SNOW Q1 2024 Earnings

Wow, this was not exactly the Snowflake report I was hoping for. But not everything was bad, either.

Below are the notes that I found stood out most from this earnings report, with some fundamentals for context in the beginning.


  • Product revenue for the quarter was $590.1M, 50% YoY growth and 5.6% sequential growth. Q1 was better than expected and beat guidance by 3%. Sequentially, product revenue is decelerating significantly: 9.7% > 18.2% > 12.1% > 6.2% > 6.3%.
  • Q2 guidance calls for $625M, which (assuming no beat) would result in 5.9% QoQ.
  • While this looks okay for a consumption-based business, what really turned investors off is the revised full-year guidance - for the second time!
    • Initially, Snowflake guided for 47% YoY growth in fiscal 2024 (preliminary, so they didn’t have to do that).
    • Then they revised that down to 40% YoY, only to reduce it again to now 34% YoY.
    • The market hates that.
  • Net Retention Rate declined further from 158% to 151%, which is in line with especially large customers optimizing their SNOW bill and buying only as many credits as they need in the shorter term.
  • Customers:
    • SNOW added 43 large customers (> $1M), which is similar to the record added in Q4 2023). Strongest customer metric of those SOW reports.
    • Total customers: I dislike. SNOW needs total customers so that they can expand them into new large customers, but the total customer net add of 317 customers is at a low since about 3 years ago.
    • Forbes 2000 Global customer net added is also comparatively low, but this is a very lumpy metric.
  • Remaining performance obligations were $3.4B, 31% YoY, dropping to -6.8% sequentially. This doesn’t give any outperformance upside for the near-term (even if Q1 RPO is also seasonally low, but much more pronounced this Q).
  • Non-GAAP adjusted free cash flow was a record $287M, up 58% YoY, representing a record FCF margin of 46%.

CC Notes

Notes on Snowflake AI

  • SNOW has a data advantage since many models have been primarily trained with Internet and public data, but with SNOW, enterprises can benefit from customizing these models with their own data. Slootman called out a large US financial institution using SNOW data to train its model.
  • Data science, ML + AI use cases keep growing. In Q1, 1,500+ customers used SNOW for any one of these workloads, up 91% YoY.
  • SNOW acquired Applica last year. Its language model helps to understand unstructured data, so users can turn unstructured data (like documents, contracts, etc.) into structured properties and reference them for analytics, data science, and AI.
  • Acquisition of Neeva:
    • Why Neeva? —> Team is great + its tech can combine LLM + generative AI with traditional tech which is interesting to get more precise answers.
    • “This will enable Snowflake users and application developers to build rich, search-enabled and conversational experiences. We believe Neeva will increase our opportunity to allow non-technical users to extract value from their data.”
    • help us accelerate the efforts around Snowflake as a platform for search and conversational experiences, but most important within the security perimeter of Snowflake with the customers’ data so that they can leverage all this new innovation and technology, but with the safety on the privacy and security of the data.
  • “asking really hard analytical questions that take people weeks and weeks or even months to figure out, that will take some workforce software to do that in a matter of seconds to be productive that way. So, we’re sort of at the top of the hype cycle. The real work really starts now.”
  • Analyst: “Do you guys envision kind of building up GPU clusters and offering training and inference on your platform? → SNOW: “We’re doing all of it. We alluded in the prepared remarks to Applica, which it is a multi-model collection of models being built at Snowflake that requires GPUs.”

On Uncertainty

The market hates uncertainty, and on this Call, it got a lot of it (bolded is mine):

  • “This may well continue near term, but cycles like this eventually run their course. Our conviction in the long-term opportunity remains unchanged.”
  • “It is challenging to identify a single cause of the consumption slowdown between Easter and today.”
  • “[…] customers remain hesitant to sign large multi-year deals.”
  • “Contrary to last quarter, the majority of this underperformance is driven by older customers.
  • “As a result, we’re reining in costs until we see a consistent change in consumption.”
  • “[…] and that we don’t have real strong visibility in terms of, “Okay, when is it all going to be different?”
  • “This, in the past, is we literally saw four weeks in April where there was no week-over-week growth per se or not material.”

