Transcripts
Meta Platforms $META Q1 2023 Earnings Call Transcript

Meta Platforms $META Q1 2023 Earnings Call Transcript

Meta Platforms $META Q1 2023 Earnings Call. Read the transcript here.

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Dave (00:07):

Good afternoon. My name is Dave, and I will be your conference operator today. At this time, I would like to welcome everyone to the Meta first quarter earnings conference call.

(00:16)
All lines have been placed on mute to prevent any background noise. After the speaker’s remarks, there will be a question and answer session. If you would like to ask a question, please press one, then the number four on your telephone key pad.

(00:29)
This call will be recorded. Thank you very much.

(00:32)
Ms. Deborah Crawford, Meta’s Vice President of Investor Relations, you may begin.

Deborah Crawford (00:38):

Thank you.

(00:38)
Good afternoon, and welcome to Meta Platforms First quarter 2023 earnings conference call.

(00:44)
Joining me today to discuss our results are Mark Zuckerberg, CEO, and Susan Li, CFO. Before we get started, I would like to take this opportunity to remind you that our remarks today will include forward-looking statements. Actual results may differ materially from those contemplated by these forward-looking statements.

(01:03)
Factors that could cause these results to differ materially are set forth in today’s press release and in our annual report on Form 10-K filed with the SEC.

(01:12)
Any forward-looking statements that we make on this call are based on assumptions as of today, and we undertake no obligation to update these statements as a result of new information or future events.

(01:23)
During this call, we may present both GAAP and non-GAAP financial measures. A reconciliation of GAAP to non-GAAP measures is included in today’s earnings press release.

(01:32)
The press release and an accompanying investor presentation are available on our website at investor.fb.com. And now I’d like to turn the call over to Mark.

Mark Zuckerberg (01:42):

All right, thanks Deborah, and thanks everyone for joining. This was a good quarter, and we’re seeing growing momentum in our products and business. Our community reached the milestone that now more than 3 billion people use at least one of our apps each day.

(01:58)
Facebook also reached the milestone of 200 million daily actives in the US and Canada, after last quarter reaching 2 billion daily actives worldwide.

(02:07)
Now, in a moment, I’ll talk more about the results in our business and the opportunities that I’m excited about. But first I want to share an update on our efficiency work.

(02:15)
The goals of our efficiency work are to make us a stronger technology company that builds better products faster, and to improve our financial performance to give us the space in a difficult environment to execute our ambitious long- term vision.

(02:31)
When we started this work last year, our business wasn’t performing as well as I wanted, but now we’re increasingly doing this work from a position of strength. Even as our financial position improves, I continue to believe that slowing hiring, flattening our management structure, increasing the percent of our company that is technical, and more rigorously prioritizing projects will improve the speed and quality of our work.

(02:57)
I also believe that a stronger financial position will enable us to weather a volatile environment, while remaining focused on our longer term priorities.

(03:06)
So far, we’ve gone through two of the three waves of restructuring and layoffs that we have planned for this year in our recruiting and our technical groups. In May, we’re going to carry out our third wave across our business groups.

(03:19)
And this has been a difficult process, but after this is done, I think we’re going to have a much more stable environment for our employees. And then for the rest of the year, I expect us to focus on improving our distributed work model, delivering AI tools to improve productivity, and removing unnecessary processes across the company.

(03:39)
Now, moving on to our products and business, we’re seeing strong engagement growth across our apps and good progress on monetization efficiency, which combine to drive good business results. Reels continues to grow quickly on both Facebook and Instagram. Reels also continue to become more social, with people re-sharing Reels more than 2 billion times every day, doubling over the last six months.

(04:05)
Reels are also increasing overall app engagement, and we believe that we’re gaining share in short form video too.

(04:13)
Now, a key theme that I want to discuss today is AI.

(04:16)
I’ve emphasized for a number of these calls now that there are two major technological waves driving our roadmap, a huge AI wave today and a building metaverse wave for the future. And our AI work comes in two main areas. First, the massive recommendations and ranking infrastructure that powers all of our products, from feed to Reels to our ad system, to our integrity systems that we’ve been working on for many, many years.

(04:46)
And second, the new generative foundation models that are enabling entirely new classes of products and experiences.

(04:55)
Our investment in recommendations and ranking systems has driven a lot of the results that we’re seeing today across our discovery engine Reels and ads. Along with surfacing content from friends and family, now more than 20% of content in your Facebook and Instagram feeds are recommended by AI from people, groups, or accounts that you don’t follow.

(05:15)
Across all of Instagram, that’s about 40% of the content that you see. Since we launched Reels, AI recommendations have driven a more than 24% increase in time spent on Instagram. Our AI work is also improving monetization. Reel’s monetization efficiency is up over 30% on Instagram and over 40% on Facebook, quarter over quarter.

(05:40)
Daily revenue from Advantage+ Shopping Campaigns is up seven X in the last six months. Our work to build out business messaging as the next pillar of our business is making progress too.

(05:51)
I shared last quarter that click to message ads reached a 10 billion revenue run rate, and since then, the number of businesses using our other business messaging service paid messaging on WhatsApp has grown by 40% quarter over quarter.

(06:06)
Our success here depends on delivering results for other businesses, and at our scale that can have macroeconomic effects. We recently did a study with economists at US Berkeley to understand the impact that our services make, and they concluded that every dollar spent on our ads drives on average $3 and 31 cents in revenues for our advertisers in the US.

(06:29)
That means over $400 billion in economic activity annually is linked to supply chains relying on our platforms, supporting more than 3 million jobs. Beyond recommendations, the other major focus of our AI work is foundation models to enable a lot of new use cases, including generative AI.

