S/O: @BatteryVentures).
I'm constructive on the tailwinds within this space and I'm long: $CFLT, $CRWD, $AMPL, $PLTR.
The report below is a great read for any AI & Enterprise SaaS Enthusiast.
Thread Summary: 1/
2/ Today's Org has a fragmented data and AI environment. Here are the different job roles required to perform certain data tasks.
For example, 1) the ETL process is going to undergo some innovation. 2) More people will become data citizens IMO.
The visual below shows it.
3/ The Data Value Chain:
The picture below explains -
i) the lifecycle of machine learning in an organization,
ii) the different applications required, and
iii) how data flows through the modern organization.