On Optimization & Usage

Snowflake is facing a multitude of different optimizations. On a positive note: some of these help its customers do more with less which is a customer-centric approach and should pay off in the long run.

Currently, they call out 3 optimization patterns:

  1. Optimizations by cloud vendors due to better hardware, result in better performance.
  2. SNOW’s own & regular optimizations improve performance and make things cheaper for customers. Optimization 1 +2 create an annual 5% headwind to revenue.
  3. A few of the largest customers change their storage retention policies —> SNOW loses storage revenue + queries run quicker which also is a headwind for revenue. Change in retention policy was also seen by one of the hyper scalers (I think it’s AWS). But, this should revert at some point since this lower data retention (earlier archiving) comes with a cost for customers.

Additional insights:

  • “[…] CFO being in the business and[…] So really artificially constraining the demand because of the general anxiety that exists in the economy. So that really needs to start lifting. And that will happen.”
  • Customers outside of financial services are the ones optimizing
  • Snow reiterated its 10B goal by 2029. From where is confidence? → “What I would say is we have a lot of customers. We have only moved a fraction of their data that we know they have multi-year plans to go on Snowflake, and that’s what gives us the confidence as well as the pipeline of deals. And I’m not just talking to pipeline now. There’s deals for next year that I know their long sales cycles, these big customers. That’s what gives us the pipeline on top of a lot of the new products we have coming out over the next couple of years.”
  • The number of queries is up 57% YoY in the quarter, outpacing revenue. Queries are running more efficiently.
  • Snowpark: SNOW went from 20% in “one quarter to 30% of our customers using it on at least a weekly basis. We think that’s going to go to 100%.”

  • Data sharing is an important metric for SNOW’s network effects and is measured via the customers having at least 1 stable edge. The number of customers using stable edges increased from 23% to 25% and grew 61% YoY. We don’t have that much historic data yet, but seasonally, Q1 and Q4 tend to be stronger than the rest of the year. Considering Q1 should be seasonally strong, stable edge growth is okay-ish, but decelerated from previous Q1 sequential growth numbers:
    • Q1 2024: 13.4% QoQ
    • Q1 2023: 18.4% QoQ
    • Q1 2022: 26.4% QoQ
  • Powered by Program: This allows customers to build their apps directly on top of Snowflake and reduces potential data redundancies. The numbers here look pretty solid: Power by Program customers grew 128% YoY and 18.1% sequentially. Here, we have even less historic data and it looks like it is also decelerating (probably also due to initially very high numbers when first reporting this metric), but it looks still relatively stable.
  • Finally, my personal lowlight of Data Cloud Metrics - Data Market Place listings. These grew only 3% QoQ, showing a significant slowdown. This was not addressed on the conference call, so I am a bit puzzled on why:
    • See here the QoQ slowdown starting at Q1 2022: 31.0% > 31.7% > 40.9% > 20.9% > 21.6% > 13.3% > 10.6% > 8% > now 3% QoQ.

On Competition

Is it “only” macro and law of large numbers? Or is it the competition?

  • SNOW mentioned that multi-year bookings are not down “due to competitive pressures, but because customers remain hesitant to sign large multi-year deals.”
  • SNOW vs. Microsoft: “And yes, we will compete, we will compete with Microsoft from day one, and that will – and we’ve been very successful in that regard for a whole bunch of different reasons. But people keep on coming, and that’s – and we expect that. […] The good news is that I think the relationship is relatively mature, meaning that when there is friction or people who are not following the rules, we have good established processes for addressing and resolving that.”
  • “Where you see huge differences is in the total cost of ownership, and that is not the cost of computing and storage. And that is like, what is the cost to run that technology? And this is where [indiscernible] has a huge advantage. And our customers know that. It’s just – it’s reduced skill sets, far fewer people, not having to touch the complexity of the underlying platforms, I mean, on and on and on.”
  • Frank Slootman on Snowpark: “[…] what we’re seeing relative to competitive platforms, Spark and by Spark, we’re seeing Snowpark being only better performance, but better price performance. So, interestingly enough, we see customers giving us technical wins and wanting to migrate because of the better economics of the competitive dynamics.”

