Stocks in This Issue
|Stock Name||Market Cap||Price||Investment Type||Current Rating|
|Bentley Systems (BSY)||$15.5 billion||52.9||Growth + Value – Design Software||Watch|
|Datadog (DDOG)||$31.1 billion||96.7||High Growth – Infra. Monitoring||Buy 1/2|
|GitLab (GTLB)||$7.60 billion||49.7||Rapid Growth – Software Dev. Tools||Watch|
|Shopify (SHOP) ★ Top Pick ★||$82.4 billion||64.5||High Growth - eCommerce||Buy 1/2|
|Shutterstock (SSTK)||$1.75 billion||48.6||Growth & Income – Content Marketplace||Watch|
Is Artificial Intelligence (AI) Hype or the Real Deal?
Excitement over the potential of generative Artificial Intelligence (AI) has helped push more than a few tech stocks to new highs this year and brought many more well off their lows.
And for good reason. Rapidly evolving AI technology has the potential to open both revenue and margin expansion opportunities for a lot of companies.
How they leverage it will determine who the eventual winners and losers are. But one thing is certain – AI is definitely the real deal.
That said, the excitement over AI does feel overdone. It’s not going to change things overnight and turn crappy companies into winners.
Rather, it’s going to be all the rage for a while then become part of the everyday conversation. Much like cloud technology did over the last decade.
Even if you fall into the “AI is hype” camp you’re likely appreciative that, after more than a year of awful trading action, excitement over AI has pushed the S&P 500 back into bull market mode.
In order to have a conversation about AI we first have to understand what it is.
In the simplest terms, AI means using computers to do things that require human intelligence that were traditionally done by people. AI does what it does by using algorithms to find patterns and relationships in data.
The market excitement has really centered around generative AI, which is the ability of applications to use data to create content such as images, text, audio and video.
But there has also been a lot of discussion around the potential of AI in terms of analytics, automation, organization and other process and efficiency types of use cases.
It doesn’t take too long to realize that any discussion of company-specific AI use cases quickly evolves into a discussion of infrastructure, models and algorithms, and software applications and platforms.
AI infrastructure includes a mix of hardware (GPUs, networking equipment, memory, storage, etc.) and software resources. A few companies in this bucket include hardware providers like Nvidia (NVDA) and Super Micro (SMCI) and the cloud infrastructure providers, Microsoft (MSFT), Alphabet (GOOG) and Amazon (AMZN).
The models, algorithms and code are the real heart of AI. These technologies continuously take in data, use it to get smarter and smarter and are then used to power customer-facing applications and platforms. The best-known examples are OpenAI’s Generative Pre-trained Transformer 4 (GPT-4) and Google’s Bidirectional Encoder Representations from Transformers (BERT).
The applications and platforms are, like with cloud software, what the average user notices and interacts with. The most obvious example right now is OpenAI’s ChatGPT, which can be used via Microsoft’s Bing search engine and Edge browser. AI is also used “behind the scenes” with Apple’s (APPL) Face ID and HubSpot’s (HUBS) ChatSpot conversational bot.
As a closing comment, and speaking in very broad terms here, we’ve already seen that the initial beneficiaries of AI have been larger companies. Why is that?
It’s probably because investors recognize that companies that already have a lot of customers, products and resources – not to mention ownership over their own data – are going to be able to move the fastest to leverage AI to find new revenue sources and/or increase margins on existing solutions.
That’s not to say there are no smaller companies attracting investor attention for their AI potential. There certainly are. Most of these either have a head start over peers in a very specific market or are meme/speculative stocks.
I’m very interested in the larger companies, and the smaller ones with head starts. My reasoning is simple – these were good companies before investor interest in AI exploded and it should provide a tailwind.
These are the stocks this Issue is focused on.
As a final note, it’s worth pointing out that we already have exposure to a few of the best stocks to leverage AI’s potential, namely MSFT and HUBS.
For that reason, and because I don’t want to run the risk of adding a ton of exposure right after a big market rally, we’ll continue our slow and steady strategy of adding a few stocks every month.
What to Do Now
The S&P 500 has come up 20% from its low, marking a new bull market.
There are even early signs of life in the IPO world. After one of the worst years for new offerings in decades in 2022 (just 71 IPOs) things are picking up, slightly. There have been 46 IPOs YTD, a 23% increase versus last year at this time. The Renaissance IPO ETF (IPO) hit a nine-month high last week.
We also have a Fed that elected to hold rates steady in June. Whether or not they’ll move forward with another hike or two throughout the year remains to be seen.
