The World Wide Web is unhealthy right now.
Most of the things on the internet are crap.
And they're crap, and we know that they're crap, but the SEO optimized crap.
So how do you de-crapify that?
AI agents can direct people to things if people start their purchase activities there.
Like Google, they kind of are a tax on GDP.
Consumer spending is a huge part of GDP.
They get a percentage of all that spend because they're charging per click.
That tax might just shift elsewhere.
Why is this system so complex?
What are the different types of purchases where AI can play a role?
And what are we hoping to see as we think about the broader market?
Today, we're talking about the future of commerce in the age of AI.
The web is flooded with SEO junk.
But what happens when AI agents start directing how we search, shop, and buy?
Joining me are Alex Brampell, general partner at A16Z, and Justine Moore, partner at A16Z.
We discuss how AI could disrupt e-commerce from impulse buys to big-ticket purchases, and what it means for Google, merchants and startups.
Let's get into it.
So you guys have both been thinking about e-commerce for a while.
Alex, why don't you talk about what inspired this piece and how did this all germinate for you?
Well, so I had started a company called TrialPay a long time ago.
And actually I'd been selling stuff on the internet for a very, very long time, even before the internet.
And I was just trying to think, well, number one, what happens to Google?
Because a lot of people, this is on their minds.
So like, is search volume going up or down?
So I have my own personal experience of like well, my search volume is going down, but not for commerce, but clearly for everything that is not commerce.
So that was one thing.
But also, this company that I started, TrialPay, we were one of the biggest affiliates in the world.
And affiliate marketing is basically you send somebody.
This is the oldest business model on the internet, if you will.
It actually predates AdWords and AdSense by a bit of.
You just get a share of the.
You get a commission, basically if you send something there.
It was all this was started, apparently apocryphally.
It came from pornography, because that was the world's oldest business model on the internet.
Like, how do you track?
So that eventually made its way to commerce, and it's all based on cookies and pixels.
So you drop a cookie on the person's computer and then on the confirmation page you have a little like invisible one-by-one tracking pixel that reads the cookie and that's how you know to say Eric sent me the customer.
So what we did at TrialPay, we were one of the biggest ones there.
Like, is that really going to be what powers this new realm of commerce?
And then is it even relevant for a lot of things?
Because impulse buys are huge.
And with impulse buys, almost tautologically, you're not going to use AI to tell you to buy something.
You shouldn't buy anything that's an impulse buy.
You go to the supermarket, you shouldn't be buying Coca-Cola in the checkout line.
They actually charge you more at the checkout line than they do if you just buy in the Coca-Cola section.
So all of these things are designed to tug at your emotions, to get you to buy and spend money that you don't want to.
That's not going to be AI.
On the other hand, it's like these very, very expensive items.
You're researching the heck out of them with AI, but there's no affiliate model.
How do you then commerce and transact?
So number one was the ontology of commerce was very interesting.
And then number two was this whole affiliate thing.
Is it still going to be relevant?
Because it seems like that's what ChatGPT and others are getting into.
And then number three was just my own personal behavior.
It's just like I probably use ChatGPT three orders of magnitude more than I use Google now, which is interesting.
Justine, what excited you to contribute to this piece?
What did you find most remarkable?
There's a couple of really massive consumer markets, the biggest of which might be online shopping.
But I think we've seen thus far relatively few startups trying to take a crack at that market with AI, even though, like Alex said, there's a lot more opportunity because you now have these really smart LLMs and agents that can help you make better decisions than you could have made on your own, or even make purchases on your behalf, which you would think would create an opportunity for more folks to package these into products that they then offer to consumers.
But we haven't seen a bunch of folks doing that yet.
So I think part of this piece was to dive into like we think about the broader market in hopes that you know folks were also who are working in the space would kind of give us a heads up and let us know and we could hear how people were approaching it.
And you can observe.
I always like to like observe first because like that's objective.
And then predict second.
Predicting is hard.
I forgot the funny quote about predicting the future.