My thoughts:

We got reminded that AWS is the closest proxy for SNOW’s performance. And well, AWS’ guide could have been a warning for me. Somehow I thought Snowflake would be able to squeeze out some unexpected surprise.

Actually, they did. But not a positive one. Guiding down 2 quarters in a row is pretty meh and indicates that they have very little visibility these days.

The metrics hat I disliked the most (besides the down-guidance) were total customer additions and the Cloud Data Metrics which slowed down across the board, but the Data Market place listings slowed down significantly. No one asked about these on the call. Too bad IMO, the call was pretty much only about optimization/usage and AI - I would have loved some color on the other metrics, too.

Long-term, I think Snowflake is still a great company with a great product and lots of tailwinds (AI, cloud transformation, data gravity, platforming different verticals, etc.).

Short-term, I don’t see so much upside with SNOW. Its proud valuation is currently not reflecting the trend in the fundamentals - actually, vice versa: its current fundamentals don’t properly reflect the high valuation. Of course, with consumption businesses, we can always get quick and unexpected upside again, but I feel like I better don’t count on it for the remainder of this year.

Bottom-line: Long-term thesis intact, short-term upside likely limited.

I won’t sell out of my position, but I am going to trim it to better reflect my current conviction.

What are your thoughts about this quarter? What do you do with your SNOW allocations - that is if anyone still has any ?

Thanks for reading and looking forward to your thoughts.

@LisaOnCloouud9 on Twitter. Long SNOW (but now: shorter than before :smiley: )


Yes, Wow. Snowflakes ER didn’t make me think they have a handle on any of kind of growth strategy, besides what they’ve been doing. Their acquisition of Neeva was given as the the reason for the share price run, prior to earnings, by some. I just didn’t feel like that was fleshed out very well on this call. Snow Summit isn’t until late June🥴.

I too am concerned about Market place listings, basically falling to irrelevance. The only time in the CC here this was addressed was in a back handed reference, IMO.

Frank Slootman

But the thing is you need to have highly-curated, highly-optimized data. And then – that is what we do at Snowflake to really power these models. You cannot just indiscriminately let these things loose on data that is – that people don’t understand in terms of its quality, and its definition, its lineage, and all these kinds of things. So, I think, we are in a really great place. And I said in the prepared remarks, data has a gravitational pull. So, we will attract tremendous demand for these type of workloads. And our strategy is to enable that to the maximum towards the extent possible.

So…basically Data Market Place was not addressed. I included the above as a sad attempt to say, “I tried.”. :woozy_face:

I wish I had a better place for my money right now. Maybe I’m being lazy. Perhaps inertia is keeping me from giving up on a serious re-evaluation of my expectations. I’ve always been pathologically optimistic, unless I can figure why going back to valuation metrics (PB, PE, etc) is going to necessarily be disproportionately rewarded, not now but, going forward.

Allocation in my portfolio depends on how I value Snowflake. I’m evaluating companies and not trying to figure out how other investors are valuing companies, when I’m making my investment decisions. I try to accurately assess: how efficiently each company will ride the combining waves of adoption for their various market leading technologies up the hockey-stick (Hypergrowth) toward their becoming behemoths.

My allocation has, thus far dropped from 20% to 16%. I’m leaving it there for now.




Wow Jason that is very brave. While I think Snow is a great company, it is really being hurt by this down turn. Having a company with a P/S of 22, should be a company that is hitting it out of the park, not slowing growth. Best of luck to you.

No position in Snow at this time but watching.


Lisa, what a fantastic writeup. I always look forward to your summaries and thoughts of these calls. Thank you for these valuable contributions.

I listened to the call live and have been chewing on it.