(06:50)
That’s been a pretty amazing year of progress on this front, and the work happening now is going to impact every single one of our apps and services. And I’m incredibly excited to ship more of the things that we’re building over the coming months.

(07:04)
Now, I want to share a little bit about our approach and what you can expect to see from us, and the specifics are going to come into focus as we ship more of these things. So these are just themes for now.

(07:14)
But first, for our products, we’re always focused on connection and expression, and I expect that our AI work will reflect that. I think that there’s an opportunity to introduce AI agents to billions of people in ways that will be useful and meaningful. We’re exploring chat experiences and WhatsApp and Messenger, visual creation tools for posts and Facebook and Instagram and ads. Overtime, video and multimodal experiences as well.

(07:41)
I expect that these tools will be valuable for everyone, from regular people to creators to businesses. For example, I expect that a lot of interest in AI agents for business messaging and customer support will come once we nail that experience.

(07:56)
Now, over time, this will extend to our work on the Metaverse two, where people will much more easily be able to create avatars, objects, worlds, and code to tie all them together.

(08:07)
All right, next, let’s talk about the technology platform to enable this. Now, right now, most of the companies that are training large language models have business models that lead them to a closed approach to development. And I think that there’s an important opportunity in the industry to help create an open ecosystem.

(08:25)
And if we can help be a part of this, then much of the industry I think will standardize on using these open tools and help improve them further. So this will make it easier for other companies to integrate with our products and platforms as we enable more integrations, and that will help our products stay at the leading edge as well.

(08:47)
Our approach to AI and our infrastructure has always been fairly open. We open source many of our state-of-the-art models so people can experiment and build with them. This quarter we released our LLaMA, LLM, to researchers. It has 65 billion parameters but outperforms larger models, and has proven quite popular.

(09:08)
We’ve also open sourced three other groundbreaking visual models along with their training data and model weights segment, Anything, Dino V2, and our animated drawings tool. And we’ve gotten some positive feedback on all of those as well.

(09:23)
Now finally, let’s talk about AI infrastructure and the CapEx. This has been a major investment for us. A couple of years ago, I asked our infra teams to put together ambitious plans to build out enough capacity to support not only our existing products, but also enough buffer capacity for major new products as well. And this has been the main driver of our increased CapEx spending over the past couple of years.

(09:48)
Now, at this point, we are no longer behind in building out our AI infrastructure, and to the contrary, we now have the capacity to do leading work in this space at scale.

(09:59)
As these new models and use cases continue scaling, we’re going to need to continue investing in infrastructure, although we’ll have a better idea of the trajectory of that investment later in the year once we can gauge usage of some of the new products we’ll launch.

(10:16)
Now, beyond AI, the other major technology wave that we’re focused on is the Metaverse. A narrative has developed that we’re somehow moving away from focusing on the Metaverse vision, so I just want to say upfront that that’s not accurate. We’ve been focusing on both AI and the Metaverse for years now, and we will continue to focus on both.

(10:36)
The two areas are also related. Breakthrough in computer vision was what enabled us to ship the first standalone VR device. Mixed reality is built on a stack of AI technologies for understanding the physical world and blending it with digital objects.

(10:52)
Being able to procedurally generate worlds will be important for delivering compelling experiences at scale. And our vision for AR glasses involves an AI-centric operating system that we think will be the basis for the next generation of computing.

(11:08)
Metaverse technologies will also help deliver AI as well. For example, embodying AI agents will take advantage of the deep investment that we’ve made in avatars over the last several years.

(11:21)
Building the Metaverse is a long-term project, but the rationale for it remains the same, and we remain committed to it. Now in the near term, we’ve reached a few milestones that I think are worth calling out. More than a billion meta avatars have now been created. Since last year, the number of titles in the Quest store with at least $25 million in revenue has doubled, and more than half of Quest Daily actives now spend more than an hour using their device.

(11:48)
The next milestone is that we’re gearing up to launch our next generation consumer virtual and mixed reality device later this year. We launched Quest 2 almost three years ago at this point. It was a very big step forward for VR, and I’m really excited to show the world all of the improvements and new technology that we have developed since then at a price point that will be accessible for lots of people.

(12:12)
All right, so that’s what I wanted to cover today. We’re seeing good momentum in our products and business. We have incredibly exciting opportunities ahead in our Family of Apps, AI and the metaverse. I’m confident that our efficiency work will improve our ability to execute on all of this.

(12:29)
As always, I’m grateful for our teams, for all of your work. I know that this has been a challenging period, but I’m proud of the work that you’re doing. And I’m also grateful for all of you for being on this journey with us.

(12:41)
And now over to Susan.

Susan Li (12:44):

Thanks, Mark. And good afternoon, everyone. Let’s begin with our consolidated results. All comparisons are on a year-over-year basis, unless otherwise noted.

(12:54)
Q1 total revenue was $28.6 billion, up 3% or 6% on a constant currency basis. Had foreign exchange rates remained constant with Q1 of last year, total revenue would’ve been about $816 million higher.

(13:14)
Q1 total expenses were $21.4 billion, up 10% compared to last year. In terms of the specific line items, cost of revenue increased 2%, driven by infrastructure related costs that were partially offset by lower reality labs costs of goods sold.

(13:34)
R&D increased 22%, driven primarily by restructuring charges related to facilities consolidation and severance expenses, and headcount related costs from our reality labs and Family of Apps segments.

(13:48)
Marketing and sales decreased 8% due mainly to lower marketing spend and headcount related expenses. And GNA increased 22%, due primarily to restructuring charges related to severance and facilities consolidation expenses and legal related expenses.

