JRo’s Notes: Alphabet Q3:2024 Earnings

Alphabet Q3:2024 Earnings:

Alphabet’s third quarter 2024 revenue increased 15% (or 16% constant currency), its operating margins expanded 450 basis points from 27.8% to 32.3%, and diluted EPS grew 37% from the same period in the prior year. The margin improvement was driven largely by Alphabet’s “reengineered cost structure” (phrasing used by Anat Ashkenazi as this was her first earnings call as Alphabet’s new CFO).

The highlight of the call for me was Anat implying that she is going to “accelerate” efforts (and “push further”) to cut costs to fund Ai growth. She said this is “one of her key priorities.”

She said, “As we look forward, we are working to balance our investments in AI and other growth areas with the cost discipline needed to fund those activities…while we have a strong balance sheet to be able to support these investments, we will be looking for efficiencies so that we can fund innovation in priority areas. Sundar, Ruth and our leadership team started an important work to reengineer our cost structure, including efforts such as optimizing our head count growth, our physical footprint, improving the efficiencies of our technical infrastructure and streamlining operations across the company through the use of AI. I plan to build on these efforts but also evaluate where we might be able to accelerate work and where we might need to pivot to free up capital for more attractive opportunities.”

She elaborated that, “this is one of my key priorities, is to look across the organization to see what we can do in terms of driving further efficiencies. There’s really good work that was done, started by Ruth, Sundar and the rest of the lead team, to reengineer the cost base. But I think any organization can always push a little further, and I’ll be looking at additional opportunities really across all the elements that I’ve mentioned in my prepared remarks, think not just about the size of the organization but mostly how we operate and how we run the business. And I think when you simplify the organization, Sundar just made a few comments on that, and when we use AI within our own processes and how we get work done, there are some efficiencies or opportunities for efficiencies.”

Breaking down revenue growth by segment, Google Services (including Search, subscriptions, devices, and YouTube ads) increased 13%, Google Cloud growth accelerated to 35%, and Other Bets revenue increased 31% to $388 million (with operating losses shrinking a bit). Within the Google Services Segment, YouTube revenue (including subs and ads) over the trailing twelve months reached $50 billion for the first time.

Free cash flow (FCF) decreased 22% as CapEx increased a whopping 62% year-over-year. The FCF decline was also driven by cash taxes that were deferred (unpaid) from Q3 to Q4 in the prior year period as well as a $3 billion cash payment related to the 2017 EC shopping fine in this quarter.

Despite the decline in FCF, Alphabet still generated a quarterly FCF margin of 20% ($17.627b in FCF on $88.268b in revenue). Alphabet also generated a trailing twelve month return on equity (ROE) of 32% and a return on invested capital (ROIC) of 21%. These growth, margin, and return metrics are truly elite for a company of such massive size in the depths of a heavy investment cycle (see the 62% increase in CapEx) into Ai infrastructure and tools. (And I’m hopeful the new CFO will help to find ways to sustain topline growth while improving margins and ROICs even further despite Ai investments and the related depreciation expense).

Alphabet is using its massive balance sheet and FCFs to return capital to shareholders via a growing dividend and share repurchases. The company returned $17.8 billion in the quarter ($15.3 billion as buybacks and $2.5 billion as dividends) and has returned $70 billion over the trailing twelve months.

I also appreciated the detail Anat provided regarding what they are spending the CapEx on and what to expect for CapEx growth in 2025.

She said, “As you saw in the quarter, we invested $13 billion in CapEx across the company. And as you think about it, it really is divided into 2 categories. One is our technical infrastructure, and that’s the majority of that $13 billion. And the other one goes into areas such as facilities, the bets and other areas across the company. Within TI, we have investments in servers, which includes both TPUs and GPUs. And then the second categories are data centers and networking equipment. This quarter, approximately 60% of that investments in technical infrastructure went towards servers and about 40% towards data center and networking equipment. And as you think about them, we offer both GPUs and TPUs, both internally and to our customers. So we have choices and options based on what our customer needs and what our internal needs are. And as you think about the next quarter and going into next year, as I mentioned in my prepared remarks, we will be investing in Q4 at approximately the same level of what we’ve invested in Q3, approximately $13 billion. And as we think into 2025, we do see an increase coming in 2025, and we will provide more color on that on the Q4 call, likely not the same percent step-up that we saw between ’23 and ’24 but additional increase.”

I want to wax poetically for the next two paragraphs: Mega-cap tech companies like Alphabet, Amazon (see note already published on the boards), Meta, and Microsoft are positioned to win in the Ai world because they provide the crucial foundational infrastructure layer (and platform layer) with their global (and growing) network of datacenters, their core infrastructure cloud platforms (in Google Cloud, AWS, and Azure), and their custom Ai semiconductors (accelerators), but also because they have the most capital, the most users, and therefore the most data that can be used to train ever increasingly complex generative Ai models. These company’s products extend from the enterprise to the consumer and that creates both cost and revenue synergies that competing companies just don’t have and won’t be able to replicate (in my opinion) because of almost impossibly high barriers to entry created by the hundreds of billions in capital and decades it would take to replicate their technological and computing power and infrastructure, as well as consumer branded products that have literally changed the way we work and live (Google changed the way we search for info and learn, Amazon changed the way we shop, Meta changed the way we communicate and socialize, and Microsoft changed the way we compute).

