Q1 FY2024 Earnings Call
META · Preprocessing Report
2024-04-24
Quality
100%
36
Turns
13
Speakers
5
Sections
9
Exchanges
456
Claims

Entities by group 34

company executives 2
Susan LipersonMark Zuckerbergperson
earnings call analysts 7
Justin PostpersonRoss SandlerpersonBrian NowakpersonKenneth GawrelskipersonMark ShmulikpersonDoug AnmuthpersonEric Sheridanperson
social apps 5
FacebookproductInstagramproductThreadsproductTikTokproductMessengerproduct
video formats 2
ReelsproductStoriesproduct
ad automation tools 1
Advantage+product
messaging apps 1
WhatsAppproduct
language models 2
Llama 3technologyLlama 2technology
smart glasses 1
Ray-Banproduct
vr headsets 1
Questproduct
search engines 2
GooglecompanyBingcompany
celebrity 1
Taylor Swiftperson
open hardware project 1
Open Computecompany
eyewear companies 1
EssilorLuxotticacompany
regulators 1
European Unioncompany
technology companies 1
Microsoftcompany
Ungrouped 5
MetacompanyYoussef SqualipersonUnited StatesotherReality Labscompanyonline commerceother
REPORTING 90PROJECTING 25POSITIONING 231EXPLANATORY 24ANALYST 41

Topics 101

artificial intelligence×61ad×39model×20revenue×18advertising×15business×14capital×14meta ai×12reels×11glasses×9product×8expense×8messaging×8recommendation×7investment×7video×6monetization×6advertiser×5metaverse×4reality labs×4

Themes 330

investment×8family of apps×8monetization×6performance×6use cases×5reality labs×5growth×4scale×4operating×4business model×3revenue growth×3video recommendations×3outlook×3ai investment×3business opportunity×3image generation×2model development×2app engagement×2value creation×2ai recommended×2efficiency×2ai and metaverse×2q1 fy2024×2total×2constant currency×2capital return×2regional growth×2across services×2ad load×2campaign automation×2meta ai×2new areas×2advertiser adoption×2product development×2full-year 2024×2spending returns×2resource allocation×2revenue and cost growth×2ai cost reduction×2long-term investment×2gaap and non-gaap presentation×1gaap to non-gaap reconciliation×1earnings materials availability×1momentum×1daily usage×1u.s. growth×1u.s. daily actives×1u.s. message sends×1and metaverse efforts×1assistant development×1product release×1service leadership×1rollout progress×1adoption×1user feedback×1demand for rollout×1international launch×1international expansion×1development playbook×1limited rollout and feedback×1model capability×1messaging integration×1query answering×1user experience×1benchmark leadership×1open source×1infrastructure scaling×1capex and energy expense scaling×1during investment phase×1product transition and scaling×1multiyear scaling cycle×1scaled experiences in apps×1new efforts×1leadership development×1product progress×1feed distribution×1ai targeting×1training efficiency×1cost efficiency×1custom development×1recommendations workloads×1lower-cost expansion×1headcount growth×1long-term focus×1metaverse convergence×1ar mainstream adoption×1fashionable ai×1ai assistant×1full context×1on glasses×1ai efforts×1strategic framing×1cross-segment attribution×1strong demand×1product expansion×1new design launch×1product strategy×1design variety for ai×1partner distribution×1open ecosystem expansion×1platform rollout×1headset designs×1first-party devices×1open platform×1bright spot×1updated full-screen×1reels usage×1user growth×1celebrity adoption×1q1 progress×1strategic opportunities×1year over year×1of revenue×1and development×1and marketing expense×1and administrative expense×1workforce size×1effective×1net×1per share×1infrastructure investment×1free cash flow×1cash and debt position×1daily active reach×1online commerce driver×1geographic mix×1advertiser demand×1impressions offset×1other revenue×1business messaging×1quest headset sales×1inventory valuation adjustments and restructuring costs×1engagement and monetization×1product momentum×1recommendation systems×1recommendations scaled×1relevance and personalization×1engagement mix×1video growth driver×1product integration×1product rollout×1integrations into apps×1within apps and feed×1chat surfaces×1social discovery strategy×1user traction×1targeting×1placement and frequency×1ad formats×1organic engagement optimization×1messaging monetization opportunity×1marketing efficiency×1marketing performance×1modeling improvement×1new architecture rollout×1larger model generalization×1smaller model replacement×1fewer models and better performance×1ai automation×1end-to-end automation×1automation adoption×1broader investment×1core business and ai×1ai capacity×1capital investment×1generative ai×1immersive experiences×1platform transition×1share repurchases and dividends×1legal and regulatory headwinds×1facial recognition trial×1potential material loss×1second quarter 2024 guidance×1foreign currency headwind×1full year guidance×1ai infrastructure×1full-year guidance×1strong start to year×1ai and reality labs initiatives×1product cycle×1mixed reality×1ai impact×1consumer signals×1timing of cycles×1buildout and scaling×1scale-up timing×1existing businesses vs new products×1product monetization×1cannibalization×1product ramp×1launch and early data×1engagement growth×1analogy point×1model relevance improvements×1improvements×1suboptimal use and signal capture×1remaining improvement areas×1advertiser testing barriers×1ai tools adoption barriers×1engagement improvement×1reels and feed×1multi-product recommendations×1reels validation×1watch time lift×1broader recommendations×1ads recommendations×1ad model consolidation×1architecture investment×1gen ai creative features×1early gen ai creative adoption×1small business adoption×1creative tools×1long-term strategy×1early stage×1tested with businesses on messenger and whatsapp×1product improvement from tests×1test expansion before broader availability×1shopping monetization×1chinese advertiser contribution×1chinese advertiser spend×1future disclosure×1revenue contribution×1ranking improvements×1call to actions and post-click experience×1direct response performance×1native to reels×1gen ai rollout across reels and instagram feed×1image expansion tools adoption among small businesses×1reels versus feed and stories×1reels supply constraints and personalization×1china spend growth×1china growth drivers×1asia pacific growth×1other geographies×1north america revenue acceleration×1china q1 outlook×1china demand recovery×1changed since last quarter×1ad market caution×1sustaining despite tough comps×1optimistic outlook×1product launch×1competitive positioning×1market leadership×1opportunity expansion×1model scaling capabilities×1assistant leadership×1ongoing investment×1pre-monetization scale×1product importance×1strategic importance×12024 comparison×1ai recommendations×1quality improvement×1better performance and organic engagement×1spend shifting to ai×1funding ai×1reallocation to ai×1returns×1historical returns and margins×1ai buckets×1core ai×1strategic ai bets×1strategic investment×1compute reallocation×1long-term outlook×1product investment×1future platform×1market opportunity×1platform growth×1ai focus×1long-term buildout×1ban or sale impact on social media landscape×1ban or sale precedent concerns×1advantage+ spend and cpm stabilization×1business impact×1ad traction×1audience adoption×1campaign performance×1advantage+ audience targeting efficiency×1advantage+ shopping and app campaign growth×1advantage+ shopping adoption×1advantage+ shopping conversion options expansion×1conversion tools×1advantage+ adoption×1ad creative features×1product learnings×1drivers of growth×1one-time item×1legal expenses×1legal matters×110-q disclosure×1long-term profile×1organic citations from ai×1long term monetization from ai×1premium ai tier×1for businesses and creators×1custom ai interactions and commerce×1real-time information partnership×1real-time information usefulness×1search differentiation×1search ads not planned×1ads and paid content×1paid access and premium features×1ads quality×1creator and business engagement×1business automation×1creator engagement×1creator commerce×1advertising and messaging×1high cost×1limited scaling opportunity×1user adoption×1large-scale development×1agentic capabilities×1definition×11:1 message-reply correspondence×1task execution×1shopping and research×1future of computing×1interactions×1customer engagement×1customer support and sales×1multiturn×1capability outlook×1reasoning and planning×1company opportunity×1ai opportunity×1leading capability×1leadership pursuit×1