(14:06)
We ended the first quarter with over 77,100 employees, down 11% from the fourth quarter, as our reported headcount no longer includes substantially all of the employees impacted by the November layoff. Employees that were impacted by layoffs in March are still included in the first quarter headcount.

(14:26)
First quarter operating income was $7.2 billion, representing a 25% operating margin. Our tax rate for the quarter was 22%. Net income was $5.7 billion or $2 and 20 cents per share. Capital expenditures, including principal payments on finance leases, were $7.1 billion, driven by investments in data centers, servers, and network infrastructure.

(14:55)
Free cash flow was $6.9 billion, and we repurchased $9. 2 billion of our class A common stock in the first quarter. We ended the quarter with $37.4 billion in cash and marketable securities.

(15:11)
Moving now to our segment results. I’ll begin with our Family of Apps segment. Our community across the Family of Apps continues to grow. For the first time, we surpassed 3 billion people using at least one of our Family of Apps on a daily basis in March, and approximately 3.8 billion people use at least one on a monthly basis.

(15:33)
Facebook continues to grow globally as well, and engagement remains strong, with DAU and MAU growing sequentially across all regions in the first quarter.

(15:43)
Facebook daily active users were 2.04 billion, up 4% or 77 million compared to last year. DAUs represented approximately 68% of the 2.99 billion monthly active users in March.

Susan Li (16:01):

… grew by $53 million or 2% compared to last year. Q1 total family of apps revenue was $28.3 billion, up 4% year-over-year, and Q1 family of apps ad revenue was $28.1 billion, up 4% or 7% on a constant currency basis. Within ad revenue, the online commerce vertical was the largest contributor to year-over-year growth, followed by healthcare and entertainment and media. Online commerce benefited from strong spend among advertisers in China, reaching customers in other markets. However, other verticals remain challenged, with financial services and technology verticals being the largest negative contributors to year-over-year growth.

(16:50)
On a user geography basis, ad revenue growth was strongest in rest of world at 9%, followed by North America and Asia Pacific at 6% and 4% respectively. Europe declined 1%. Foreign currency remained a headwind to advertising revenue growth in all international regions. In Q1, the total number of ad impressions served across our services increased 26%, and the average price per ad decreased 17%. Impression growth was primarily driven by Asia Pacific and rest of world. The year-over-year decline in pricing was primarily driven by strong impression growth, especially from lower monetizing surfaces and regions, foreign currency depreciation, and lower advertising demand. While overall pricing remains under pressure from these factors, we believe our ongoing improvements to ad targeting and measurement are continuing to drive improved results for advertisers.

(17:52)
Family of apps other revenue was $205 million in Q1, down 5%, as strong business messaging revenue growth from our WhatsApp business platform was more than offset by a decline in other line items. We continue to direct the majority of our investments toward the development and operation of our family of apps. In Q1, family of apps expenses were $17.1 billion, representing approximately 80% of our overall expenses. Family of apps expenses were up 9% due primarily to restructuring charges and growth and infrastructure related costs. Family of apps operating income was $11.2 billion, representing a 40% operating margin. Within our Reality Labs segment, Q1 revenue was $339 million, down 51% due to Lower Quest 2 sales. Reality Labs expenses were $4.3 billion, up 18% due mostly to employee related costs and restructuring charges. Reality Lab’s operating loss was $4 billion.

(19:03)
Next, I’ll discuss our ongoing monetization work. As I mentioned last quarter, there are two primary levers to increasing monetization; growing supply and demand. On the ad supply side, our foremost focus remains on building engaging experiences for our community, and we’re continuing to make encouraging progress on our product priorities. Our investments in the discovery engine are delivering results. In-Feed recommendations are contributing to engagement, and we’ve seen Reel time become more incremental to overall engagement on our services as we continue to improve our recommendation system. This is an important signal because it demonstrates that people are finding added value from the content we’re helping them discover.

(19:48)
Beyond that, we continue to focus on further narrowing the gap in monetization efficiency or monetization per time between Reels and our more mature surfaces, Feed and Stories. There are structural supply constraints with the Reels format as people view a Reel for a longer time than a piece of Feed or Stories content, which results in fewer opportunities to serve ads in between posts. That will make it likely more challenging to close the monetization efficiency gap than it was with Stories. However, the overall economics of Reels will be determined by a combination of our ability to continue growing monetization per time on Reels and our ability to drive incremental engagement from Reels. As Mark noted, we have seen a 24% increase in overall time spent on Instagram from our ranking improvements since launching Reels globally. We continue to expect that Reels will become neutral to overall revenue by end of this year or early next year.

(20:49)
The other side of monetization is growing advertiser demand. One area of focus is around driving advertiser performance, and we are seeing continued strong conversion growth for advertisers, which we believe, coupled with lower cost per action, is driving higher return on investment. We remain focused on continuing to improve ads ranking and measurement with our ongoing AI investments, while also leveraging AI to power increased automation for advertisers through products like Advantage Plus shopping, which continues to gain adoption and receive positive feedback from advertisers. These investments will help us develop and deploy privacy-enhancing technologies and build new innovative tools that make it easier for businesses to not only find the right audience for their ad, but also optimize and eventually develop their ad creative.

(21:42)
Scaling onsite conversions is another important part of our work, and click to message ads continue to grow and bring incremental demand onto our platform. This format is mostly used by smaller advertisers today in Southeast Asia and Latin America, and one of the exciting opportunities ahead is to expand adoption to larger advertisers in more markets by investing in increased automation and reporting to help businesses more easily manage messages and measure results at scale.