While this didn’t excite me from a hypergrowth standard, this bolstered my long-term buy & hold (LTBH) conviction. I believe SNOW mentioned they actually helped some of these customers find ways to optimize and save money in the short run. I know if a vendor did this for my company they’d keep me as a customer for life.

This told me that the hypergrowth spring is being pulled back with more and more tension for when the macro headwinds finally subside and potentially reverse. As a LTBH I’m enthused by that, but as a more immediate hypergrowth holder I’m still skeptical until I see this result in better revenue growth.

Overall, I cut my position from 15% down to 0% for now, although I will probably buy back in a much smaller 1-2% position as a LTBH position in the coming weeks. SNOW is one of my highest LTBH convictions and remains at the top of my watchlist to overweight if they show signs that the loaded spring of hypergrowth does return.


Very well put Lisa and I agree with your assessment. Enjoy your write ups.



Hi Andy,
Your surprise at my allocation was expected. Your use of valuation to explain it wasn’t. I mean, I guess I wasn’t clear about my not using valuations to asses a companies prospects😜.

I just read Bert’s take on Ticker Target. He’s much better than I at expressing his reasons for holding Sniwflake.

The CEO of this company, Frank Slootman, is one of the best of the best when it comes to sales management. It was telling to me that he indicated that the bookings shortfall had nothing to do with sales resources or sales execution or competition or even customer prioritization; it had everything to do with macro trends.

Slootman talked about a number of interesting product initiatives on the call. I am sure many readers would get impatient with me if I tried to reprise many of them. Of the numerous initiatives, the one I found most interesting, and the one that probably has the most revenue potential, is the potential to use Snowflake as a data platform for Supply Chain Management. Supply Chain Management has been an orphan for 20 years since the implosion of industry pioneers ITWO and Manugistics. If Snowflake can succeed in “platforming” a supply chain, the revenue potential is substantial.

He leans towards recommending buying beaten up ‘stocks’ (not beaten up ‘companies’).

I recommend his service to everyone.




Thank you, Lisa, for yet another fantastic report.

I don’t look that deep into a company’s own numbers, but I do compare companies of interest to me against one another.

I also think, as an outsider with limited knowledge, that the long-term thesis is intact. But in the moment, I just don’t see where SNOW excels in absolute terms and even so more once the valuation and market cap are taken into account.

It is not the projected revenue growth, it is not the FCF, it is not the ROE, not ROA, not revenue efficiency, not profit efficiency, and to top it off, the growth, while durable in the big scheme of things, has proven unpredictable.

SNOW scores right in the middle, overall, of the 39 companies I looked at in terms of the above metrics, right behind BILL, btw. However, BILL has 1/5th of the market cap and 1/2 the valuation.

Anyway. Just explaining how I look at SNOW at the moment. If I had a proper LTBH port, I would hold a position in there of 3-4% of my net worth and just let it be for years, The Motley Fool way.


I agree this was a disappointing print.

  1. As @LisaOnCloud9 stated, the 317 total customers added was the lowest in 16 quarters based on the numbers I have (248 in 1Q20).

  2. RPO dropped 7% QoQ. The only other quarter we have that this occurred was last Q1 at -1.4%. So even if this is now a seasonal Q1 thing, that’s a disappointing number. And going back to a thread a couple years ago, SNOW still carries that slide in its presentation stating how RPO is one of its main health metrics.

  3. Adding insult to injury, current RPO expected to be recognized over the next 12 months fell sequentially for the first time ever at -$70M and -3.5%.

  4. Expenses as a % of revenue has ticked up on both a GAAP and non-GAAP basis for the second quarter in a row. Lumpy? Maybe, but still worth watching given the other metrics being pressured.

Pulling back though, even that much digging might be unnecessary. Slootman or no Slootman, Snowflake has now had to drop guidance not once but twice. With dozens of companies floated here and literally thousands on the market, it is hard to make a case SNOW has justified its best-in-class reputation the last several quarters. I’d personally start the slide with the pass-through of cost savings that led to the downside surprise last Q1. That and unfortunate timing into an economic contraction have put SNOW on a trajectory that might take a while to reverse.