Key Metrics 74

revenue×33capital expenditures×8expenses×7engagement×6ad performance×6ad load×4revenue growth×4adoption×4users×3time spent×3ad revenue growth×3operating expenses×3return on capital×3cost×3gaap×2daily active users×2ad impressions×2content×2operating income×2operating margin×2tax rate×2pricing growth×2operating loss×2ad spend×2conversion×2return on investment×2general and administrative expense growth×2user growth×1message sends×1requests×1parameters×1benchmarks×1stock volatility×1posts×1ads×1demand×1monthly actives×1r&d expense×1sales and marketing expense×1g&a expense×1employees×1net income×1earnings per share×1free cash flow×1share repurchases×1dividends×1cash and marketable securities×1daily active reach×1average price per ad×1impression growth×1video growth×1ad count×1ad optimization×1monetization×1monetization efficiency×1marketing performance×1capital expenditure×1profitability×1watch time×1model performance×1supply×1direct response performance×1performance×1spend×1growth rate×1cpm×1adoption growth×1campaign performance×1cost per click×1legal expense×1general and administrative expense×1accrual×1margin×1message-reply ratio×1

Entities 810

Meta×383Susan Li×147Mark Zuckerberg×137Reels×22Advantage+×18Facebook×13Instagram×9Justin Post×8WhatsApp×6Ross Sandler×6Brian Nowak×5Kenneth Gawrelski×5Llama 3×4Stories×4Ray-Ban×4Threads×4Mark Shmulik×4Doug Anmuth×4Quest×3TikTok×3Youssef Squali×3Messenger×2Taylor Swift×2United States×2Eric Sheridan×2Google×2Open Compute×1EssilorLuxottica×1Reality Labs×1European Union×1online commerce×1Llama 2×1Bing×1Microsoft×1

Business Segments 252

Family Of Apps×203Reality Labs×49

Sectors 285

artificial intelligence×112consumer internet×70digital advertising×23extended reality×22cloud computing×10wearables×10consumer electronics×8eyewear×4mixed reality×4semiconductor×3video streaming×3media and entertainment×2search engine×2enterprise software×2business messaging×2mobile applications×1display technology×1operating systems×1financial services×1advertising technology×1gaming×1instant messaging×1customer service×1

Regions 29

U.S.×9China×6Asia Pacific×3Rest of World×2North America×2Canada×2Texas×2English-speaking countries×1Europe×1EU×1

Metadata Distributions

Sentiment
positive 189negative 20neutral 202
Temporality
backward 96forward 117current 198
Certainty
definitive 101confident 131moderate 129tentative 49speculative 1
Magnitude
major 44moderate 295minor 72
Direction
improvement 38decline 3mixed 4none 366
Time Horizon
immediate 89near_term 137medium_term 73long_term 35unspecified 77
Verifiability
quantitative 71event 27qualitative 313
Analyst Intent
probing 18confirming 2seeking_detail 13seeking_guidance 8

Speakers

Executives
MZMark ZuckerbergCEOSLSusan LiCFO
Analysts
BNBrian NowakanalystDADoug AnmuthanalystESEric SheridananalystJPJustin PostanalystKGKenneth GawrelskianalystMSMark ShmulikanalystRJRonald JoseyanalystRSRoss SandleranalystYSYoussef Squalianalyst
Other
KDKenneth DorellirOPOperatoroperator

Sections

TypeLabelSpeaker
preamblePreambleOperator
prepared_remarksPrepared RemarksMark Zuckerberg, Susan Li, Kenneth Dorell
qa_sessionQ&A Session
closing_remarksClosing RemarksKenneth Dorell
operator_signoffOperator Sign-offOperator

Q&A Exchanges 9

#AnalystFirmTurns
1
ESEric Sheridan
Goldman Sachs3
2
BNBrian Nowak
Morgan Stanley3
3
MSMark Shmulik
Bernstein Research3
4
DADoug Anmuth
JPMorgan4
5
JPJustin Post
Bank of America4
6
YSYoussef Squali
Truist Securities3
7
KGKenneth Gawrelski
Wells Fargo3
8
RSRoss Sandler
Barclays4
9
RJRonald Josey
Citi3

Claim Taxonomy 411

REPORTING90
resultFinancial outcome for a completed period45
metricNon-financial quantitative fact24
operationalDiscrete completed event21
PROJECTING25
guidanceQuantitative expectation with number + time9
commitmentPromise with binary verifiable outcome14
targetLong-term aspirational quantitative goal2
POSITIONING231
strategyPriority, direction, or initiative209
competitiveCompany's position or advantages8
opportunityMarket condition framed as growth driver6
riskHeadwind, constraint, or uncertainty8
EXPLANATORY24
attributionWhy a specific outcome happened7
contextNon-company macro/industry fact17
FRAMING0
thesisFalsifiable belief about how the world works0
ANALYST41
questionInterrogative seeking information27
observationRestates a fact or data point11
concernFlags a risk or challenge0
estimateAnalyst's own projection or calculation2
sentimentOpinion, praise, or critique1