(22:14)
Before turning to our revenue outlook, I’d also like to talk about our operating philosophy given the recent significant changes to our investment plans. We believe increasing our organizational efficiency is vital to our long-term success. This will increase the speed of our execution and agility to ensure that we are constantly innovating for the people who use our services. Narrowing the scope of the projects that we are working on allows us to increase our focus on the highest leverage opportunities for the company, including AI today and the Metaverse longer term. It also enables us to invest in these areas while maintaining a strong financial position.

(22:54)
As we look forward, I also expect that we will modestly evolve our capital structure over time to improve our overall cost of capital. We expect to do so through periodically accessing the debt markets to diversify our funding sources, while still maintaining a positive or neutral net cash balance over time. In addition, we continue to monitor ongoing regulatory developments. We expect the IDPC to issue a decision in May in its previously disclosed inquiry relating to Trans-Atlantic data transfers of Facebook EU-EEA user data, including a suspension order for such transfers and a fine. Our ongoing consultations with policy makers on both sides of the Atlantic continue to indicate that the proposed new EU-US data privacy framework will be fully implemented before the deadline for suspension of such transfers, but we cannot exclude the possibility that it not be completed in time. We will also evaluate whether and to what extent the IDPC decision could otherwise impact our data processing operations even after a new data privacy framework is enforced.

(24:06)
Turning now to the revenue outlook, we expect second quarter 2023 total revenue to be in the range of $29.5 to $32 billion. Our guidance assumes foreign currency headwinds will be less than 1% to year-over-year total revenue growth in the second quarter based on current exchange rates. Turning now to the expense outlook, we anticipate our full year 2023 total expenses will be in the range of $86 to $90 billion, updated from our prior outlook provided in March. This outlook includes $3 to $5 billion of restructuring costs related to facilities consolidation charges and severance and other personnel costs. We continue to expect Reality Labs operating losses to increase year-over-year in 2023.

(24:59)
Turning now to the capex outlook, we expect capital expenditures to be in the range of $30 to $33 billion, unchanged from our prior estimate. This outlook reflects our ongoing build-out of AI capacity to support ads, Feed, and Reels, along with an increased investment in capacity for our generative AI initiatives. Onto tax, absent any changes to US tax law, we expect our full year 2023 tax rate percentage to be around 20%. In closing, Q1 was a solid quarter for our business. Our global community continued to grow. We made important progress on our company priorities and improved the efficiency of our operations while strengthening the financial position of the company, which sets us up well to execute on the opportunities ahead. With that, Dave, let’s open up the call for questions.

Dave (25:57):

Thank you very much. We will now open the lines for a question and answer session. To ask a question, press one followed by the number four on your touch phone. Please pick up your handset before asking your question to ensure clarity. If you’re streaming today’s call, please mute your computer speakers. Your first question comes from line of Brian Novak with Morgan Stanley. Your line is open.

Brian Novak (26:21):

Thanks for taking my questions. I have two, one for Mark, one for Susan. Mark, first one for you is on generative AI and how you think about generative AI and some of the division models, large language models, potentially impacting your long-term advertising business and finding ways to deliver more value for advertisers over the next 2, 3, 5 years; how do you see Gen AI impacting advertising? Then the second one for Susan, just as we’re thinking about hiring expectations for ’24 and beyond, I think there’s been some ink in the press about potential 1% to 2% hiring going forward; can you just talk to us about that a little bit and how does using AI internally factor into your thoughts about long-term hiring? Thanks.

Mark Zuckerberg (27:07):

Yeah, I can start off by taking the generative AI question, although there aren’t that many details that I’m going to share at this point. More of this will come in focus as we start shipping more of these things over the coming months. But I do think that there’s a big opportunity here. You asked specifically about advertisers, but I think it’s going to also help create more engaging experiences, which should create more engagement, and that by itself creates more opportunities for advertisers. But then I think that there’s a bunch of opportunities on the visual side to help advertisers create different creative. We don’t have the tools to do that, over time, eventually making it. So we’ve always strived to just have an advertiser just be able to tell us what their objective is and then have us be able to do as much of the work as possible for them. And now being able to do more of the creative work there ourselves for those who want that, I think could be a very exciting opportunity.

(28:06)
I also think that there’s going to be a very interesting convergence between some of the AI agents and messaging and business messaging, where right now we see a lot of the places where business messaging is most successful are places where a lot of businesses can afford to basically have people answering a lot of questions for people and engaging with them in chat. And obviously once you light up the ability for tens of millions of small businesses to have AI agents acting on their behalf, you’ll have way more businesses that can afford to have someone engaging in chat with customers, so I think that that could be a pretty big opportunity too. So those are just a few of the things that we’re looking at. I think this is very broad. Like I said, I think this is literally going to touch every single one of our products and services in multiple ways, and this is just a very big wave and new set of technologies that’s available and we’re working on it across the whole company.

Susan Li (29:07):

Hi Brian, it’s Susan. Thanks for the question. You were asking about the 1% to 2% headcount growth stat that’s been out there, and I thought it was worth clarifying. So that comes from something Mark mentioned in a recent internal employee Q&A, that he had expected company headcount to increase only 1% to 2% year-over-year, and I want to clarify that Mark was actually speaking to employees about headcount budgets that have already been allocated. What we’ve also said previously is we have been in a broad-based hiring freeze for the last half year, and as we complete our layoffs in April and May, we will resume hiring and we would expect headcount growth in excess of 1% to 2% in 2024 as a result, as we ramp up those recruiting pipelines.