But it's very hard to predict the future.
And like there actually is a lot that can be observed.
And like that's where like I think camel, camel, camel is like the greatest sign in the world.
We have no stake in camel, camel, camel.
So this is not self-promotional at all.
But it's like people use this thing.
It's like Google News alerts for pricing.
Yeah.
And I gave a talk to the Amazon Prime team recently and they're very, very aware of it because I think it's actually Amazon's biggest affiliate.
And people every day are like, I would buy this product.
I mean, this is like Econ 101.
I would buy this product if it was priced here.
It is currently priced here.
Please let me know when it is priced here because what will I do with that information?
I'm going to buy it.
So the consumer is the agent, and this is like a very, very inefficient AI.
And if you could actually complete the entire circle and say no longer give information, but allow for automatic action on information, people will do that because we have observed that behavior today.
This is the easiest form of predicting the future ever, because you're really just chronicling the present.
And you're just saying there's going to be one additional appendix to the present, which people would do anyway, because they are doing it anyway.
They just have an easier way to do it.
I think my version of observing was seeing.
There's a couple viral examples of this, some that were really good because the AI found the product perfectly, and some that were hilariously bad because AI couldn't find the product.
But teenage girls started using ChachiBT to upload photos of, like Lana Del Rey at a concert, or Taylor Swift like snapped in a street style photo or whatever, and asking like what is this hair bread she's wearing?
Or like, what is this sweater?
Like...
I want to find it and I want to buy it.
And it worked really well because it often found like, hey, this sweater is like $5,000.
Like you as a 19 year old girl in Missouri are probably not going to be buying this.
Like here are some alternative, maybe less expensive options that look the same that you can buy.
And that age demographic tends to be like a really early predictor of all sorts of consumer behavior, which is why I was.
You know this is probably going to be happening more and more from the research side of things, all the way to making purchases, probably agentically, when prices are right, like Alex was mentioning.
Alex, you imagine a world where there's sort of dynamic custom pricing, sort of to the extreme, where it's like we're looking at the same thing on Amazon, but it charges you more because maybe I'm cheaper than you or you have more money.
Do you imagine that world?
Well, I mean, people have tried this a lot.
I mean the problem.
I think this probably it's a very smart world from an econ 101 perspective for sure.
Like, how do you capture the consumer surplus?
Consumer surplus is great for consumer.
It's bad for producer.
And apparently Delta is doing this a little bit, or they were trying to do this.
I mean, there are like the poor man's versions of this which are like if you have an iPhone, you should get charged more than if you have an Android phone, because iPhones are more expensive.
You have basically communicated that your elasticity of demand is different than somebody who has less money.
I think probably you're going to run into regulatory challenges with that, or certainly you will run into very, very high levels of unpopularity with your customer base.
But people have tried this.
But generally, it's hard to get away with.
Right.
Let's reflect on previous platform shifts before getting into this one.
Right now, e-commerce is 16% of total retail sales.
If we were talking 20 years ago and predicting what percentage of e-commerce, we would probably think it's much higher.
Why hasn't that been the case?
It turns out the demand curve is different for immediacy versus non-immediacy.
So, even though overnight shopping is pretty darn cool, instantaneous one-second shopping is like I need toothpaste right now because I'm going to bed and I want to brush my teeth and I just ran out.
Oh, there's a Walgreens over there.
I'm going to go there and buy toothpaste.
And Amazon's awesome, but getting the toothpaste at 7 a.m., it's like, I don't have demand for that.
That's not part of the demand curve.
There's demand curve for real-time toothpaste.
That's part.
The other part is just like, I'm bored.
Like, what do I do today?
I know I will go to the shopping mall.
And like, there's the experience of doing that.
And it's like that's kind of a little bit more impulsive.
Like, Maybe I'm going to gawk at that Rolex a little bit more and, ooh, I just got my bonus.
Maybe I'll go buy it.
But it's all part of the experience.
So I think those are kind of broadly speaking the two.