Transcript

Preamble
OP
Operatoroperator
Good afternoon. My name is Krista, 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. [Operator Instructions] This call will be recorded. Thank you very much. Ken Dorell, Meta's Director of Investor Relations, you may begin.
Prepared Remarks
KD
Kenneth DorellirMeta
Thank you. Good afternoon, and welcome to Meta Platform's First Quarter 2021 Earnings Conference Call.
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. Factors that could cause these results to differ materially are set forth in today's earnings press release and in our annual report on Form 10-K filed with the SEC. 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.
During this call, we will present both GAAP and certain non-GAAP financial measures. A reconciliation of GAAP to non-GAAP measures is included in today's earnings press release. The earnings 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.
#1
#2
#3
#4
#5
#6
#7
guidance#8
strategy#9
strategy#10
#11
MZ
Mark ZuckerbergCEOMeta
All right. Thanks, Ken, and everyone, thanks for joining.
It's been a good start to the year, both in terms of product momentum and business performance. We estimate that more than 3.2 billion people use at least one of our apps each day, and we're seeing healthy growth in the U.S. And I want to call out WhatsApp specifically, where the number of daily actives and message sends in the U.S. keeps gaining momentum, and I think we're on a good path there. We've also made good progress on our AI and metaverse efforts, and that's where I'm going to focus most of my comments today. So let's start with AI. We're building a number of different AI services, from Meta AI, our AI assistant that you can ask any question across our apps and glasses, to creator AIs that help creators engage their communities and that fans can interact with, to business AIs that we think every business eventually on our platform will use to help customers buy things and get customer support to internal coding and development AIs to hardware like glasses for people to interact with AIs and a lot more. Last week, we had the major release of our new version of Meta AI that is now powered by our latest model, Llama 3. And our goal with Meta AI is to build the world's leading AI service, both in quality and usage. The initial rollout of Meta AI is going well. Tens of millions of people have already tried it. The feedback is very positive. And when I first checked in with our teams, the majority of feedback we were getting was people asking us to release Meta AI for them wherever they are. So we've started launching Meta AI in some English speaking countries, and we'll roll out in more languages and countries over the coming months.
You all know our product development playbook by this point. We release an early version of a product to a limited audience to gather feedback and start improving it, and then once we think it's ready, then we make it available to more people. That early release was last fall and with this release, we are now moving to that next growth phase of our playbook. We believe that Meta AI with Llama 3 is now the most intelligent AI assistant that you can freely use. And now that we have the superior quality product, we are making it easier for lots of people to use it within WhatsApp, Messenger, Instagram and Facebook. Now in addition to answering more complex queries, a few other notable and unique features from this release. Meta AI now creates animations from still images and now generates high-quality images so fast that it can create and update them as you are typing, which is pretty awesome. I've seen a lot of people commenting about that experience online and how they've never seen or experienced anything like it before. In terms of the core AI model and intelligence that's powering Meta AI, I'm very pleased with how Llama 3 has come together so far.
The 8 billion and 70 billion parameter models that we released are best-in-class for their scale. The 400-plus billion parameter model that we're still training seems on track to be industry leading on several benchmarks. And I expect that our models are just going to improve further from open source contributions. Overall, I view the results our teams have achieved here as another key milestone in showing that we have the talent, data and ability to scale infrastructure to build the world's leading AI models and services. And this leads me to believe that we should invest significantly more over the coming years to build even more advanced models and the largest scale AI services in the world. As we're scaling CapEx and energy expenses for AI, we'll continue focusing on operating the rest of our company efficiently. But realistically, even with shifting many of our existing resources to focus on AI, we'll still grow our investment envelope meaningfully before we make much revenue from some of these new products. I think it's worth calling that out that we've historically seen a lot of volatility in our stock during this phase of our product playbook, where we're investing in scaling a new product but aren't yet monetizing it. We saw this with Reels, Stories as newsfeed transition to mobile and more. And I also expect to see a multiyear investment cycle before we fully scale Meta AI, business AIs and more into the profitable services I expect as well. Historically, investing to build these new scaled experiences in our apps has been a very good long-term investment for us and for investors who have stuck with us. And the initial signs are quite positive here, too. But building the leading AI will also be a larger undertaking than the other experiences we've added to our apps, and this is likely going to take several years. On the upside, once our new AI services reach scale, we have a strong track record of monetizing them effectively. There are several ways to build a massive business here, including scaling business messaging, introducing ads or paid content into AI interactions and enabling people to pay to use bigger AI models and access more compute. And on top of those, AI is already helping us improve app engagement, which naturally leads to seeing more ads and improving ads directly to deliver more value. So if the technology and products evolve in the way that we hope, each of those will unlock massive amounts of value for people and business for us over time. We're seeing good progress on some of these efforts already. Right now, about 30% of the posts on Facebook feed are delivered by our AI recommendation system. That's up 2x over the last couple of years.
And for the first time ever, more than 50% of the content that people see on Instagram is now AI recommended. AI has also been a huge part of how we create value for advertisers by showing people more relevant ads. And if you look at our 2 end-to-end AI-powered tools, Advantage+ shopping and Advantage+ app campaigns, revenue flowing through those has more than doubled since last year. We're also going to continue to be very focused on efficiency as we scale Meta AI and other AI services.
Some of this will come from improving how we train and run models. Some improvements will come from the open source community, and we're improving cost efficiency is one of the main areas that I expect that open sourcing will help us improve similar to what we saw with Open Compute. We'll also keep making progress on building more of our own silicon. Our Meta training and inference accelerator chip has successfully enabled us to run some of our recommendations-related workloads on this less expensive stack. And as this program matures over the coming years, we plan to expand this to more of our workloads as well. And of course, as we ramp these investments, we will also continue to carefully manage headcount and other expense growth throughout the company. Now in addition to our work on AI, our other long-term focus is the metaverse.
It's been interesting to see how these 2 themes have come together. This is clearest when you look at glasses. I used to think that AR glasses wouldn't really be a mainstream product until we had full holographic displays — and I still think that, that's going to be awesome and is the long-term mature state for the product. But now it seems pretty clear that there's also a meaningful market for fashionable AI glasses without a display. Glasses are the ideal device for an AI assistant because you can let them see what you see and hear what you hear. So they have full context on what's going on around you as they help you with whatever you're trying to do. Our launch this week of Meta AI with Vision on the glasses is a good example where you can now ask questions about things that you're looking at. Now one strategy dynamic that I've been reflecting on is that an increasing amount of our Reality Labs work is going towards serving our AI efforts. We currently report on our financials as if Family of Apps and Reality Labs were 2 completely separate businesses, but strategically, I think of them as fundamentally the same business with the vision of Reality Labs to build the next generation of computing platforms in large part so that we can build the best apps and experiences on top of them. Over time, we'll need to find better ways to articulate the value that's generated here across both segments so it doesn't just seem like our hardware costs increase as our glasses ecosystem scales, but all the value flows to a different segment. The Ray-Ban Meta glasses that we built with Essilor Luxottica continue to do well and are sold out in many styles and colors. So we're working to make more and release additional styles as quickly as we can. We just released the new cat-eye Skyler design yesterday, which is more feminine.