YMMV, of course.


Hi Lisa, great write-up as always from you. Since you asked, I sold out of my remaining small SNOW position after this report, going in just a few months from a 24% position in top place in my portfolio, to 16% the next month, to 8% the month after, to 1% and now completely out. The consumption model just seems too unpredictable in this macro. Just think, they missed their guided to revenue growth by a lot two quarters in a row now, even though they were well into the quarter when they gave their guidance. Even the CFO can’t predict. And yet their valuation is higher by far than any of my other companies. Who needs that? I think I just have better places for my money.


Many great comments were already made here, so I’ll add a few thoughts of my own that I hope could enhance the conversation.

@SaulR80683 - Consumption-based pricing has been concerning to me as well for 2 reasons.

First, it is relatively easy for customers to decrease usage without entirely leaving the platform - software “stickiness” may prevent leaving but not optimization (doing the same with less) / rationalization (doing less by focusing on the most important things) of usage.

Second, consumption-based usage throttles benefit maximization and customers do not get “addicted” to the product as quickly. Part of this “addiction” is tinkering (or experimentation / research) and exploring new features / use cases, finding ones that work and scaling them up. If tinkering costs money, people do not tinker as much.

However, in Snowflake’s particular case, it is challenging to have an “all you can eat” type of pricing model. On the ER call, an analyst tried to probe this issue gently - emphasis mine:

And when it comes to pricing, you talked about customers focusing a lot on cost savings. How is this translating into your ability to hold kind of unit pricing, especially on renewals?

Frank Slootman

…the thing about pricing is, look, physics are physics, a read is a read, a write is a write. And there’s economics. It costs a certain amount of money, right? And there’s just not that much room other than playing games or temporarily sponsoring or subsidizing different parts of the business to really get a sustained pricing edge on one player or another. We’re all converging to very, very similar economics.

This tells me that every lever has been pulled to get the cost down to the bare bones - economies of scale have likely been reached. Something else has to be done to differentiate from competition.

@LisaOnCloud9 had already quoted from the following ER call transcript paragraph, and I will emphasize a different portion of it to make my point.

Where you see huge differences is in the total cost of ownership, and that is not the cost of computing and storage. And that is like, what is the cost to run that technology? And this is where [indiscernible] has a huge advantage. And our customers know that. It’s just – it’s reduced skill sets, far fewer people, not having to touch the complexity of the underlying platforms, I mean, on and on and on… So, we have really abstracted the complexity, and that’s what generates this TCO advantage. But the raw cost of computing and storage, there’s not that much opportunity to be [indiscernible].

For context, I am a small business owner. My highest expense is payroll, and my highest pain point is finding and hiring qualified staff. If I can hire fewer people and be less demanding with respect to their qualifications, it’s an absolute gift to me. I talk to many other small and medium business owners, and I feel like we are quoting from the same chapter and verse when it comes to HR.

So if SNOW can have a lower TCO by being easy on the payroll (or consulting expenses), that’d be a large competitive advantage. Then, I ask myself a couple of questions:

  1. Do I see SNOW as having a strong competitive position in its field, and is at early stages of a long growth runway? I think the answer is yes.

  2. Is the company executing well? From the quality of their product, from their growth initiatives, from their responses to questions, I think yes.

So why the huge slowdown, especially when some other SAAS companies seem to be stabilizing or even recovering from the downturn? I think it may in part be related to the fact that SNOW typically uses upfront annual billing. In this case, revenues and even RPOs may be somewhat lagging indicators and SNOW may participate in recovery later than others.

What would be a good comparison? How about MDB - they also have usage-based pricing, and their recent share performance has been pretty good? Here is how they bill: - looks like monthly. I tried to find an annual option on their website, but could not.

Although even MDB got dinged on the recent analyst note: MongoDB falls after Guggenheim downgrade after survey shows no spending rebound | Seeking Alpha Reason? No spending rebound. This tells me that macro is a real, believable cause of a slowdown at SNOW.