I think it’s a forgone conclusion that the aforementioned companies (and a few other key Ai infrastructure providers like Nvidia) are winning (and will win) the infrastructure layer of the Ai stack (and the infrastructure part of this Ai buildout cycle), but I also think these companies will be leading providers of Ai applications (apps) that will live in and sit on top of their infrastructure/platform layers because as mentioned before, they have the capital (rock solid balance sheets plus insane FCF generation), the users, and the data to create Ai apps that their users want. To give an idea of just how many users Alphabet has (and consequently how much user data), it has 7 products with at least 2 billion monthly users, and all 7 products are currently using/offering Alphabet’s generative Ai model Gemini. And just as we discussed in the Amazon note, Alphabet is using its own Ai tools internally to cut costs and improve efficiency and productivity. It’s still early days yet more than ¼ of all new code written at Google is generated by Ai and then reviewed and accepted by human engineers. It’s hard for me to wrap my head around just how much progress on internal efficiencies/productivity these leading providers of Ai tools will be able to make over the next 5 to 10 years. The future is here and no one has any idea what it entails given the speed of development in these Ai models.

Alphabet CEO Sundar Pichai opened the earnings call talking about how the company is well positioned across the full Ai stack: “We are uniquely positioned to lead in the era of AI because of our differentiated full stack approach to AI innovation, and we are now seeing this operate at scale. It has 3 components: first, a robust AI infrastructure that includes data centers, chips and a global fiber network; second, world-class research teams who are advancing our work with deep technical AI research and who are also building the models that power our efforts; and third, a broad global reach through products and platforms that touch billions of people and customers around the world, creating a virtuous cycle. Let me quickly touch on each of these. We continue to invest in state-of-the-art infrastructure to support our AI efforts from the U.S. to Thailand to Uruguay. We are also making bold clean energy investments, including the world’s first corporate agreement to purchase nuclear energy from multiple small modular reactors, which will enable up to 500 megawatts of new 24/7 carbon-free power. We are also doing important work inside our data centers to drive efficiencies while making significant hardware and model improvements. For example, we shared that since we first began testing AI Overviews, we have lowered machine cost per query significantly. In 18 months, we reduced cost by more than 90% for these queries through hardware, engineering and technical breakthroughs while doubling the size of our custom Gemini model. And of course, we use and offer our customers a range of AI accelerator options, including multiple classes of NVIDIA GPUs and our own custom-built TPUs. We are now on the sixth generation of TPUs known as Trillium and continue to drive efficiencies and better performance with them. Turning to research. Our team at Google DeepMind continues to drive our leadership. Let me take a moment to congratulate Demis Hassabis and John Jumper on winning the Nobel Prize in Chemistry for their work on AlphaFold. This is an extraordinary achievement and underscores the incredible talent we have and how critical our world-leading research is to the modern AI revolution and to our future progress. Also, congratulations to Geoff Hinton, who spent over a decade here on winning the Nobel Prize in Physics. Our research teams also drive our industry-leading Gemini model capabilities, including long context understanding, multimodality and agentive capabilities. By any measure, token volume, API calls, consumer usage, business adoption, usage of the Gemini models is in a period of dramatic growth. And our teams are actively working on performance improvements and new capabilities for our range of models. Stay tuned. And they’re building out experiences where AI can see and reason about world around you, Project Astra is a glimpse of that future. We are working to ship experiences like this as early as 2025. We then work to bring those advances to consumers and businesses. Today, all 7 of our products and platforms with more than 2 billion monthly users use Gemini models. That includes the latest product to surpass the 2 billion user milestone Google Maps. Beyond Google’s own platforms, following strong demand, we are making Gemini even more broadly available to developers. Today, we shared that Gemini is now available on GitHub Copilot with more to come.”

In Search, Alphabet’s largest and most profitable business (with a 40% operating margin in the quarter), Ai Overviews has been launched in 100 new countries and is now reaching more than 1 billion monthly users. Sundar said, “This leads to users coming to Search more often for more of their information needs, driving additional Search queries…People are asking longer and more complex questions and exploring a wider range of websites. What’s particularly exciting is that this growth actually increases over time as people learn that Google can answer more of their questions. The integration of ads within AI Overviews is also performing well, helping people connect with businesses as they search.” And the Head of Google Services said, “As gen AI expands what’s possible, we continue to see a significant opportunity in Search.”