And in general, I'm optimistic about our approach of starting with the classics and expanding with an increasing diversity of options over time. If we want everyone to be able to use wearable AI, I think eyewear is a bit different from phones or watches in that people are going to want very different designs. So I think our approach of partnering with the leading eyewear brands will help us serve more of the market. I think a similar open ecosystem approach will help us expand the virtual and mixed reality headset market over time as well. We announced that we're opening up Meta Horizon OS, the operating system we've built to power Quest.
As the ecosystem grows, I think there will be sufficient diversity in how people use mixed reality, that there will be demand for more designs than we'll be able to build. For example, a work-focused headset may be slightly less designed for motion but may — you want to be lighter by connecting to your laptop; a fitness-focused headset may be lighter with sweat-wicking materials; an entertainment-focused headset may prioritize the highest resolution displays over everything else; a gaming-focused headset may prioritize peripherals and haptics or a device that comes with Xbox controllers and a game pass subscription out of the box. Now to be clear, I think that our first-party Quest devices will continue to be the most popular headsets as we see today, and we'll continue focusing on advancing the state-of-the-art tech and making it accessible to everyone. But I also think that opening our ecosystem and opening our operating system will help the overall mixed reality ecosystem grow even faster.
Now in addition to AI and the metaverse, we're seeing good improvements across our apps. I touched on some of the most important trends already with WhatsApp growth in the U.S. and AI-powered recommendations in our feeds and reels already. But I do want to mention that video continues to be a bright spot. This month, we launched an updated full-screen video player on Facebook that brings together reels, longer videos and live content into a single experience with a unified recommendation system. On Instagram, reels and video continue to drive engagement, with reels alone now making up 50% of the time that's spent within the app. Threads is growing well, too. There are now more than 150 million monthly actives, and it continues to generally be on the trajectory that I hoped to see. And of course, my daughters would want me to mention that Taylor Swift is now on Threads, that one was a big deal in my house. All right. That is what I wanted to cover today. I am proud of the progress we've made so far this year. We've got a lot more execution ahead to fulfill the opportunities ahead of us. A big thank you to all of our teams who are driving all these advances and to all of you for being on this journey with us. And now here is Susan.
#12
#13
strategy#14
metric#15
metric#16
metric#17
metric#18
strategy#19
#20
strategy#21
operational#22
competitive#23
strategy#24
metric#25
opportunity#26
metric#27
commitment#28
commitment#29
strategy#30
strategy#31
strategy#32
competitive#33
strategy#34
commitment#35
commitment#36
strategy#37
context#38
strategy#39
context#40
metric#41
strategy#42
strategy#43
competitive#44
strategy#45
strategy#46
context#47
context#48
strategy#49
strategy#50
strategy#51
strategy#52
strategy#53
strategy#54
strategy#55
attribution#56
strategy#57
strategy#58
metric#59
metric#60
metric#61
strategy#62
result#63
strategy#64
strategy#65
competitive#66
strategy#67
opportunity#68
strategy#69
strategy#70
strategy#71
context#72
strategy#73
context#74
strategy#75
strategy#76
strategy#77
strategy#78
strategy#79
strategy#80
strategy#81
metric#82
commitment#83
operational#84
strategy#85
strategy#86
attribution#87
attribution#88
operational#89
context#90
strategy#91
competitive#92
strategy#93
strategy#94
strategy#95
strategy#96
operational#97
metric#98
strategy#99
metric#100
operational#101
#102
#103
strategy#104
risk#105
#106
#107
SL
Susan LiCFOMeta
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. Q1 total revenue was $36.5 billion, up 27% on both a reported and constant currency basis. Q1 total expenses were $22.6 billion, up 6% compared to last year.
In terms of the specific line items, cost of revenue increased 9% as higher infrastructure-related costs were partially offset by lapping Reality Labs' inventory-related valuation adjustments. R&D increased 6%, driven mostly by higher headcount-related expenses and infrastructure costs, which were partially offset by lower restructuring costs. Marketing and sales decreased 16% due mainly to lower restructuring costs, professional services and marketing spend. G&A increased 20% as higher legal-related expenses were partially offset by lower restructuring costs.
We ended the first quarter with over 69,300 employees, up 3% from Q4. First quarter operating income was $13.8 billion, representing a 38% operating margin. Our tax rate for the quarter was 13%. Net income was $12.4 billion or $4.71 per share. Capital expenditures, including principal payments on finance leases, were $6.7 billion, driven by investments in servers, data centers and network infrastructure. Free cash flow was $12.5 billion. We repurchased $14.6 billion of our Class A common stock and paid $1.3 billion in dividends to shareholders, ending the quarter with $58.1 billion in cash and marketable securities and $18.4 billion in debt.
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, with approximately 3.2 billion people using at least one of our Family of Apps on a daily basis in March. Q1 total Family of Apps revenue was $36 billion, up 27% year-over-year. Q1 Family of Apps ad revenue was $35.6 billion, up 27% or 26% on a constant currency basis.
Within ad revenue, the online commerce vertical was the largest contributor to year-over-year growth, followed by gaming and entertainment and media. On a user geography basis, ad revenue growth was strongest in Rest of World and Europe at 40% and 33%, respectively. Asia Pacific grew 25% and North America grew 22%. In Q1, the total number of ad impressions served across our services increased 20%, and the average price per ad increased 6%. Impression growth was mainly driven by Asia Pacific and Rest of World. Pricing growth was driven by advertiser demand, which was partially offset by strong impression growth, particularly from lower-monetizing regions and services. Family of Apps other revenue was $380 million in Q1, up 85%, driven by business messaging revenue growth from our WhatsApp business platform.
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 $18.4 billion, representing approximately 81% of our overall expenses. Family of Apps expenses were up 7% due mainly to higher legal and infrastructure costs that were partially offset by lower restructuring costs. Family of Apps operating income was $17.7 billion, representing a 49% operating margin. Within our Reality Labs segment, Q1 revenue was $440 million, up 30%, driven by Quest headset sales. Reality Labs expenses were $4.3 billion, down 1% year-over-year as higher head count-related expenses were more than offset by lapping inventory-related valuation adjustments and restructuring costs. Reality Labs operating loss was $3.8 billion. Turning now to the business outlook.
There are 2 primary factors that drive our revenue performance: our ability to deliver engaging experiences for our community and our effectiveness at monetizing that engagement over time. On the first, we remain pleased with engagement trends and have strong momentum across our product priorities. Our investments in developing increasingly advanced recommendation systems continue to drive incremental engagement on our platform, demonstrating that people are finding added value by discovering content from accounts they are not connected to. The level of recommended content in our apps has scaled as we've improved these systems, and we see further opportunity to increase the relevance and personalization of recommendations as we advance our models. Video also continues to grow across our platform, and it now represents more than 60% of time on both Facebook and Instagram. Reels remains the primary driver of that growth, and we're progressing on our work to bring together Reel's longer-form video and live video into one experience on Facebook. In April, we rolled out this unified video experience in the U.S. and Canada, which is increasingly powered by our next-generation ranking architecture that we expect will help deliver more relevant video recommendations over time.
We're also introducing deeper integrations of generative AI into our apps in the U.S. and more than a dozen other countries. Along with using Meta AI within our chat surfaces, people will now be able to use Meta AI in search within our apps as well as feed and groups on Facebook. We expect these integrations will complement our social discovery strategy as our recommendation systems help people to discover and explore their interests, while Meta AI enables them to dive deeper on topics they're interested in. Threads also continues to see good traction as we continue to ship valuable features and scale the community. Now to the second driver of our revenue performance, increasing monetization efficiency. There are 2 parts to this work. The first is optimizing the level of ads within organic engagement. Here, we continue to advance our understanding of users' preferences for viewing ads to more effectively optimize the right time, place and person to show an ad to. For example, we are getting better at adjusting the placement and number of ads in real time based on our perception of a user's interest and ad content and to minimize disruption from ads as well as innovating on new and creative ad formats.
