We recently compiled a list of the 11 Best Cloud Stocks to Buy According to Analysts. In this article, we are going to take a look at where Snowflake Inc. (NYSE:SNOW) stands against the other cloud stocks.
The surge in internet speed and usage has created a plethora of new industries in its wake such as eCommerce, social media, and online streaming. On the business side, one of the biggest beneficiaries of advances in communication is cloud computing. Cloud computing in its simplest terms is the use of computing resources virtually, where companies host expensive hardware and data servers and sell this capacity to customers.
Naturally, it’s unsurprising that some of the biggest companies in the world either directly offer cloud computing software products or the hardware that powers these systems. In fact, out of the five most valuable companies in the world in terms of market capitalization, three have leading cloud computing divisions (Google Cloud, Amazon AWS, and Microsoft Azure) while the other is a hardware company that is Wall Street’s AI darling.
In fact, cloud computing is so valuable that research from Bloomberg shows that AWS alone can reach a whopping valuation of $3 trillion. To wit, only the world’s biggest companies have crossed this metric, so this figure shows the potential that’s present in this industry. This isn’t the only time that a trillion dollar figure has been chosen to describe cloud computing’s potential. One of the biggest benefits of cloud computing is that it allows businesses to save on costs by outsourcing their hardware procurements.
These benefits will be worth quite a bit as research from McKinsey shows that by 2030, they can enable cloud computing companies to capture up to $1 trillion in run rate operating income (EBITDA) from Fortune 500 firms. Run rate EBITDA is a key metric in cloud valuation, as it projects current earnings into the future to make an estimate of value. Another mention of the enticing trillion dollar valuation comes in the form of market research. This suggests that the global cloud computing market was worth $484 billion in 2022, and from 2023, it can grow at a compounded annual growth rate (CAGR) of 14.1% to be worth $1.5 trillion.
Looking at these estimates, it’s clear that there’s at least some value in cloud computing stocks. The next question to ask is, how does one pick out the right cloud computing stocks? On this front, there are several valuation metrics that can be relied upon. Standard models such as the discounted cash flow (DCF) often do not capture the potential of cloud computing stocks since there are few reasonable estimates to measure their growth. These stocks differ from traditional companies since they don’t have to fork out massive capital to buy equipment and prime themselves for growth. Instead, software development is a margin heavy business with low development costs and stable, recurring revenue. This makes management focus on growing market share, and since this also leads to higher operating costs, many cloud computing stocks remain unprofitable for years.
The direct implication of this fact on valuation is that cloud computing stocks cannot be valued by traditional metrics such as the price to earnings (P/E) ratio. Instead, the enterprise value to sales is used as it captures the market and debt value minus cash and compares its scale with the revenue that the firm generates. Investors also have to nevertheless measure the ‘value’ a firm is generating even though it’s unprofitable. This is captured through the free cash flow. One of the most well known cloud computing stock valuation metrics is the Rule of 40. This combines the FCF with the revenue growth rate to evaluate the margins that such firms achieve. The logic is that the revenue growth rate plus the FCF margin (FCF divided by revenue) should be greater than 40 for a cloud computing firm to be sustainable. Combining these together, the ideal cloud computing stock should have a high Rule of 40 scores but a low EV/Sales, as this principle shows that a sustainable business is available at a cheap entry price.
Looking at the data, the EV/Sales multiple varies with a firm’s growth rate, and those with higher growth naturally command a higher multiple. For instance, as of recent market close, data shows that stocks with a Rule of 40 score greater than 40 and a revenue growth rate greater than 30% (Category 1) have a median EV/Sales multiple of 12.5x. On the flip side, those that fall below both of these have a median multiple of 5.1x (Category 2). Crucially, though, the category of stocks that have a growth rate higher than 30% but a Rule of 40 scores lower than 40 (Category 3) have a median EV/Sales ratio of 12.2x in today’s market which implies that investors are valuing growth more than profitability.
Why do we say “today’s market”? Well, when we compare this to the era of low interest and inflation rates in, say October 2021, the picture is different. Back then, Category 1 firms had a median EV/Sales ratio of 27.7x (!) while Category 3 firms had a ratio of 24.9x. This difference was even sharper in September 2020, with a ratio of 42.3x for Category 1 stocks and a value of 29.1x for Category 3 firms. To conclude, it appears that investors place a higher premium on growth than profitability when inflation tightens the belt and higher rates place a premium on attracting business spending for cloud computing stocks.
Our Methodology
To make our list of the best cloud stocks according to analysts, we ranked the holdings of First Trust’s cloud ETF by their average analyst percentage share price upside and picked out the stocks with the highest upside.