(29:53)
But our long-term focus is very much on efficiency, and as hiring resumes, you’ll find the biggest areas that we are hiring in will be to support priority areas like generative AI, ads, infrastructure, Reality Labs, some of the areas that we’ve been talking about. And you also asked about using AI internally and how that factors into our thoughts on long-term hiring. We certainly don’t have enough visibility yet into how AI will make our workforce more productive, but it’s something we’re excited about, and I think we will have more clarity on that as more tools begin getting developed to enhance employee productivity across the industry.

Dave (30:34):

Your next question comes from line of Eric Sheridan with Goldman Sachs. Your line is open.

Eric Sheridan (30:40):

Thanks so much for taking my questions. Maybe two, if I can. Mark, I was intrigued by your comment about open source and open systems with respect to AI. Obviously we’re coming off of Web 2.0 and mobile where there were a lot more walled gardens and ecosystems; can you talk a little bit about what you might want to try to do, either from a priority or an investment standpoint, to be a driver of more open-ended systems in AI compared to what we saw with Web 2.0? And then maybe for Susan, you introduced the concept last quarter about revisiting your data center architecture over the medium to long term; is there any update there for us in terms of how to think about AI as a driver of data center architecture medium to long term, and what that might mean for capital intensity? Thanks so much.

Mark Zuckerberg (31:27):

Yeah, I can take the first one. I think that there’s an important distinction between the products we offer and a lot of the technical infrastructure, especially the software that we write to support that. And historically, whether it’s the Open Compute project that we’ve done or just open sourcing a lot of the infrastructure that we’ve built, we’ve historically open sourced a lot of that infrastructure, even though the products themselves are obviously… We haven’t open sourced the code for our core products or

Mark Zuckerberg (32:00):

Or anything like that. And the reason I think why we do this is that, unlike some of the other companies in the space, we’re not selling a cloud computing service where we try to keep the different software infrastructure that we’re building proprietary. For us, it’s way better if the industry standardizes on the basic tools that we’re using and therefore we can benefit from the improvements that others make and other’s use of those tools can, in some cases like Open Compute, drive down the costs of those things which make our business more efficient too.

(32:38)
So, I think to some degree we’re just playing a different game on the infrastructure than companies like Google or Microsoft or Amazon, and that creates different incentives for us. So, overall, I think that that’s going to lead us to do more work in terms of open sourcing some of the lower level models and tools. But of course, a lot of the product work itself is going to be specific and integrated with the things that we do. So, it’s not that everything we do is going to be open. Obviously, a bunch of this needs to be developed in a way that creates unique value for our products. But I think in terms of the basic models, I would expect us to be pushing and helping to build out an open ecosystem here which I think is something that’s going to be important.

Susan Li (33:25):

Hi, Eric. So, I think your question had two parts. The first was an update on the data center architecture that we announced last quarter and we’re progressing with construction there, but the new data centers that we’re building are intended really for future year capacity, so they won’t come online for a few years. So we don’t have too much more to share there except that that work is ongoing. And the second part of your question was really, I think, about how AI might drive capital intensity over the next few years. So you can really think about our CapEx investment as having three broad buckets. The first, we’ve talked about before, non-AI compute needs. We do have ongoing general compute and storage needs to support the existing business, but this is an area where we’ve become much more efficient in terms of capital intensity and are very much focused on continuing to do so over time.

(34:19)
The second area is in our core AI investments which is really most of our AI investment today, and that’s supporting the building of the discovery engine, ranking unconnected organic content, ranking ads. And we’re focused on measuring the return of those investments and making sure that we feel good about the ROI of our spend there, and that really will drive our future plans in terms of that core AI spend. And then the third bucket is really around CapEx investments now to support Gen AI. And this is an emerging opportunity for us. We’re still in the beginning stages of understanding the various applications and the possible use cases.

(34:57)
And I do think this may represent a significant investment opportunity for us that is earlier on the return curve relative to some of the other AI work that we’ve done. And it’s a little too early to say how this is going to impact our overall capital intensity in the near term. So to the extent that we spend more on CapEx in the near future, I expect it mostly to be to power this work. But I want to emphasize that we remain focused overall on striking the right balance between building out the AI capacity we need and being efficient with our CapEx spend.

Dave (35:30):

Your next question comes from the line of Mark Schmulik with Bernstein. Your line is open.

Mark Schmulik (35:36):

Yes, I have a couple of questions. Mark, this one’s a bit more philosophical, but if we compare where META is today, kind of pre-IDFA cookie application type of world, how do you see the relative competitive position in digital advertising in light of all of these technical integrations and AI tools? Because I think the prevailing view is that privacy would level the playing field, but it certainly doesn’t seem that way. And then second for Susan, I certainly appreciate the outlook on the revenue guidance, but in light of some of the commentary we’ve been hearing about US consumers trading down, is there any additional color you can share about where you’re seeing strengths and weaknesses effectively quarter to date and beyond? Thank you.

Susan Li (36:16):

Thanks, Mark, I can go ahead and take both of those. So your first question was about the post ATT landscape and how we’re positioned in terms of our ads business. We’ve talked really a great deal of course about this over the last few years. We’re making progress certainly in mitigating the direct impact from ATT’s platform changes. But this is really, I think, just the reality of the online advertising environment that we’re in now. And we’ve invested across not only the direct mitigations that we’ve talked about in the past, including things like conversions API, but really I think now we’re focused on improving ad performance in the current signals landscape with our investments both in increasing the volume of ads with onsite objectives and then second of all, with our AI investments that have really, I think, enhanced the performance of our ads as well as enabled us to introduce new tools and features for advertisers.