We expect to continue that work going forward, while surfaces with relatively lower levels of monetization, like video and messaging, will serve as additional growth opportunities. The second part of improving monetization efficiency is enhancing marketing performance. Similar to our work with organic recommendations, AI is playing an increasing role in these efforts. First, we are making ongoing ads modeling improvements that are delivering better performance for advertisers. One example is our new ads ranking architecture, Meta Lattice, which we began rolling out more broadly last year. This new architecture allows us to run significantly larger models that generalize learnings across objectives and surfaces in place of numerous smaller ad models that have historically been optimized for individual objectives and surfaces. This is not only leading to increased efficiency as we operate fewer models but also improving ad performance. Another way we're leveraging AI is to provide increased automation for advertisers. Through our Advantage+ portfolio, advertisers can automate one step of the campaign setup process, such as selecting which ad creative to show, or automate their campaign completely using our end-to-end automation tools, Advantage+ shopping and Advantage+ app ads. We're seeing growing use of these solutions, and we expect to drive further adoption over the course of the year while applying what we learned to our broader ads investments. Next, I'd like to discuss our approach to capital allocation.
We continue to see compelling investment opportunities to both improve our core business in the near term and capture significant longer-term opportunities in generative AI and Reality Labs. As we develop more advanced and compute-intensive recommendation models and scale capacity for our generative AI training and inference needs, we expect that having sufficient infrastructure capacity will be critical to realizing many of these opportunities. As a result, we expect that we will invest significantly more in infrastructure over the coming years. Our other long-term initiatives that we're continuing to make significant investments in is Reality Labs. We are also starting to see our AI initiatives increasingly overlap with our Reality Labs work. For example, with Ray-Ban Meta smart glasses, people in the U.S. and Canada can now use our multimodal Meta AI assistant for daily tasks without pulling out their phone. Longer term, we expect generative AI to play an increasing role in our mixed reality products, making it easier to develop immersive experiences. Accelerating our AI efforts will help ensure we can provide the best version of our services as we transition to the next computing platform. We expect to pursue these opportunities while maintaining a focus on operating discipline, and we believe our strong financial position will allow us to support these investments while also returning capital to shareholders through share repurchases and dividends. In addition, we continue to monitor an active regulatory landscape, including the increasing legal and regulatory headwinds in the EU and the U.S. that could significantly impact our business and our financial results. We also have a jury trial scheduled for June in a suit brought by the state of Texas regarding our use of facial recognition technology, which could ultimately result in a material loss.
Turning now to the revenue outlook. We expect second quarter 2024 total revenue to be in the range of $36.5 billion to $39 billion. Our guidance assumes foreign currency is a 1% headwind to year-over-year total revenue growth based on current exchange rates. Turning now to the expense outlook. We expect full year 2024 total expenses to be in the range of $96 million to $99 billion, updated from our prior outlook of $94 million to $99 billion due to higher infrastructure and legal costs. For Reality Labs, we continue to expect operating losses to increase meaningfully year-over-year due to our ongoing product development efforts and our investments to further scale our ecosystem. Turning now to the CapEx outlook. We anticipate our full year 2024 capital expenditures will be in the range of $35 billion to $40 billion, increased from our prior range of $30 billion to $37 billion as we continue to accelerate our infrastructure investments to support our AI road map. While we are not providing guidance for years beyond 2024, we expect CapEx will continue to increase next year as we invest aggressively to support our ambitious AI research and product development efforts.
On to tax. Absent any changes to our tax landscape, we expect our full year 2024 tax rate to be in the mid-teens.
In closing, Q1 was a good start to the year. We're seeing strong momentum within our Family of Apps and are making important progress on our longer-term AI and Reality Labs initiatives that have the potential to transform the way people interact with our services over the coming years. With that, Krista, let's open up the call for questions.
#108
commitment#109
context#110
result#111
result#112
result#113
result#114
result#115
result#116
result#117
metric#118
result#119
result#120
result#121
result#122
result#123
result#124
strategy#125
result#126
result#127
result#128
result#129
#130
#131
metric#132
result#133
result#134
result#135
result#136
result#137
result#138
metric#139
metric#140
result#141
result#142
result#143
result#144
strategy#145
strategy#146
result#147
result#148
result#149
result#150
result#151
attribution#152
result#153
attribution#154
result#155
#156
strategy#157
strategy#158
strategy#159
strategy#160
strategy#161
metric#162
opportunity#163
strategy#164
operational#165
strategy#166
commitment#167
commitment#168
commitment#169
strategy#170
strategy#171
#172
strategy#173
strategy#174
strategy#175
strategy#176
strategy#177
strategy#178
strategy#179
strategy#180
strategy#181
strategy#182
operational#183
strategy#184
operational#185
attribution#186
strategy#187
strategy#188
strategy#189
strategy#190
strategy#191
#192
strategy#193
strategy#194
strategy#195
strategy#196
strategy#197
strategy#198
strategy#199
strategy#200
strategy#201
strategy#202
result#203
risk#204
commitment#205
risk#206
Q&A Session
Q&A 1/9
OP
Operatoroperator
[Operator Instructions] And your first question comes from the line of Eric Sheridan from Goldman Sachs.
ES
Eric SheridananalystGoldman Sachs
Maybe I'll ask a two-parter. Mark, you used the analogy of other investments cycles you've been through around products like Stories and Reels. I know you're not giving long-term guidance today, but using those analogies, how should investors think about the length and depth of this investment cycle with respect to either AI and/or Reality Labs more broadly and mixed reality? And you both talked about the impact AI is having on the advertising ecosystem. What are you watching for in terms of adoption or utility on the consumer side to know that AI adoption is tracking along with the investment cycle?
strategy#207
guidance#208
guidance#209
strategy#210
guidance#211
MZ
Mark ZuckerbergCEOMeta
Yes. In terms of the timing, I think it's somewhat difficult to extrapolate from previous cycles. But I guess like the main thing that we see is that we will usually take, I don't know, a couple of years, I mean, it could be a little more, it could be less to focus on building out and scaling the products. And we typically don't focus that much on monetization of the new areas until they reach significant scale because it's so much higher leverage for us just to improve monetization on other things before these new products are at scale. So you enter this period where I think kind of smart investors see that the product is scaling and that there's a clear monetizable opportunity there even before the revenue materializes. And I think we've seen that with Reels and with Stories and with the shift to mobile and all these things, where basically, we build out the inventory first for a period of time and then we monetize it. And during that time, when it's scaling, sometimes it's not just the case that we're not making money from that thing. It can often actually be the case that it displaces other revenue from other things. So like you saw with Reels, I mean, it scaled and there was a period where it was not profitable for us as it was scaling before it became profitable.
So I think that's more the analogy that I'm making on this. But I think it's — what that suggests is that what we should all be focused on for the next period is as the consumer products scale, Meta AI really just launched in a meaningful way so we don't have any kind of hard stats to share on that. But I'd say that's the main thing that I'm focused on for this year and probably a lot of next year is growing that product and the other AI products and the engagement around them. And I think we should all have quite a bit of confidence that if those are on a good track to scale, then they're going to end up being very large businesses. So that's the main point that I was trying to make there.
guidance#212
strategy#213
guidance#214
guidance#215