Factoring in the relatively strong economy, a decent Q1 earnings season and a reasonably constructive outlook for 2023 earnings, things feel a HECK of a lot better than they did a few months ago.
The only question now is … has the market moved too far too fast?
Maybe. After this run, some give-back is entirely possible prior to Q2 earnings season since there isn’t an obvious catalyst. That said, it feels like we’re in a much more stable macro/interest rate policy environment, plenty of stocks/sectors haven’t participated all that much in the rally and investors are realizing the sky is no longer falling.
These should all be positive for the market over the coming 12 months.
Short version, we’re not changing portfolio management tactics. Continue to selectively add positions (partial positions are good) and trim here and there depending on company-specific factors/performance.
Bentley Systems (BSY)
If you want to combine a U.S. infrastructure play and AI exposure, Bentley Systems (BSY) is the ticket.
The company sells software that is used by engineers, architects, city planners, geospatial planners, etc., to design and build large-scale infrastructure systems. We’re talking things like corporate campuses, industrial facilities, roads and bridges, water and wastewater systems and so on.
Bentley is a direct beneficiary of the trillions of dollars of incentives becoming available through the CHIPS and Science Act, the Inflation Reduction Act (IRA) and the Infrastructure Investment and Jobs Act.
Collectively, these incentive programs are driving tons of manufacturers to secure locations for new plants in the U.S. Reuters reports demand for sites to build semiconductors, EVs, solar equipment and more is so strong that it’s hard to find large building sites that are ready to go.
The company has a ton of solutions. A few include MicroStation-based apps for modeling and simulation, ProjectWise for project delivery, AssetWise for asset and network performance and the iTwin platform for infrastructure digital twins.
As far as AI goes, Bentley uses the technology in its digital twin solutions for visualization, simulation and monitoring, in reality modeling solutions (3D models created from pictures and videos) and in various design automation and efficiency solutions.
Truth be told, AI is already integrated into many of the company’s basic and premium offerings. So the path forward is really about continuing to bring more AI features into its entire product suite to help make design, engineering, visualization and simulation processes more efficient.
Turning to financial performance, Bentley is more steady growth than fast and furious. Revenue was up 20% in 2021 and up 14% in 2022. Expected revenue of $1.23 billion this year implies 12% growth.
The company is also consistently profitable. Expected 2023 EPS of $0.86 implies 4% growth over last year. Acquisitions are part of the story as well.
On the Q1 2023 earnings call (May 9) management surpassed expectations and talked about a strong start to the year with public works, utilities and industrial markets all notable standouts.
The only real issue with BSY is that it trades at a premium valuation, which may or may not matter much, depending on investor risk tolerance and broad market performance.
BSY came public on September 23, 2020, at 22 and jumped 52% the first day. The stock peaked at 71.9 during the pandemic (September 2021) and bottomed out at 26.3 last May. Throughout the balance of 2022 BSY was up and down mostly in the 30 to 42 range. Shares entered 2023 trading around 37 and the stock tightened up over the first four months of 2023, mostly staying above its 50-day line. The stock jumped above 45 after the Q1 earnings report and has raced up into the low 50s since. We’ll put BSY on our Watch List today. WATCH
We doubled our money on Datadog (DDOG) in 2021-2022 as demand for cloud infrastructure monitoring soared.
The company was already enjoying a strong market for solutions that monitored and protected applications in public, private and on-premise cloud infrastructure before the pandemic. Then the boom in work-from-home when Covid hit was like throwing gas on an already red-hot cloud security market.
Things calmed down a bit as pandemic restrictions eased. But there’s no doubt Datadog has held on to a ton of business and become one of the premier vendors in its specialized market.
Revenue this year should be around $2.1 billion. That’s up 250% from 2021. Datadog is also very profitable – EPS was almost $1.00 last year – and both revenue and earnings should grow well north of 20% for several years.
The big-picture reasons the company is doing well are about the same now as they were a few years ago. We also have an emerging AI boom that could be like another bucket of gasoline thrown on the infrastructure monitoring market.
Think of it this way: The two big megatrends that Datadog taps into are: (1) digital transformation (using digital technologies to create new and/or evolve existing business models, operations and customer experiences) and (2) cloud migration (moving data and applications from a company’s private, on-site servers into a cloud provider’s servers).
As companies create new applications and generate/capture new data, they call on Datadog to keep it all safe and functioning.
AI is likely to speed up the creation of digital applications and the amount of data those technologies create.
That should be good for Datadog, which will use AI in a variety of ways to develop, launch and operate its own application/data monitoring, alerting and issue-resolving solutions.