I mean, I've seen this.
I'm on the board of a company called Wise, and the product is sending money.
And it turns out that the market for sending money where it is received in real time is just much, much different than the market for sending money where it is received two days later.
Because sometimes it's just like the two days later send thing is just like – less demand for that.
And again Amazon has proven this.
As shipping has become, it's like once upon a time, like when you go back to the early days of e-commerce you would get something in like two weeks.
So it's almost not surprising that the curve has just continued to expand.
It's almost surprising that it's only, you said, 16%?
Yeah.
That seems very low.
I think it's higher.
So I'm not doubting your research on the numbers.
Here's why I think it's higher.
I think there's a lot of behaviors where people do research online and then purchase in person, especially for big sorts of purchases.
Or even sometimes I'm like, hey, I need a new laptop.
I'm going to do all of the research on Reddit or on...
Instagram or on the Apple website.
But then I'm gonna like go into the store and feel like okay, what is actually the difference in like the pro weight versus like the MacBook Air weight?
Right, and so I think there's a lot of those sorts of things where like or buying clothes is another great example where, like I live in SF, so a lot of people will just order a ton of clothes, try it all on and then send a ton of it back because there's not a lot of big stores near us.
But I grew up in Oregon and there like, It doesn't make a ton of sense to order a ton of clothes online and send them back.
It's just inefficient when there's so many clothing stores that are like a five to 10 minute drive from you.
But a lot of people will kind of do research about where to go or what specific items they're looking to find or, like what style they're looking to buy online.
So I think, yeah, it might be like 16% are like fully transacted online.
But I think there, even in a lot of those other purchases, there is some sort of online research component.
Well, this is actually the hardest thing that's related to this topic, is attribution.
It's the bane of everybody's existence, which is like okay, how do I allocate attribution for Justine's MacBook sale?
And the most...
The most kind of pervasively corrosive business model.
I think on the internet is this like last click attribution.
So you allocate 100%.
It's like, okay, part of it was like, I read this post on Reddit that kind of inspired me.
Part of it was I saw this really cool ad at the Super Bowl.
Yeah, you could do this like kind of piecemeal, which is probably the more accurate way of doing it, but it's not exactly deterministic.
And the thing that feels deterministic, which is actually incorrect, is it's like oh, whoever sent me the click last is the one that I should reward with the spoils.
And a lot of people that just don't understand correlation versus causation fall into this trap where and this is the business model that I hate the most in the entire world like the things like Honey.
You know Honey, right?
So what is that doing?
It's like you're already on the webpage about to purchase.
And then it's like, do you want a coupon code?
Yes, I do.
Why would I not want a coupon code?
10% off, click here.
You go click here.
What does it do?
It redirects you to an affiliate page.
It puts a cookie on your machine.
It redirects you back to the page that you were just on, and then it actually steals that attribution.
And what's funny is if you talk to a lot of the marketing people at these larger e-commerce companies and Amazon is very smart.
That's why they don't do any of this stuff.
They're like, oh, our best channel by far is Honey.
They're growing so much.
Or RetailMeNot, that was the original one.
It went public, big valuation, and it was just theft.
But it's just because, again, how do I figure out how to do attribution?
And this is only going to get more complicated in the AI world, where it might be the same thing, where it's like Justine might have.
Researched on Reddit, saw the Superbot did all of these things, asked a question on ChatGPT and then clicked purchase.
And it actually is incorrect for Apple to say oh ChatGPT, we owe you the entire that drove the purchase.
No, it didn't.
It's part of it, but it didn't drive the purchase.
And figuring out and disentangling attribution is very, very hard.
Let's reflect back on the category as well.
It seems like the big winners have been at the aggregator level with Shopify or obviously Amazon and sort of the individual big brands like, I don't know, Allbirds or Casper.
It seems like they were quick to get a lot of revenue but didn't become durable businesses.
In the same way, didn't get better as they scaled.
Why don't you reflect, Alex, a bit on the category in general and why it's played out that way?