YouTube is a one-of-a-kind media asset and is gaining even more relevance in our influencer-based media and social landscape (ex: over 70 billion YouTube Shorts are watched every single day).
The Head of Google Services said, “On YouTube, we remain focused on building a platform that enables creators to thrive and unlocking a whole new world of creativity with AI. Creators are at the heart of the YouTube ecosystem, and the content they are making is driving robust growth in watch time across the platform. We’re also using AI to greatly improve recommendations on YouTube. Driven by Gemini, our large language models have a deeper understanding of video content and viewers’ preferences. As a result, they can recommend more relevant, fresher and personalized content to the viewer. Short-form creation continues to thrive on YouTube. Shorts monetization improved again this quarter, and we continued to significantly close the gap with in-stream video, particularly in the U.S. and other more highly monetizing markets. Of all the channels uploading to YouTube each month, 70% are uploading Shorts. And we recently announced a top requested feature, the ability to upload shorts up to 3 minutes long. Also, advertisers can now book first position on Shorts blocks in close to 40 markets. We’re unlocking more opportunities in the living room. Our momentum here continues as we maintain our status as the #1 streamer in the U.S. according to Nielsen. This is driven by the strength of our creators such as [ Michelle Khare ] and Rhett & Link, who are increasingly crafting experiences designed specifically for the big screen. And it’s paying off. The number of creators making the majority of the YouTube revenue and TV screens is up more than 30% year-on-year. YouTube is becoming a premier destination for sports watching. People come for the game and stay for the commentary and around the game content from creators like [ Evelyn Gonzalez ], Adam W and Brad Coleman. During the Olympics, content from Paris 2024 had over 12 billion views on YouTube. More than 850 million unique viewers watched over 40 billion minutes of content with 35% on their TV screens. And recently, we kicked off our second season of NFL Sunday Ticket on YouTube TV, which continues to receive a positive reception from advertisers or partners at the NFL and fans. We have continued to invest in our product experience with improvements to multiview and deeper integrations for fantasy football fans.”

Moving to Google Cloud, as mentioned, it grew revenue 35% year-over-year and it is taking market share. The rapid scaling and operating leverage allowed Google Cloud to generate an operating margin of 17% (up from an operating margin of only 3% in the same period last year). I think Google Cloud can continue to grow at or above 20% for the next five years, and I think it’s still under-earning and has room to dramatically improve the operating margin further (its operating margin is still significantly less than operating margins at AWS and Azure).

Moving on to Other Bets, Waymo is the clear commercial leader in autonomous ride-sharing at this point. Pichai says, “I want to highlight Waymo, the biggest part of our portfolio. Waymo is now a clear technical leader within the autonomous vehicle industry and creating a growing commercial opportunity. Over the years, Waymo has been infusing cutting-edge AI into its work. Now each week, Waymo is driving more than 1 million fully autonomous miles and serves over 150,000 paid rides, the first time any AV company has reached this kind of mainstream use. Through its expanded network and operations partnership with Uber in Austin and Atlanta, plus a new multiyear partnership with Hyundai, Waymo will bring fully autonomous driving to more people and places.”

Pichai continued: “it’s been an exciting year, both in the Phoenix market and in San Francisco. We’ve definitely scaled and particularly scale paid rights and definitely surprised us on the positive in terms of how much consumers are loving the experience from a safety standpoint, privacy standpoint, reliability standpoint, et cetera. So I think all of that has been on the positive side. And obviously, the product will continue to improve. So for us, we are mainly focused on each city as we go. The pace at which we can now do an additional city gets easier. So we are definitely accelerating that way. That’s why we — you’ve seen us move into L.A. We’re also striking partnerships in newer and unique ways, hence the Uber partnership and expansion to Austin and Atlanta. And we have more options where we are looking at the Driven by Waymo model with other network partners, fleet managers, et cetera.”

My thesis: Alphabet has $64 billion in net cash, which is equal to about 15% of its total assets and 3% of its market cap. Its legacy business (Search) is arguably the greatest business in the history of the world. Yes, Search is under intense regulatory scrutiny and Google may be forced to remove Safari as the preferred Search tool on Apple and Android devices, but Alphabet also has seven products with 2 billion monthly users, the equivalent of its own Netflix (with YouTube), the third largest hyperscale cloud company in the world in Google Cloud (which is arguably the most advanced Ai cloud platform) that is taking market share with possibly 1000 basis points (or more) of operating margin expansion potential, the (currently) leading autonomous driving platform in Waymo, and a host of Other Bets (moon shots) that provide upside optionality. Yet the stock seems hated, trading at a NTM P/E of only 21x (which is a discount to the S&P 500 that’s trading at 22x according to FactSet). And on two-year out consensus estimates, Alphabet trades at less than 18x.

Official release: https://abc.xyz/assets/71/a5/78197a7540c987f13d247728a371/2024q3-alphabet-earnings-release.pdf