strategy#216
guidance#217
strategy#218
strategy#219
#220
Q&A 2/9
OP
Operatoroperator
Your next question comes from the line of Brian Nowak from Morgan Stanley.
BN
Brian NowakanalystMorgan Stanley
Thanks for taking my questions, I have 2.
The first one is on sort of the recommendation engine improvements and even, Susan, when you talked about further opportunities to increase the relevance of the models. Could you just unpack that a little bit for us? Can you give us examples of where you're still running the model in a suboptimal basis or opportunities for improved signal capture use or data you're not using? Where are sort of the areas of improvement you see from here?
And then the second one, when you talk about driving incremental adoption of AI tools for advertisers, what are sort of some of the main gating factors you've encountered to get advertisers to test these tools? And how do you think about sort of addressing that throughout '24 and '25?
#221
observation#222
question#223
observation#224
question#225
#226
strategy#227
SL
Susan LiCFOMeta
Thanks, Brian. So to your first question, where are there more opportunities for us to leverage and improve our recommendations models to drive engagement? One of the things I would say is, historically, each of our recommendation products, including Reels, in-feed recommendations, et cetera, has had their own AI model. And recently, we've been developing a new model architecture with the aim for it to power multiple recommendations products. We started partially validating this model last year by using it to power Facebook Reels. And we saw meaningful performance gains, 8% to 10% increases in watch time as a result of deploying this. This year, we're actually planning to extend the singular model architecture to recommend content across not just Facebook Reels, but also Facebook's video tab as well. So while it's still too early to share specific results, we're optimistic that the new model architecture will unlock increasingly relevant video recommendations over time. And if it's successful, we'll explore using it to power other recommendations. And analog exists, I would say, on the ad side.
We've talked a little bit about the new model architecture Meta Lattice that we deployed last year that consolidates smaller and more specialized models into larger models that can better learn what characteristics improve ad performance across multiple services, like feed and Reels and multiple types of ads and objectives at the same time. And that's driven improved ad performance over the course of 2023 as we deployed it across Facebook and Instagram to support multiple objectives. And over the course of 2024, we expect to further enhance model performance and include support for even more objectives like web and app and ROAS. So there's a lot of work that we're investing in, in the underlying model architecture for both organic engagement and ads that we expect is going to continue to deliver increasing ads performance over time.
The second question you asked was around getting advertisers to test and adopt gen AI tools. There are 2 flavors of this. The more near-term version is around the gen AI ad creative features that we have put into our ads creation tools. And it's early, but we're seeing adoption of these features across verticals and different advertiser sizes. In particular, we've seen outsized adoption of image expansion with small businesses, and this will remain a big area of focus for us in 2024, and I expect that improvements to our underlying foundation models will enhance the quality of the outputs that are generated and support new features on the road map. But right now, we have features supporting text variations, image expansion and background generation, and we're continuing to work to make those more performant for advertisers to create more personalized ads at scale.
The longer-term piece here is around business AIs. We have been testing the ability for businesses to set up AIs for business messaging that represent them in chats with customers, starting by supporting shopping use cases such as responding to people asking for more information on a product or its availability. So this is very, very early. We've been testing this with a handful of businesses on Messenger and WhatsApp, and we're hearing good feedback with businesses saying that the AIs have saved them significant time while customer — consumers noted more timely response times. And we're also learning a lot from these tests to make these AIs more performant over time as well. So we'll be expanding these tests over the coming months, and we'll continue to take our time here to get it right before we make it more broadly available.
strategy#228
strategy#229
strategy#230
strategy#231
strategy#232
strategy#233
strategy#234
attribution#235
operational#236
strategy#237
operational#238
strategy#239
strategy#240
strategy#241
Q&A 3/9
OP
Operatoroperator
Your next question comes from the line of Mark Shmulik from Bernstein Research.
MS
Mark ShmulikanalystBernstein Research
I guess back to that product playbook that we talked about a few times, with kind of Reels now such a large share of kind of time spent on Instagram and Facebook, how do we think about the next leg of kind of monetization growth from here? In particular, as we kind of get back to kind of shopping on platform or other ways to monetize, any color there on the road map kind of just beyond ad insertion from here? And then, Susan, just on the ad market, in particular, previously, we heard a lot about kind of Chinese-based advertiser contribution. Any color you could share there on kind of how that spend is trending?
#242
observation#243
question#244
question#245
SL
Susan LiCFOMeta
Sure. Thanks, Mark. So Reels revenue continued to grow across Instagram and Facebook in Q1, and that's driven both by higher engagement and increased monetization efficiency through our ads ranking and delivery improvements. And we — as we've mentioned before, we don't plan on quantifying the impact from Reels going forward, but it remains a positive contributor to overall revenue. And we expect that there are going to be opportunities for us to continue improving performance and growing supply. So on the performance improvements, we are investing in ongoing ranking improvements.
We're continuing to make ads easier and more intuitive to interact with through work like optimizing call to actions and post-click experiences, which are especially important for DR performance. And we're also optimizing ads to feel more native to Reels. In Q1, we rolled out our gen AI image expansion tools across Facebook and Instagram Reels after having introduced it to Instagram feed in Q4, and we're seeing, again, outsized adoption with small businesses. So we're excited about the opportunities to continue making these ads more performant. And even though ads — the Reels ad loads, sorry, has increased over the last year, it remains lower on a per time basis than both Feed and Stories. So we're going to continue to look for opportunities to thoughtfully grow it in the future and invest in creative ways to address the structural supply constraints of the Reels format being more video-heavy, including higher density experiences and formats and increasingly personalizing ad loads, which we think will make sure that we're really putting ads in front of people when they're most likely to be interested and engaged with them.
The second question you asked was around China. Growth in spend from China advertisers remained strong in Q1. This was driven by online commerce and gaming, and it's reflected in our Asia Pacific advertisers segment, which remained the fastest-growing region, at 41% year-over-year in Q1. Now we did see strength across other geographies as well, including a 6-point acceleration in total revenue growth from North America advertisers. So I would say that we aren't quantifying the Q1 contribution from China, and we don't have forward-looking expectations to share on quarterly China-based ad revenue, but I will say that we are lapping periods of increasingly strong demand over the course of 2024 given the recovery of China-based advertisers in 2023 from their prior pandemic-driven headwinds.
question#246
question#247
question#248
#249
strategy#250
context#251
strategy#252
operational#253
metric#254
commitment#255
strategy#256
strategy#257
strategy#258
operational#259
operational#260
strategy#261
strategy#262
Q&A 4/9
OP
Operatoroperator
Your next question comes from the line of Doug Anmuth from JPMorgan.
DA
Doug AnmuthanalystJPMorgan
Can you just talk about what's changed most in your view in the business and the opportunity now versus 3 months ago?
And is there anything you're more cautious about in revenue in the ad market? And is the AI opportunity just even bigger, and therefore, requiring more investment than expected? And then, Susan, can you also just comment on how you're thinking about that ability to sustain growth rates over the next few quarters as you face tougher comps off a big base of ad dollars?
observation#275
observation#276
observation#277
question#278
MZ
Mark ZuckerbergCEOMeta
