Release Date: August 01, 2024
For the complete transcript of the earnings call, please refer to the full earnings call transcript.
Positive Points
- Amazon.com Inc (AMZN, Financial) reported $148 billion in revenue, up 11% year-over-year, excluding the impact from foreign exchange rates.
- Operating income was $14.7 billion, up 91% year-over-year.
- AWS revenue growth accelerated from 17.2% in Q1 to 18.8% in Q2, driven by cost optimization, infrastructure modernization, and AI adoption.
- Advertising revenue increased by over $2 billion year-over-year, with more than $50 billion in revenue in the trailing 12 months.
- Prime Video continues to show strong performance, with significant viewership and critical acclaim, including 62 Emmy nominations.
Negative Points
- Foreign exchange rates posed a $1 billion headwind to revenue, higher than anticipated.
- North America segment operating margin decreased slightly due to increased Q2 spend in investment areas like Project Kuiper.
- Customers are trading down on price, impacting average selling prices and revenue growth in higher ticket items.
- Seller fees were lower than expected due to changes in seller behavior following recent fee adjustments.
- The macroeconomic environment continues to pressure consumer spending, particularly in discretionary categories like electronics and TVs.
Q & A Highlights
Q: There's been a theme during the last couple of weeks of earnings of the potential to overinvest as opposed to underinvest in AI as a broad team. I'm curious, Andy, if you have a perspective on that in terms of thinking about elements of capitalizing on the theme longer term against the potential for basic cadence of investment on AWS as a segment? And the second part would be coming back to your comments on custom silicon. How do you feel about custom silicon both from a pace of investment? And then more broadly, how you think about it as a return profile on a pivot to more custom silicon in your portfolio over the medium to long term?
A: Thanks, Eric. I'll take them in order. I think on the question about investment in AWS and on the AI side, I think where I'd start is, I think one of the least understood parts about AWS over the last 18 years has been what a massive logistics challenge it is to run that business. If you think about the fact that we have about 35 regions and think of a region as multiple -- a cluster of multiple data centers and about 110 availability zones, which is roughly equivalent to a data center, sometimes it includes multiple. And then if you think about having to land thousands and thousands of SKUs across the 200 AWS services in each of those availability zones at the right quantities, it's quite difficult. And if you end up actually with too little capacity, then you have service disruptions, which really nobody does because it means companies can't scale their applications. So most companies deliver more capacity than they need. However, if you actually deliver too much capacity, the economics are pretty woeful, and you don't like the returns of the operating income. And I think you can tell from having -- we disclosed both our revenue and our operating income in AWS that we've learned over time to manage this reasonably well. And we have built models over a long period of time that are algorithmic and sophisticated that land the right amount of capacity. And we've done the same thing on the AI side. Now, AI is newer and it's true that people take down clumps of capacity in AI that are different sometimes. I mean -- but it's also true that it's not like a company shows up to do a training cluster asking for a few hundred thousand chips the same day. Like, you have a very significant advanced signal when you have customers that want to take down a lot of capacity. So while the models are more fluent, it's also true that we've built, I think, a lot of muscle and skill over time in building these capacity signals and models, and we also are getting a lot of signal from customers on what they need. I think that it's -- the reality right now is that while we're investing a significant amount in the AI space and in infrastructure, we would like to have more capacity than we already have today. I mean we have a lot of demand right now and I think it's going to be a very, very large business for us. On the custom silicon point, it's really interesting what's happened here. And it's also -- our strategy and approach here has been informed by running AWS for 18 years. When we started AWS, we had and still have a very deep partnership with Intel on the generalized CPU space. But what we found from customers is that they -- when you find a -- an offering that is really high value for you and high return, you don't actually spend less, even though you're spending less per unit, you spend less per unit, but it enables you and free you up to do so much more inventing and building for your customers. And then when you're spending more, you actually want better price performance than what you're getting. And a lot of times, it's hard to get that price performance from existing players unless you decide to optimize yourself for what you're learning from your customers and you push that envelope yourself. And so we built custom silicon in the generalized CPU space with Graviton, which we're on our fourth model right now. And that has been very successful for customers and for our AWS business is it saves customers about -- up to about 30% to 40% price performance versus the other leading x86 processors that they could use. And we saw the same trend happening about five years ago in the accelerator space, in the GPU space, where the products are good, but there was really primarily one provider and supply was more scarce than what people wanted. And people -- our customers really want improved price performance all the time. And so that's why we went about building Trainium, which is our training chip and Inferentia, which is our inference chip, which we're on second versions of both of those. They will have very compelling relative price performance. And in a world where it's hard to get GPUs today, the supply is scarce and all the schedules continue to move over time, customers are quite excited and demanding at a high clip our custom silicon, and we're producing it as fast as we can. I think that's going to have very good return profile just like Graviton has and I think it will be another differentiating feature around AWS relative to others.
Q: In the second quarter, the retail gross margins that we're trying to do, the monkey math, look a little weaker than expected. Was there any extra pressure on retail gross margins because of discounting? Or is that where Kuiper is? Or sort of how do we think about some of the drivers of retail gross margins in the quarter at shipping? And the second one, Andy, in the past, you talked about cost to serve improvement and sort of getting the North America margins back to pre-pandemic levels. Can you just remind us again sort of the internal philosophy about executing on that? Is there a time line to deliver on that? Sort of how are you sort of balancing showing that profitability improvement over the next couple of years versus pressing on new investments like Kuiper and perhaps reinvesting some of those profits over the next couple of years?
A: Brian, let me start with the first question on North America margins. So if you look at the segment operating margins, we did decrease 20 basis points sequentially from Q1 to Q2. I'll remind you that we have seen the annual step-up in stock-based compensation at the end of Q1 each year, and that added about $1.8 billion of stock-based comp expense in Q2 versus Q1. So that's impacting, to some extent, all three segments. But even with that stock-based comp step up, the stores part of the North America segment, increased the margin again last quarter. So we're continuing to see strong improvements in cost to serve as well as improvement in speed, added selection, better safety. So a lot of the key areas that we're hitting on are strong. What you're seeing for the segment is that some of our investment areas had a tick up in expenses and investment in Q2 versus Q1. That's not unheard of. Q1 is usually the lightest investment quarter. Things like Prime Video and devices have less investment going on in those quarters. But the one thing I'd point out, I think we mentioned this, Kuiper stepping up a bit in Q2 versus Q1 as we start to build satellites that we'll launch in Q3 and Q4
For the complete transcript of the earnings call, please refer to the full earnings call transcript.