(37:18)
So I think we’re quite well positioned here in terms of onsite conversions. We have a lot of offerings that have been growing very well for us. I think we’ve talked a lot about click to messaging ads and what that has meant in terms of driving growth for our business and new business opportunities. Other formats that have been, I think, performing well in terms of onsite conversions are lead ads, shops ads, so there are different ad formats that we’re working on there. And then, we’ve just really been investing in using AI for a long time to improve our ad systems, including ranking, to improve our modeling and measurement and to, again, support the introduction of new AI powered tools and products. So I think we feel quite good about our relative position. Again, this is just work that we’ve been doing for a long time that, I think, in conjunction with seeing some stabilization in the macro environment has enabled us to see that work pay off.

(38:16)
And then, your second question was about strengths and weaknesses in the Q1 revenue performance as well as in our outlook. In terms of the Q1 revenue performance and the acceleration relative to Q4, we certainly saw stronger demand including the impact of lapping the Ukraine war which began in Q1 of 2022. And in particular, we saw acceleration among advertisers in China targeting users in other markets which we believe was due in part to dropping shipping costs and easing COVID lockdowns for those advertisers. And then you’ve seen FX play a part there as well. Looking forward to Q2 and the back half of the year, it’s certainly an easier compare there as there are tailwinds to year-over-year growth coming from lapping a weaker demand period and then moving into the first full quarter in Q2 without Russia revenue in terms of the comparison relative to Q2 2022. And we certainly expect that currency is also going to be less of a headwind than it was in the first quarter.

(39:24)
With that said, there’s a broad range of expectations captured in our Q2 outlook and it reflects that we feel it remains a volatile macro environment. The market has absorbed a lot of new developments over the last year with inflation, higher interest rates, banking instability, et cetera. And it’s hard to have perfect visibility on how those dynamics will impact the broader economy and specifically the advertising markets for Q2 and for the rest of the year. It also continues to be a challenging regulatory environment. So that’s something that we’re continuing to monitor closely. But on the other hand, we’ve been pleased with the performance we’re delivering for advertisers and how those investments have paid off. Core engagement trends remain strong and Reels is a revenue headwind today that we expect will become revenue neutral by the end of the year early next year. Again, we expect FX will be a tailwind. And again, we’re lapping relatively softer comps. So lots of puts and takes as we look into Q2 and beyond.

Dave (40:29):

Your next question comes from the line of Doug Anmuth with JP Morgan. Your line is open.

Dough Anmuth (40:35):

Thanks for taking questions. Susan, you’ve talked about the goal of building the muscle for long-term financial discipline. Just given the restructuring that we’ve seen across the business so far, how far along are you in building this muscle and what gives you the confidence that it’s a durable and sustainable long term, even in a better macro environment, especially given all the work ahead on AI and the metaverse?

Susan Li (41:03):

Thanks, Doug. I think there are a couple components to this. A lot of this efficiency work that we’ve been undertaking and especially this year, is driven not by solely financial imperative, but really with the focus of increasing operational efficiency. So that’s been, I think, one of the foremost goals and a lot of the work has been architected around that. And that really includes more carefully scrutinizing roadmaps, winding down projects that are no longer at the top of our priority list, reprioritizing investments. That’s really a muscle that I think we have spent a lot of time building over the last half year. And I expect that we will be carrying that discipline into the way that we assess our product roadmaps going forward. Similarly, I think a lot of the work that we’ve done around increasing operational efficiency, around making sure that we feel good about management spans and layers, that work, I think, is also in service of making us a company that can build more and ship faster.

(42:12)
And we would expect to continue to make sure that we think our organizational posture is really in service, again, of building and shipping product. And as we move forward, including out of the layoffs that we’ve been implementing in the direct restructuring work, we’re going to continue focusing on efficiency work, including in other areas like helping developers build and ship quality products faster. We’re going to be investing in tooling where we can to increase the velocity of product development and we’ll continue streamlining cross-functional or processes that might tax the development process or slow us down and make sure that we’re really focused on also increasing the quality and frequency of collaborative and in-person time to build relationships across the organization and get things done faster. So I expect this to all be very much ongoing for us in the years to come.

Dave (43:14):

Your next question comes from line of Justin Post with Bank of America Merrill Lynch. Your line is open.

Justin Post (43:21):

Thank you. This could be for Susan or Mark. I think really interesting stat on Instagram time you gave, but just wondering how you characterize the health of the Facebook user base and usage on the site. Obviously DAUs went up to 68% this quarter. I think Asia was really strong, but what are you seeing there and is there a catch-up here where the Reels content could start really helping Facebook time spent as well as you saw with Instagram? But just stepping out, I think there’s an narrative that that usage could be flat or down. I’m just wondering what your thoughts are and what you’re seeing on the core Facebook. Thank you.

Susan Li (44:01):

Thanks, Justin. In terms of core Facebook user growth, we’ve been pleased with growth of the community and the engagement trends that we’ve been seeing. In particular, I think in Q1, DAU growth benefited from strong product execution, but I should also note that Q1 is a seasonally strong engagement quarter for us. So that has some benefit in terms of quarter-over-quarter growth. You mentioned whether the work in Reels is driving engagement in Facebook. And what I would say there is that more broadly, the discovery engine work for us and the investments we’ve made, ranking unconnected content is expansive beyond Instagram and I think is certainly a part of what is also driving growth on Facebook as well.

Dave (44:52):

Your next question comes from line of Youssef Squali with Truist Security. Your line is open.