Yes, I can speak to the first one. I think we've gotten more optimistic and ambitious on AI. So previously, I think that our work in this — I mean when you were looking at last year, when we released Llama 2, we were very excited about the model and thought that, that was going to be the basis to be able to build a number of things that were valuable that integrated into our social products. But now I think we're in a pretty different place. So with the latest models, we're not just building good AI models that are going to be capable of building some new good social and commerce products. I actually think we're in a place where we've shown that we can build leading models and be the leading AI company in the world. And that opens up a lot of additional opportunities beyond just ones that are the most obvious ones for us. So that's — this is what I was trying to refer to in my opening remarks where I just view the success that we've seen with the way that Llama 3 and Meta AI have come together as a real validation technically that we have the talent, the data and the ability to scale infrastructure to do leading work here. And with Meta AI, I think that we are on our path to having Meta AI be the most used and best AI assistant in the world, which I think is going to be enormously valuable.
So all of that basically encourages me to make sure that we're investing to stay at the leading edge of this. And we're doing that at the time when we're also scaling the product before it is making money. So that's the analogy that I was making before, which is we've gone through some of those cycles before.
But fundamentally, I think if you look at the facts of what our team is able to produce, I think it just — our optimism and ambition have just grown quite a bit, and I think that this is just going to end up being quite an important set of products for us. So it was already going to be. Now I think it has the potential to be even more important.
#279
#280
result#281
result#282
strategy#283
strategy#284
strategy#285
strategy#286
strategy#287
context#288
strategy#289
operational#290
strategy#291
strategy#292
metric#293
strategy#294
risk#295
#296
result#297
strategy#298
metric#299
SL
Susan LiCFOMeta
And I can take that second question, Doug. So we aren't giving full year 2024 guidance. And obviously, our revenue for the full year will be influenced by many factors, including macro conditions and things that are harder to predict the further out you go.
And of course, over the course of 2024, we will also be lapping periods of increasingly strong demand. With that said, we expect to see good opportunities to continue growing engagement across our products, driven by the investments we made in AI-based content recommendations, our ongoing video work. And we also expect that we will continue to drive ads performance gains and continue to make our ads sort of more effective and deliver increasing value to advertisers. One thing I'd share, for example, is that we actually grew conversions at a faster rate than we grew impressions over the course of this quarter. So we are — we're expecting to — which basically suggests that our conversion grade is growing and is one of the ways in which our ads are becoming more performant. So I feel like there's a lot of opportunity for us, both with our organic engagement growth and with continuing to make the ads better and to continue driving more results for advertisers.
opportunity#300
result#301
strategy#302
opportunity#303
Q&A 5/9
OP
Operatoroperator
Your next question comes from the line of Justin Post from Bank of America.
JP
Justin PostanalystBank of America
First on the CapEx, mostly, you're kind of talking about an investment cycle here. Is there any way you could kind of use some of the metaverse spend over into AI? Are they converging and kind of use some of the money from the other areas to kind of fund the AI?
And then second, longer-term investors are very focused on returns on capital. Obviously, great returns on CapEx in the past with your margins today. How do we think about the returns on the capital you're spending? How are you thinking about it, I guess, going forward 2, 3 years out?
question#304
question#305
question#306
question#307
#308
strategy#309
operational#310
SL
Susan LiCFOMeta
So on the — I would say — well, I can start with the second part, and then I'll defer to Mark on the first one.
In terms of measuring the ROI on our CapEx investments, we've broadly categorized our AI investments into 2 buckets. I think of them as sort of core AI work and then strategic bets, which would include gen AI and the advanced research efforts to support that. And those are just really at different stages as it relates to being able to measure the return and drive revenue for our business. So with our core AI work, we continue to have a very ROI-driven approach to investment, and we're still seeing strong returns as improvements to both engagement and ad performance have translated into revenue gains. Now the second area, strategic bets, is where we are much earlier. Mark has talked about the potential that we believe we have to create significant value for our business in a number of areas, including opportunities to build businesses that don't exist on us today. But we'll need to invest ahead of that opportunity to develop more advanced models and to grow the usage of our products before they drive meaningful revenue. So while there is tremendous long-term potential, we're just much earlier on the return curve than with our core AI work. What I'll say though is we're also building our systems in a way that gives us fungibility in how we use our capacity so we can flex it across different use cases as we identify what are the best opportunities to put that infrastructure toward.
strategy#311
strategy#312
competitive#313
strategy#314
operational#315
competitive#316
strategy#317
risk#318
strategy#319
strategy#320
MZ
Mark ZuckerbergCEOMeta
And then on the question of shifting resources from other parts of the company. I would say, broadly, we actually are doing that in a lot of places in terms of shifting resources from other areas, whether it's compute resources or different things in order to advance the AI efforts.
For Reality Labs specifically, I'm still really optimistic about building these new computing platforms long term. I mentioned in my remarks upfront that one of the bigger areas that we're investing in Reality Labs is glasses. We think that that's going to be a really important platform for the future. Our outlook for that, I think, has improved quite a bit because previously, we thought that, that would need to wait until we have these full holographic displays to be a large market. And now we're a lot more focused on the glasses that we're delivering in partnership with Ray-Ban, which I think are going really well. And — so that, I think, has the ability to be a pretty meaningful and growing platform sooner than I would have expected. So it is true that more of the Reality Labs work, like I said, is sort of focused on the AI goals as well. But I still think that we should focus on building these long-term platforms, too.
strategy#321
strategy#322
#323
commitment#324
guidance#325
context#326
strategy#327
strategy#328
metric#329
strategy#330
Q&A 6/9
OP
Operatoroperator
Your next question comes from the line of Youssef Squali from Truist Securities.
YS
Youssef SqualianalystTruist Securities
Mark, with the upcoming ban or sale of TikTok signed into law earlier today, how do you think that will impact the U.S. social media landscape? And then, in particular, what do you say to people who believe that this is potentially a slippery slope in terms of the government picking up — picking winners and losers? And Susan, how big is Advantage+ in terms of the spend on the platform and just in terms of its impact on overall CPM stabilizing?
observation#332
question#333
question#334
question#335
question#336
SL
Susan LiCFOMeta
Thanks, Youssef. We've obviously been following the events related to TikTok closely, but at this stage, it is just too early, I think, to assess its impact or what it would mean for our business.
To your second question on Advantage+, we're continuing to see good traction across our Advantage+ portfolio, including both with solutions, I mentioned this, that automate individual steps of a campaign creation setup as well as ones that automate the full end-to-end process. So on the single-step automation, Advantage+ audience, for example, has seen significant growth in adoption since we made it the default audience creation experience for most advertisers in Q4. And that enables advertisers to increase campaign performance by just using audience inputs as a suggestion rather than a hard constraint. And based on tests that we ran, campaigns using Advantage+ audience targeting saw, on average, a 28% decrease in cost per click or per objective compared to using our regular targeting. On the end-to-end automation products like Advantage+ shopping and Advantage+ app campaigns, we're also seeing very strong growth. Mark mentioned the combined revenue flowing through those 2 has more than doubled since last year.
And we think there's still significant runway to broaden adoption, so we're trying to enable more conversion types for Advantage+ shopping. In Q1, we began expanding the list of conversions that businesses could optimize for. So previously, it only supported purchase events, and now we've added 10 additional conversion types. And we're continuing to see strong adoption now across verticals. So generally, I would say we are building a lot more functionality into the Advantage+ tools over time. also where a lot of our gen AI ads creative features have been introduced and where advertisers have the opportunity to experiment with those. And we'll keep looking to apply what we learn from these products more broadly to our ads investments over the course of the year.
sentiment#337