Within its platform of 17 solutions Datadog already offers Watchdog, an AI-powered solution that detects potential application and infrastructure issues and alerts users to irregularities.
Expect more AI-powered solutions in the future. After all, Datadog has nearly 26,000 customers (300 of which spend $1 million or more a year) and its platform integrates with over 600 applications.
It would be an absolute shocker if the company isn’t moving quickly on AI every hour of every day.
DDOG came public at 27 in September 2019, jumped 39% its first day and eventually ran all the way to 200 during the peak of the pandemic bull market. By the time the post-pandemic correction was over shares had given half of that back. DDOG bottomed at 61.3 on January 6, 2023. While DDOG rallied to 90 in February it moved right back into the low 60s in March. It wasn’t until after earnings on May 3 that DDOG got going. And even now, with shares trading around 96 and up 46% from their low, the stock is still pretty beat up. We’ll take a swing on a half-sized position. BUY HALF
GitLab (GTLB) is another way to approach AI potential from the infrastructure angle (like DDOG).
The company provides a source code management (SCM) platform. It includes a variety of tools software developers use to collaborate, share, track changes and resolve code conflicts.
Big picture, GitLab’s end-to-end DevOps platform functions as a system of records for source code. Yes, the platform has a lot of fancy tools that software developers across all industries use to develop and deploy applications quickly, efficiently and at scale for their customers.
But for the layperson, the important thing to understand is that the quality and stability of an organization’s/application’s source code is everything in the digital economy. No application exists without it. And having a platform that permits near-instantaneous changes can mean success or failure for users that rely on that application.
That’s what GitLab provides.
In terms of AI, the company has already integrated AI into the platform and has been using it for years. AI is used to generate code, summarize various code management processes (reviewers, issue comments, merge requests, etc.), generate tests, explain code and in GitLab chat, to name a few.
There are many more AI offerings and product enhancements in beta mode, likely to be released on an ongoing basis once they can reliably help software engineers work more efficiently.
Specifically, expect GitLab to focus AI development in the three areas of Automation, Intelligent Code Security and Code Suggestions.
With just over 7,000 customers and over 1 million paying users, AI capabilities can be significant in both new customer acquisition and retention. That said, Microsoft owns GitHub, a competing platform. And with Microsoft’s partial ownership of OpenAI and massive scale, it’s a formidable competitor.
It may be that GitLab’s best path forward is to be acquired by a similarly large player. But we’ll see. With 2022 revenue of $424 million (+68%) and estimated 2023 revenue of $540 million (+27%), it’s no slouch. EPS is also likely to turn positive next year (estimated 2023 EPS is -$0.15).
Given all the variables we’ll keep an eye on the stock for now.
GTLB came public at 77 on October 14, 2021, and traded as high as 143 during the pandemic. It gave it all back, and then some. GTLB traded into the mid-30s last November and even that wasn’t low enough. Shares seem to have finally bottomed just weeks ago, at 26.2, on May 4. Some excitement came back to the stock after the June 5 earnings report, which sent GTLB from 35 to around 50 over a couple of weeks. It’s an intriguing company, and there’s clear potential, but we’ll look for a little more evidence that the stock can sustain some momentum before jumping in. WATCH
Shopify (SHOP) ★ Top Pick ★
I featured Shopify (SHOP) last month and discussed the stock’s upside potential as the company bails on its logistics business (Shopify Fulfilment Network, or SFN) and refocuses on what it does best – namely, being a pure-play e-commerce specialist for small- and medium-sized businesses.
Things are going according to plan for Shopify. SFN has been sold to Flexport for the expected 13% equity position and the company is now free of the open-ended capital spending program required to build out a fulfillment business.
Also, over the last four weeks, investors have become enamored with any stock with potential to harness artificial intelligence (AI) technology. Shopify isn’t the first name most investors land on when thinking about AI. But it should be right up there in the top 10.
First, Shopify is already one of the leading e-commerce companies out there with over 2 million sellers and nearly $200 billion of gross merchandise value (GMV) flowing through its platform in 2022. The company powers around 10% of all U.S. e-commerce.
There is a lot of room for technology to improve/streamline/personalize things.
At the top of the list is AI technology that can make it easier for shoppers to find what they want. Shopify is already using AI in its Shopify Magic solution (released earlier this year), which auto-generates product descriptions based on search keywords.
The company has also released an AI shopping assistant (March 2023) that provides product recommendations and other engagement tools (abandoned cart, etc.) for customers.
And the new Commerce Components solution for enterprises, which integrates with Google Cloud AI, is aimed at bringing much larger retailers into the fold.