Youssef Squali (44:58):

Great, thank you. I have two questions. I guess relative to OPEX guides from Q3 of last year, the new guide at the midpoint by something like 10 to $15 billion lower adjusted for the restructuring costs. How does this impact your expectations for growth well beyond 2023? I’m not talking about this year, I’m just talking about the next say two to three years. Trying to get a sense of, is it all about efficiency or are we potentially cutting into the bone? And then on the regulatory front, can you just help explain how changes to the transatlantic data transfer rules may impact your European business as it goes into effect? Just trying to get a sense if we have potentially an IDFA situation with a signal loss here again. Thank you.

Susan Li (45:49):

Youssef, thank you. So for your first question, how much has the total expense guidance coming down, especially since we issued our first passive guidance in Q3 last year, how has that downward trend impacted our expectations beyond 2022 in the next two or three years? So we certainly haven’t shared expense guidance for the out years, and frankly, that’s something that we are, ourselves, working on internally as we undergo our long-term planning exercise. But I do think that a lot of the muscle that we’re building with regard to efficiency is going to translate into the longer run roadmap. And so I expect that we have really improved our cost structure over the last six months, and that’s going to form the basis along with an increased focus on operating efficiency going forward. I think that’s going to form the basis for our future outlook and making sure that we are constantly evaluating our investment roadmap to make sure that we are investing against the highest priority work and deprioritizing and winding down investments again where don’t see the ROI or we don’t see a compelling opportunity.

(47:09)
So again, we don’t have guidance to share yet on the out years, but I do expect the overall efficiency ethos very much to be a part of the coming years. On your second question on what the potential impact to our European business is of the transatlantic data transfer rules. So first I want to emphasize we continue to be hopeful that the new EU-US privacy framework will be implemented before a deadline for a suspension. But if it comes to that, there’s a lot that we don’t know in terms of the specifics of a final order and how long a suspension order would last, which would be important variables in determining the overall impact. What we do know is that roughly 10% of worldwide ad revenue comes from ads delivered to Facebook users in EU countries.

Susan Li (48:00):

But there are more details that we would need to understand, including the impact on advertisers and EU countries before we’d be able to really provide a more accurate or Folsom estimate of that impact.

Dave (48:13):

Your next question comes from line of Mark Mahaney with Evercore ISI. Your line is open.

Mark Mahaney (48:20):

Okay, thanks. Two questions. Are there any restructuring charges still to be had, Susan in Q2 or beyond that three to 5 billion that you talked about? Did we pretty much see all of that in Q1? And then secondly, I wonder if I could just go back to the broader opportunity around click to message? Facebook has had these two wonderful assets or just three now messaging assets, but really leading off with WhatsApp for quite some time. It’s always sort of under monetized versus some of the other leading assets, but that seems to have really started to change the numbers of becoming material.

(48:51)
You mentioned that there’s a real power alley in terms of marketers in Latin America and Southeast Asia. How can you take what is really a differentiated product and really kind of, I don’t know, blow it out more? Is there anything, other steps you can take to really get more advertisers to realize the opportunity just given the kind of cultural shifts, if you will, towards embracing messaging? Thank you very much.

Susan Li (49:15):

Thanks Mark. So on your first question about restructuring charges, Q1 restructuring charges are in the range of $1.1 billion and then we gave a range of $3 to $5 billion for the full year. So we do expect that we will be recognizing further restructuring charges throughout the year. And then the second question about the sort of opportunity in click to messaging ads and particularly in WhatsApp, what does the opportunity look like there? This is an area that I mean we’re very excited about. We’ve invested a lot. We see continued opportunity to scale click to message, particularly in WhatsApp and the click to Instagram direct area. Both of those are earlier on the growth curve. And we’re investing in a few areas to continue making it easier for people and businesses to connect.

(50:05)
First, we’re really investing in trying to make it easier to create ads. So in the last year, we’ve invested in a revamped experience in ads manager, native ad creation experiences directly in WhatsApp. We’re also scaling partners. So with the cloud hosted API, we now have hosted API solutions across WhatsApp, Messenger and Instagram so that our ecosystem of developers can help build good best in class experiences for businesses.

(50:33)
And then we’re also working on making these ads more performant by driving more action further down funnel. So we’re working on ranking and optimization to yield better conversion from these ads and introduce new ways to drive outcomes. We’ve introduced new features like in thread payments and other commerce tools. So we think that there’s a big opportunity here. We’re trying to make every part of the experience for advertisers easier, better, and more performant. And we’re excited to also see growth beyond the core markets here in Southeast Asia and Latin America where messaging is already common as a way for businesses to engage with customers and for businesses to engage with customers and their customer prospects. But we’re hopeful that we’ll see this also take off in other markets. We’re seeing strong growth in the US and Canada, but it’s just earlier there today.

Dave (51:27):

Your next question comes from line of Ross Sandler with Barclays. Your line is open.

Ross Sandler (51:34):

Hey, one more for Mark on the open sourcing of the models and infrastructure for generative AI. So do you view that as kind of a opportunity for developers to plug in to help ultimately improve engagement and revenue on your family of apps? Or do you think there could be other kind of business models that come out of that, like APIs and other types of partnerships? Just any thoughts on that.

(51:59)
And then second question is the back to the 24% increase in time spent on Instagram from Reels and content ranking, pretty incredible. So how much of that was lost engagement from folks like TikTok that you’re now recouping? And how do you think about how much more runway you have to increase that? Or when you layer in the discovery engine across Blue and other apps as you’re doing right now, is there some kind of benchmark you look at for increasing time spent is a 20%, 30%? Any thoughts on that? Thank you.