observation#338
question#339
question#340
#341
strategy#342
strategy#343
strategy#344
strategy#345
strategy#346
strategy#347
risk#348
strategy#349
strategy#350
Q&A 7/9
OP
Operatoroperator
Your next question comes from the line of Ken Gawrelski from Wells Fargo.
KG
Kenneth GawrelskianalystWells Fargo
As you look out through the coming period of product investment, how should we think about the relationship between Family of Apps revenue and cost growth?
Is there any insight you can give us there? And then maybe just one that's a little bit more specific to the G&A growth in 1Q. You called out legal expenses. Just wanted to see if there's anything onetime in there that would cause the elevated growth in 1Q.
question#361
question#362
question#363
#364
context#365
SL
Susan LiCFOMeta
Yes.
On the second part of your question first, so on the G&A side, that was really driven by legal expenses. We recognized some accruals in Q1 related to ongoing legal matters, and you'll see more detail on that in the 10-Q. On the first part of your question, which is really about sort of the kind of long-term margin profile of Family of Apps, we aren't giving guidance on that per se.
But one of the things that we really have been very disciplined about over the course of 2023 and continuing is really operating the business in a very efficiency oriented way. So we're being very disciplined with allocation of new resources. This is a muscle that we really built over 2023 that we believe is important for us to keep carrying forward. And I think you'll see us continue to emphasize that, especially with the Family of Apps business being at the scale that it is.
strategy#366
strategy#367
operational#368
strategy#369
result#370
strategy#371
result#372
strategy#373
operational#374
Q&A 8/9
OP
Operatoroperator
Your next question comes from the line of Ross Sandler from Barclays.
RS
Ross SandleranalystBarclays
Great.
Mark, you partnered with Google and Bing for Meta AI organic search citations. So I guess stepping back, do you think that Meta AI longer term could bring in search advertising dollars at some point? Or do you view this as what others are doing, where you kind of attach a premium subscription tier once people kind of get going on it? And then the second question is, you mentioned that you guys are working on building AI tools for businesses and creators. So just, I guess, how do you see the business model evolving when we all get to the stage of interacting with something like Taylor Swift's custom AI for merchandise or tickets or something like that. How is that going to play out?
question#380
question#381
question#382
observation#383
question#384
#385
result#386
MZ
Mark ZuckerbergCEOMeta
All right. So yes, on the Google and Microsoft partnerships, yes, I mean we work with them to have real-time information in Meta AI. It's useful.
I think it's pretty different from search. We're not working on search ads or anything like that. I think this will end up being a pretty different business. I do think that there will be an ability to have ads and paid content in Meta AI interactions over time as well as people being able to pay for whether it's bigger models or more compute or some of the premium features and things like that.
But that's all very early in fleshing out. The thing that I actually think is probably — the biggest clear opportunity is all the work around business messaging. That's in addition to the stuff that we're already doing, just generate to increase engagement and ads quality in the apps. But business messaging thing, I mean, whether it's a creator or one of the 100-plus million businesses on our platform, we basically want to make it very easy for all of these folks to set up an AI to engage with their community. For a business, that's going to be able to do sales and commerce and customer support.
And I think it will be similar for creators, although there will be more of a kind of just fun and engaging part there, but a lot of creators are on the platform because they see this as a business too, whether they're trying to sell concert tickets or products or whatever it is that their business goal is. And a lot of these folks either aren't advertising as much as they could or, in business, the business messaging parts, I think, are still relatively undermonetized compared to where they will be. And I think a lot of that is because the cost of engaging with people in messaging is still very high.
But AI should bring that down just dramatically for businesses and creators. And I think that, that has the potential. That's probably the — beyond just increasing engagement and increasing the quality of the ads, I think that, that's probably one of the nearer-term opportunities, even though that will — it's not like next quarter or the quarter after that scaling thing, but it's — but that's not like a 5-year opportunity either. So I think — that is one that I think is going to be pretty exciting to look at. But yes, I mean, as Meta AI scales too, I think that, that will have its own opportunities to monetize, and we'll build that out over time. But like I tried to emphasize, we're in the phase of this where the main goal is getting many hundreds of millions or billions of people to use Meta AI as a core part of what they do. That's the kind of next goal, building something that is super valuable. We think this has the potential to be at a very large scale. And that's sort of the next step on the journey.
result#387
commitment#388
result#389
strategy#390
strategy#391
strategy#392
strategy#393
KD
Kenneth DorellirMeta
Krista, we have time for one last question.
Q&A 9/9
OP
Operatoroperator
And that question comes from the line of Ron Josey from Citi.
RJ
Ronald JoseyanalystCiti
Mark, I want to follow up on a prior question that you mentioned optimism has grown internally quite a bit just with all the improvements and investments and innovations you're making. And we're seeing that in the experience for a few days of Meta AI. So can you just talk to us maybe how the $400 billion parameter model just might evolve the experience on Meta or how you think things might change over the next, call it, months, years, et cetera, as maybe messaging becomes a greater focus and things along those lines? So just a vision longer term.
#394
observation#395
estimate#396
estimate#397
MZ
Mark ZuckerbergCEOMeta
Yes. I mean I think that the next phase for a lot of these things are handling more complex tasks and becoming more like agents rather than just chat bots, right? So when I say chatbot, what I mean is you send it a message and it replies to your message, right? So it's almost like almost a 1:1 correspondence. Whereas what an agent is going to do is you give it an intent or a goal, then it goes off and probably actually performs many queries on its own in the background in order to help accomplish your goal, whether that goal is researching something online or eventually finding the right thing that you're looking to buy. There's a lot of complexity and sort of different things. I think people don't even realize that they will be able to ask computers to do for them. And I think basically, the larger models and then the more advanced future versions that will be smaller as well are just going to enable much more interesting interactions like that. So I mean if you think about this, I mean, even some of the business use cases that we talked about, you don't really just want like sales or customer support chatbot that can just respond to what you say.
And if you're a business, you have a goal, right? You're trying to support your customers well and you're trying to position your products in a certain way and encourage people to buy certain things that map to their interests and would they be interested in? And that's more of like a multiturn interaction, right? So the type of business agent that you're going to be able to enable with just a chatbot is going to be very naive compared to what we're going to have in a year even, but beyond that, too, is just the reasoning and planning abilities if these things grow to be able to just help guide people through the business process of engaging with whatever your goals are as a creator of a business.
So I think that that's going to be extremely powerful. And I think the opportunity is really big. So — and on top of that, I think what we've shown now is that we have the ability to build leading models in our company. So I think it makes sense to go for it, and we're going to. And I think it's going to be a really good long-term investment. But I did just want to spell out on this call today, the extent to which we're focusing on this and investing in this for the long term because that's what we do.
observation#398
question#399
question#400
#401
context#402
strategy#403
competitive#404
strategy#405
strategy#406
strategy#407
strategy#408
strategy#409
strategy#410
strategy#411
strategy#412
strategy#413
strategy#414
strategy#415
context#416
risk#417
strategy#418
Closing Remarks
KD
Kenneth DorellirMeta
Great. Thank you for joining us today. We appreciate your time, and we look forward to speaking with you again soon.
#429
#430
#431
#432
#433
strategy#434
strategy#435
metric#436
strategy#437
strategy#438
context#439
context#440
strategy#441
strategy#442
strategy#443
strategy#444
context#445
strategy#446
strategy#447
strategy#448
strategy#449
strategy#450
strategy#451
strategy#452
strategy#453
Operator Sign-off
OP
Operatoroperator
This concludes today's conference call. Thank you for your participation, and you may now disconnect.