For now, these AI tools are mainly aimed at helping Shopify customers drive higher sales and better customer experiences, thereby boosting sales conversions on Shopify’s platform. This is a relatively easy lift at this point. And the technology may help Shopify do a lot more with less overhead.
Looking forward, I expect to see AI play a larger role on Shopify’s platform, including personalized advertising, human modeling for clothes, retailer storefront design, creative abandoned cart reminders, product recommendations and more.
It’s hard to see any other e-commerce player, other than Amazon, with more potential to leverage AI than Shopify.
Back to the numbers, remember that the company delivered a better-than-expected first quarter.
Free cash flow and profit margins are set to grow significantly now that the SFN drag has been cut free. Revenue should be up by at least 15% this year, then 25% next year. EPS of $0.22 this year could double next year.
The bull case could be a lot better.
Shopify came public at a split-adjusted 1.5 in May 2015. At the pandemic peak, it traded near 176 (again, split-adjusted). While revenue has continued to trend higher since forever, SHOP fell nearly 50% from its pandemic high through October 2022. After bottoming near 23.6 the stock enjoyed a tentative recovery with a few decent rallies. From the end of February through May 4, SHOP traded mostly in the 40 to 50 range. Then it broke out on the SFN divestment news and rallied nearly 40%. Over the last seven weeks, SHOP has held up well, trading in the 55 to 65 range, with most of that time spent well above 60. BUY HALF
In the early 2000s, a photographer and programmer named Jon Oringer saw a gap in the market for selling stock photos. He uploaded 30,000 of his own pictures, created a website, and started charging $49 a month for unlimited downloads.
A couple decades later, his company, Shutterstock (SSTK), has grown into a significant online marketplace for digital commercial imagery, including photos, 3D models, video footage and music.
The platform brings contributors and users of content together so they can supply and/or source high-quality, licensed content. The company generated revenue of $828 million (+7%) last year and EPS of $3.87 (+11%).
Contributors simply upload their content to Shutterstock’s web properties and earn royalties based on customer download activity.
Users of content include brands, businesses, media companies, prosumers and consumers. They can search a huge variety of content for what they want, pay a license fee and use that content for a variety of purposes ranging from websites, marketing materials and social media posts to media productions, games and architectural renderings.
Shutterstock is a steady and modest-growth company that’s profitable. But with corporate spending (especially among small and mid-sized businesses) more tightly controlled in 2023 and e-commerce sales weak lately (especially in Europe) investors have been lukewarm on the stock.
Generative AI has the potential to change that. At the BofA Global Tech Conference earlier this month management discussed three big areas of opportunity.
First is the potential for Shutterstock to sell clean data to companies so they can train their models on licensable content. Use of clean/licensed data is a key differentiator since it means Shutterstock customers will have legit content that will stand up forever and they won’t become the center of trademark and/or IP issues that will likely plague users of illicit data.
Second, Shutterstock has preferential access to OpenAI’s API. It was one of the companies that provided data to help train DALL-E 2 into the model today. This means the company has a timing advantage for building AI technology into its solutions.
Third is the potential to grow Shutterstock’s funnel of freemium users (no or low-price solutions) then upsell them to paid/higher-priced solutions. There is also potential at the mid and high end (enterprise scale) of the market for premium content. For example, 3D models sell for around $50 each versus a dollar or two for basic images.
The company is not wasting time. It recently launched an AI image generator which drove a wave of new users (albeit free ones). Back in March, management said 10% of subscribers had tried the solution, generating two million images on Shutterstock weekly.
Looking forward, analysts see Shutterstock growing revenue by around 3% to $850 million this year and delivering EPS of $4.08 (+5%). Revenue from AI and GIPHY (recently acquired from META) aren’t factored into expectations and management has sounded a conservative tone given weakness in e-commerce (but strength in enterprise).
A share buyback program ($100 million), cost reductions and ongoing dividend payments (current yield 2.2%) are additional teasers for a stock that’s struggling but which could snap back at any moment on a variety of potential catalysts.
SSTK came public in 2012, and while the stock hasn’t always been great, revenue and EPS have trended in the right direction. EPS growth was particularly strong during the pandemic and helped SSTK hit 128 in October 2021. But by last November shares were back in the mid-40s. The stock rallied nearly 50% in January when AI fever caught fire but drifted lower then really dropped after the April 25 earnings report. With the stock still bouncing around near 50 we’ll monitor the potential from a safe distance. WATCH
Previously Recommended Stocks
Since the May 17 Issue, we have made two sales. We sold another third of our position in Xponential Fitness (XPOF) on May 22 for a 39% gain (we still own one third of a position) and we sold our half position in Samsara (IOT) for a 23% gain.