Mark Zuckerberg (52:41):

Sure. I’ll take the first one and then Susan can take the second one. On the AI tools, and we have a bunch of history here. So if you look at what we’ve done with PyTorch for example, which has generally become the standard in the industry is a tool that a lot of folks who are building AI models and different things in that space use, it’s generally been very valuable for us to provide that because now, all of the best developers across the industry are using tools that we’re also using internally. So the tool chain is the same. So when they create some innovation, we can easily integrate it into the things that we’re doing. When we improve something, it improves other products too because it’s integrated with our technology stack. When there are opportunities to make integrations with products, it’s much easier to make sure that developers and other folks are compatible with the things that we need and the way that our systems work.

(53:39)
There are a lot of advantages, but I view this more as a kind of backend infrastructure advantage with potential integrations on the product side, but one that should hopefully enable us to stay at the leading edge and integrate more broadly with the community and also make the way we run all this infrastructure more efficient over time. There are a number of models, I just gave PyTorch as an example. Open Compute is another model that has worked really well for us in this way, both to incorporate both innovation and scale efficiency into our own infrastructure. Our incentives I think are basically aligned towards moving in this direction.

(54:18)
Now that said, there’s a lot to figure out. So when you asked if there were going to be other opportunities, I hope so. I can’t speak to what all those things might be now. This is all quite early in getting developed. The better we do with the foundational work, the more opportunities I think that will come and present themselves. So I think that that’s all stuff that we need to figure out but at least at the base level, I think we’re generally incentivized to move in this direction and we also need to figure out how to go in that direction over time.

(54:47)
I mean, I mentioned LLaMA before and I also want to be clear that while I’m talking about helping contribute to an open ecosystem, LLaMA is a model that we only really made available to researchers and there’s a lot of really good stuff that’s happening there. But a lot of the work that we’re doing, I think we would aspire to and hope to make even more open than that. So we’ll need to figure out a way to do that.

Susan Li (55:14):

And Ross, your second question. Oh, sorry. I think there was a second part to the question, which is really about Reels driving an increase in time spent on Instagram and how much runway we see. So we certainly aren’t quantifying the kind of expected engagement growth, but we’re very pleased with what we’ve seen Reels drive in terms of incremental engagement to the platform so far. And we’ve talked about how the incrementality has grown over time and that’s important as we continue to improve ranking because we’re very focused not only on the absolute growth of Reels, but on increasing the incremental engagement. And that’s something where we’re very pleased with the trends that we’ve been seeing. As it comes to plays, watch time, re-shares, reactions, all of the metrics that we keep an eye on, we’re seeing meaningful growth in Reels. It’s clear that people value short form video and recommendations.

(56:08)
It’s also unlocking an entirely new content pool, which we think creates an engagement opportunity as we help people discover more interesting posts. And then that’s really valuable on top of the social graph. And we’re seeing the sharing flywheel take off with the growth of Reels reshares, which has doubled over the last six months. And then more broadly in terms of how the discovery engine is driving incremental engagement across the platform, our in-feed recommendations certainly go well beyond Reels. They cover all types of content including text, images, links, group content, et cetera. And on Facebook, we see that AI-driven recommendations are continuing to grow and contribute to increasing engagement on the app. So again, we’re not quantifying this, but it’s a place where I think we are both pleased with our progress and see significant opportunity for us to do better.

Speaker 1 (57:00):

Operator, we have time for one last question.

Dave (57:03):

Certainly. Thank you. That will come from the line of Michael Nathanson with MoffettNathanson. Your line is open.

Michael Nathanson (57:10):

Thank you so much. I have two if you can hear me. The first is Susan, I appreciate the confidence about Reel’s monetization going forward, but you share a bit what’s giving you the confidence that it goes from a headwind to neutral to a tailwind down the line, anything you share on data points about ROAS or adoption. And then just quickly, all the updates on Messenger are really great to hear. Do you think the adoption’s also being driven by maybe loss in signal and how does messaging improve marketer’s ability to basically retarget on post IDFA? Is there anything on signal loss and how messaging helps you marketers regain that? Thanks.

Susan Li (57:53):

Thanks Michael. So on Reels, we have shared for I think a while now that we’re working down the headwind to revenue from the growth of Reels cannibalizing some time that is spent on our more mature ad surfaces feed and stories. And basically we have been balancing the two factors here, which is the degree to which Reels is driving incremental engagement on the platform versus the lower monetization efficiency of Reels relative to the feed and stories engagement that it cannibalizes. And ultimately, the overall economics of Reels is really going to be determined by the combination of those two things. The thing that I would … So while we’re on track to Reels becoming neutral to revenue by end of year, early next year, but I do think it’s important to call out that Reels is structurally different from feed and stories. And so we don’t have line of sight of getting Reels to monetization parity per time with feeder stories anytime soon because of those structural differences.

(59:07)
But because it drives incremental engagement, we expect that we will continue and we expect we will continue to improve its monetization from current levels. So we expect the combination of those things will get us to revenue neutral by end of this year, early next and positive to revenue beyond that, despite that it doesn’t monetize as efficiently.

(59:28)
The second part of your question was updates on messaging and how does messaging improve marketer ability to retarget and face of signal loss? So click to messaging ads are a really important part of our overall ad strategy in terms of onsite objectives. And so it is a big part of the sort of first party data playbook. And so I think from that perspective, it is both sort of a first party data ads format, which I think in a signal challenge landscape is important for us. And then of course, it’s a way for us to both monetize messaging behavior that’s happening on our platform and create robust avenues of communication for businesses directly with their consumers, which we hope to broaden with broader business messaging offerings over time. So we’re very excited. We’re really excited with the progress that click to messaging ads have shown and the business opportunity that we have going forward there.

Speaker 1 (01:00:36):

Great. Thank you for joining us today. We appreciate your time. And we look-

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