We also mentioned the number of hedge funds that had bought these stocks during the same filing period. Why are we interested in the stocks that hedge funds pile into? The reason is simple: our research has shown that we can outperform the market by imitating the top stock picks of the best hedge funds. Our quarterly newsletter’s strategy selects 14 small-cap and large-cap stocks every quarter and has returned 275% since May 2014, beating its benchmark by 150 percentage points (see more details here).
A software engineer at work, surrounded by a wall of computer monitors connected to a ‘Data Cloud’ platform.
Snowflake Inc. (NYSE:SNOW)
Number of Hedge Fund Investors in Q1 2024: 73
Analyst Average Share Price Target: $206.66
Upside: 52%
Snowflake Inc. (NYSE:SNOW) is one of the biggest cloud computing companies in the world. It is a data processing cloud company that allows businesses to consolidate their data and generate insights. Estimates show that Snowflake Inc. (NYSE:SNOW) holds a 22% market share in the data warehousing market, making it unsurprising that the firm’s latest market capitalization sits at $44 billion. While this relieves some of the pressure on management to pursue the holy grail of growth in the cloud industry, Snowflake Inc. (NYSE:SNOW) is yet to turn a profit despite its heft. This also increases the pressure on management to achieve profitability, or high free cash flow and operating margins. Snowflake Inc. (NYSE:SNOW)’s management had also set lofty expectations for growth, but when it withdrew its FY2029 $10 billion revenue target in February, investors reacted and the shares plummeted by 27% in the aftermath. The following quarter wasn’t great on the cost front either, as its gross profit and operating margin guidance for the full year were guided at 75% and 3%, respectively. These were lower than the 75% and 6% that it had previously guided.
However, Snowflake Inc. (NYSE:SNOW)’s management is quite optimistic about its AI initiatives. During the Q1 2025 earnings call, it shared:
Like first and foremost, I think it is important for all of us to acknowledge that AI language models are going to have an impact at multiple levels of what you can think of as a data stack. So for example, the way in which people are going to be migrating from an old system, an on-prem system to something like Snowflake, is going to be aided by the presence of a Copilot that can do much of the translation. We already have such a translation product and we think AI is going to make that go even faster. But in other areas like data cleansing, data engineering that are perhaps not as sexy, but nevertheless required a huge amount of investment in order to make sure that the data is enterprise grade.
We think AI is going to play a big role both in the creation of those pipelines, but also in things like how does one make sure that the data is clean. For example, if PII accidentally flips into a table or a distribution goes very wonky, language models can help detect deviations from patterns. And then going up the stack, we have a very acclaimed product for writing SQL, our Copilot within our user interface, that can significantly accelerate in analysts’ ability to get to know a data set and be productive with it. And then, of course, to something like a data API, which now begins to put enterprise data into the hands of a business user, but with a very high degree of reliability. And so my point is there is a broad impact. And I think things like automating some of the work that an analyst has to do, for example, to troubleshoot problems, will be things that a language model can do.
Having said that, for a variety of problems, small models, which we are perfectly capable of developing from scratch like we have done for document AI or more a midsized model like what we did with Arctic, actually suffices for the vast majority of the applications that I’m talking about. And so there are academic benchmarks like there’s one called MMLU, it’s a notoriously difficult benchmark, and depends very much on model size and how many dollars people are throwing at training those models. We can get a huge amount done with a small team under modest investment without needing to play at that level where you’re talking — companies are talking about spending billions of dollars. I don’t think we need to be there. I think being very focused on what we need to deliver for our customers will take us a long way with the amount of investments that we are making.
And finally, I will add that we have amazing partnerships with a ton of people. Even today, I wrote about how we’re collaborating with landing that AI and doing company, but we have partnerships with Mistral, with Reika with a ton of other companies. The field of AI is so large that I don’t think there’s going to be one company that is going to make every model that every person is going to use. We are very good at developing the models that we need in our core and we actively collaborate with a large set of players for other kinds of models. And obviously, they see value in the 10,000 customers we have and being able to go to market together. And so I think this is likely to continue for the indefinite future in terms of what we need to do.
Overall SNOW ranks 2nd on our list of the best cloud stocks to buy. You can visit 11 Best Cloud Stocks to Buy According to Analysts to see the other cloud stocks that are on hedge funds’ radar. While we acknowledge the potential of SNOW as an investment, our conviction lies in the belief that some AI stocks hold greater promise for delivering higher returns and doing so within a shorter timeframe. If you are looking for an AI stock that is more promising than SNOW but that trades at less than 5 times its earnings, check out our report about the cheapest AI stock.
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Disclosure: None. This article is originally published at Insider Monkey.