From our Watch List today I’m dropping coverage of Shift4 Payments (FOUR) due to mediocre performance and an uninspiring quarterly report in May.
An updated table of all stocks rated BUY, HOLD and WATCH as well as recent stocks SOLD, is included below.
Please note that stocks rated BUY are suitable for purchasing now. In all cases, and especially recent IPOs, I suggest averaging into every stock to spread out your cost basis.
For stocks rated BUY A HALF, you should average into a position size that’s roughly half the dollar value of your typical position. We may do this when stocks have little trading history (for instance, IPOs), when there is more uncertainty in the market or with a stock than normal, or if a stock has recently jumped higher.
Those rated HOLD are stocks that still look good and are recommended to be kept in a long-term-oriented portfolio. Or they’ve pulled back a little and are under consideration for being dropped.
Stocks rated SOLD didn’t pan out, or the uptrend has run its course for the time being. They should be sold if you own them. SOLD stocks are listed in one monthly Issue, then they fall off the SOLD list.
Please use this list to keep up with my latest thinking, and don’t hesitate to email with any questions.
|Company Name||Ticker||Date Covered||Ref Price||6/21/23||Current Gain||Notes||Current Rating|
|Airbnb||ABNB||1/20/22 & 8/4/22||139.02||127.31||-8%||Top Pick||Buy|
|e.l.f. Beauty||ELF||4/19/23||93.53||110.4||18%||Buy 1/2|
|HubSpot||HUBS||4/19/23||417.04||515.64||24%||Top Pick||Buy 1/2|
|Rivian||RIVN||10/19/22 & 5/22/23||22.51||16.09||-29%||Top Pick||Buy|
|Shopify||SHOP||6/21/23||NEW||64.26||NEW||Top Pick||Buy 1/2|
|Snowflake||SNOW||10/19/22 & 3/8/23||156.56||182.22||16%||Buy|
|Xponential Fitness||XPOF||9/21/22||19.86||26.63||34%||Top Pick||Hold 1/3|
Recently Sold Positions
|Company Name||Ticker||Date Covered||Reference Price^||Date Sold||Price Sold^||Gain/loss||Notes|
|Axonics||AXNX||5/18/22||49.09||1/9/23||57.38||17%||Sold Second 1/4|
|Halozyme||HALO||12/21/22||57.89||1/11/23||50.45||-13%||Bought 1/2, sold 1/2|
|Bill.com||BILL||6/17/20||77.73||1/13/23||101.75||31%||Sold Final 1/4|
|Chewy||CHWY||12/21/22||40.75||1/13/23||43.57||7%||Bought 1/2, sold 1/2|
|Xponential Fitness||XPOF||9/21/22||19.86||1/13/23||25.4||28%||Sold 1/3|
|Axonics||AXNX||5/18/22||49.09||2/2/23||61.57||25%||Sold Final 1/4|
|NerdWallet||NRDS||11/16/22 & 1/13/23||11.31||2/16/23||18.78||66%||Sold 1/3|
|Option Care Health||OPCH||10/19/22||33.78||2/23/23||31.13||-8%||Trade Opportunity|
|PowerSchool||PWSC||2/15/23||23.73||2/23/23||23.59||-1%||Bought 1/2, sold 1/2|
|PINS||9/21/22||24.49||3/8/23||25.94||6%||Bought 1/2, sold 1/2|
|Sight Sciences||SGHT||1/18/23||12.38||3/10/23||9.79||-21%||Bought 1/2, sold 1/2|
|NerdWallet||NRDS||11/16/22 & 1/13/23||11.31||3/10/23||19.32||71%||Sold second 1/3|
|NerdWallet||NRDS||11/16/22 & 1/13/23||11.31||5/3/23||10.36||-8%||Sold final 1/3|
|SiTime||SITM||3/15/23||124.19||5/4/23||89.96||-28%||Bought 1/2, sold 1/2|
|Catalyst Pharmaceuticals||CPRX||12/21/22||18.99||5/17/23||12.43||-35%||Bought 1/2, sold 1/2|
|Xponential Fitness||XPOF||9/21/22||19.86||5/22/23||27.52||39%||Sold second 1/3|
|Samsara||IOT||3/3/23||19.27||6/2/23||23.63||23%||Bought 1/2, sold 1/2|
The next issue of Cabot Early Opportunities will be published on July 19, 2023.