But then business cycles are, well, cycles and, IMO, while some hyper-growth investors perhaps extrapolated up-sloping growth to infinity in 2021, it could be similarly suboptimal to extrapolate down-sloping contraction to zero.


I have seen a few anecdotal comments on Twitter that Databricks is winning more business away from Snowflake. I’m not a tech person, so I don’t know if/how they compete - just sharing what I have read from others.

Interesting fact that may interest only me - do you know what that big blue arrow is pointing to in the chart above? It’s the day (12/15/21) that the CEO and CFO sold $340MM and $240MM worth of stock. In a single day. The CEO has sold almost nothing since that day. They knew.

I sold out a week or two prior to ER. I think I sold in the mid 150’s, so I didn’t get any great price or anything. Just lost conviction and did not think it was worth the risk based on the valuation and the current macro.


Like AnalogKid I sold out weeks before the run-up, so I didn’t get a better price than anyone selling today. Why did I sell? Because I updated my beliefs/thesis on Snowflake’s long term future. I once believed they would grow faster than most any company for longer than most any company. Here are my updated beliefs:

  1. I’m lowering my expectations for future revenue growth. I’m still fairly convinced Snowflake will reaccelerate after growth slows to ~30% YoY the next few quarters. But to what? Not 50%+, I don’t think, at this scale…maybe for a few quarters but not year after year. And I see no reason to believe in their $10b target, because…
  2. I’m now painfully aware that management doesn’t have as much visibility as I formerly believed, and that they were not enough aware of this to avoid having to lower guidance. Two quarters in a row.
  3. I’m concerned with large customers reducing spend even by dumping some stale or less valuable data this quarter. How much data will be dumpable? Will they be able to do this every year as data ages? And so…are these very large customers going to expand much year after year? Can they afford the bill to do so?
  4. Many customers will surely continue to expand and ramp up, but the NRR has been mega-juiced by giant customers ramping up. While I expect they will continue to find giant customers, each one going forward obviously moves the needle a little less than the previous one (which was borne out this quarter when they added the same number of $1 million+ customers (roughly) that they’ve added each of the last few quarters (~40 customers) and revenue growth and NRR came down.
  5. The high valuation becomes more of a problem as growth slows. And for the last 12 months, FCF was 28% of revenue. There’s not that much more expansion they can do there (certainly not explosion – further expansion of FCF will be incremental)…so coupled with a top line that obviously isn’t going to be growing at 50%+ every single year…the math doesn’t really work. It’s already a ~$50b+ company…I’m not gonna limit them – maybe they can be a trillion dollar company someday, but if that’s 25+ years away, what’s your rate of return? And how high are the chances that doesn’t happen? In my opinion, there’s not enough long term upside to offset the long term risks.



I believe 10 billion is target for 2028. So that is 5 years out from this point. Today SNOW based on current quarter annualized is 2.5 billion, so we need a quadruple from this point. FY 24 guidance is 2.6 billion at 30 percent growth. I believe they will beat it, there is only so much optimizations that companies can do. But even assuming 2.6 billion, they need 40 percent to hit 10 billion in 4 years, which does not look unreasonable. Granted, it is harder to move numbers at higher numbers. But the market here for a data cloud is massive and opportunity space bigger than that of a typical SAAS company. I would say somewhere a notch below the hyperscalars. (For context Oracle does 50 billion a year).


Interesting, but how much does Snowflake get vs Databricks and others? And how long does it take? And the hyperscalers have slowed massively…so how do we know that (for example) AWS will ever reaccelerate to 25%+ growth? And if data cloud grows a notch below that…maybe I’m not following you.

And how do you update your Snowflake-specific expectation vs their visibility and execution lately?



Not sure why anyone would think someone can sincerely answer these questions. Or maybe these questions are intended to be rhetorical, but they didn’t present to me as rhetorical in this thread.

At least @Oracleoo provided: a company target for Snowflake, which is likely more informed then anything we can produce, and a market size reference point from a large-scale competitor (Oracle) that has almost certainly lost tons of potential and existing business to cloud alternatives both for data storage and other applications like CRM (Salesforce in particular).

The answers to these questions are unknowable for Snowflake and the equivalent questions for the future and competitive landscape of any other company are also unknowable.

Do you (or anyone) have these answers for the future for any company you currently own or have ever owned?

If yes, please share the details.


Maybe rhetorical is an apt word. My questions were meant to prod at the question: what if [Oracleoo] is correct? What does that mean for Snowflake?

He/she said 40% growth is “not unreasonable” for the next several (four?) years. I was disagreeing with that (though perhaps I should have been more explicit), even if he/she is correct about this statement:

For context, Oracle is a ~$280b company. How many years would Snowflake have to grow at 40% to get to 50b in revenue? And if they were only a $280b company at that point, what would the rate of return be?

Not sure if that is rhetorical…but it’s a good math problem.



The real question is does a company that is growing at 30 percent worth a P/S of 21.5. I think not. Snow has a long ways to fall.



That’s a much more precise question about a specific hypothetical valuation and growth trajectory.


Ok, let’s look in context, at the forest as a whole, what do we see?

Using an aggregator of information for analysts consensus 2023 expected growth:

AAPL 1% growth and 7 P/S. But stellar ROE and safety.
MSFT 7% growth and 12 P/S. But top of the mountain safety.

SNOW 42% at 24 P/S (again aggregator data) vs
TTD 21% at 20 P/S or

ENPH 40% at 9 P/S or
CRWD 37% at 16 P/S.
PANW 28% at 10.

BILL 60% at 11
S 54% at 14
MNDY 36 at 14

And so on and so forth. It is hard to find a pattern but a few things stand out:

Cannot take the macro out of the analysis. Otherwise, one can never explain the valuations of Big Tech and especially AAPL and MSFT. Forget the AI mania. Similarly, sure there is some organic/non-organic lapping, but the cheapness of BILL and S is inexplicable outside the macro.

In short, the valuations TO ME seem to expose how the market as a whole sees the next 6-12 months. Nothing more than that. It does not mean that any particular company will deliver better or worse returns over the short-term.

What it should mean is that the surest way to handicap long-term returns now is to join the QQQ train or its constituent parts, especially AAPL and MSFT.

And massive upside value investing now is ENPH, BILL, S, MNDY just paying attention to the company actually making it to the other side. I do not understand ENPH’s low valuation given the company’s exceptional profitability, but for the other three, the market just seems to prioritize risk avoidance with little care for anything else.

As for TTD and SNOW, they fall in between. To me, the market considers them best in class and in no danger of going under.

So that’s what the valuations tell me.

It is a quintessential Motley Fool moment: one is looking past the Wall St calendar year time horizon.


This earnings call stands out to me as being strikingly bad both from a product and numbers perspective.

The prior earnings report to this one had predicted full year 24 revenue as 2.7B and this is revised down to 2.6B

On the product side they are getting hit from optimizations from every direction. These are just the four obvious ones,

  1. Archiving or deleting old data. Older cohorts are apparently deleting data to save costs. They said on the call there’s no visibility or way to control this because the customer can determine their strategy.

  2. Hardware optimizations make queries run faster and cost less. Hardware is going to continue to optimize as time goes on.

  3. Query optimizations by the customer. Their customers are looking to save. They mentioned in 2020 and 2021, it was growth at all costs and the mentality was let it rip. Now they are saying it is the inverse.

  4. Internal Snowflake optimizations. There’s been twice where the engineers at the company discovered ways to speed up things by ~20% which means Snowflake gets less revenue.

They said on the call that AI is going to drive a whole other vector in terms of workload development. Where is it though in the results?

They reported the same day as Nvidia and the results are dramatically the opposite. I’m trying to understand myself why hardware companies are benefitting so much more then software from AI right now, and will start a separate thread on this topic.