Well, I mean, ultimately, if it's a one and done transaction, you don't really make the product.
Like Casper didn't make the mattress, right?
Like there's probably some OEM in China that made the mattress and they put their little logo and they called it Casper on it.
Well, then they're just buying, they're buying traffic on Google and Facebook.
So actually Google and Facebook were the real victors there, more so than anybody else.
And then people were like, wow, mattresses, that's a really good category.
I should do that.
Oh, I'm going to go to Shenzhen or wherever.
I'm going to slap my logo on it.
I'm going to undercut them on price.
And that's what always happens.
And it's one thing of you can ameliorate this to a certain extent if at least you have recurring billing.
It's like, I'm going to have this problem.
Think about what Dropcam did, if you remember that.
That was an e-commerce product, but at least it was attached to a subscription.
Right.
So now there are like 9 billion cameras that all do the exact same thing.
So that category has arguably gotten worse, even as the category has expanded or the demand has expanded.
But at least Google owns Nest, which bought Dropcam.
They probably still make a lot of money on that category.
Whereas Casper, if I bought a Casper mattress five years ago, I'm still sleeping on it.
And they have to find new people to sell that mattress to.
And meanwhile the original factory that was making the mattresses is now selling the exact same mattress to 5000 other manufacturers.
And it's just not a good business model.
So in general, just being a commodity reseller of products, and I think this is the problem.
A lot of people will say, oh, well, Casper is its own mattress.
Allbirds is its own shoe.
But like...
Like, they're not normally making these products.
Like, there's somebody else that's making the product.
Because it's almost obvious, like what happened during intranet 10, the long tail of commodity resellers went away because location no longer mattered.
Because a lot of what really drove retail for the longest time was that, like in Justine's town in Oregon, like there's this store and like you could drive like somewhere else, but that's really far away.
So of course you're going to go to this store.
Now the intranet, you can go to any store.
So if there are like 5000 stores that don't make their own products and they all sell the exact same shoe from Nike, that doesn't make sense.
You should either go to Nike directly or you should go to like the one store that has the fastest shipping, the best service, whatever.
And like the long tail of commodity retailers basically started dying.
And like we saw this play out.
Yeah.
But the first party commerce experience is not that much better either, because it's like the actual like there's no barrier to entry.
And if there's no barrier to entry, then that normally doesn't.
It works out great for the consumer in capitalism.
It doesn't work out great for that.
You know one of N, where N is quite large producers of or non-producers, but just marketers of the product.
I think there's also, especially with true consumer products and I would consider a mattress maybe more of a utility product, but with shoes like Allboards or makeup, it's very trend-based, especially with the internet.
Nothing stays that hot for that long.
Allboards is the big shoe one year, and then the next year, it's the retro Adidas that everyone's going back to, and now it's the on-running shoes.
I was watching the the Bama Rush sorority TikToks this year and, like every single girl, has the on-running shoes, whereas last year they all had the New Balance.
Like cool look from Japan.
And if you're all birds, like, that's a problem, right?
Because you can't capture all of the trends.
Like you have your kind of one SKU or multiple SKUs across one style whereas, like the Shopify's and the Amazon's, can kind of ride whatever the trend is and have demand come to those individual SKUs, which I think is going to be an interesting challenge in the age of AI too, because you could argue that AI agents can direct people to things if people start their purchase activities there, which could be an opportunity or a challenge for the single SKU retailers.
My guess is it'll still end up being more of a positive for the aggregators.
Also, I think it's going to be very hard for AI to, for lack of a better term, inculcate demand.
Yeah.
Which is like, how do I know that the on shoe is cool?
It's like, well, I need to see that, Bama.
Yeah.
I'll send you some.
I meant like, I need you.
Yes.
I mean, it's a metaphorical I, right?
It's like, once I see, oh, wow, I should have that too.
Right.
I'm in a sorority.
I want that shoe.
Yeah.
And it's very hard for AI to do that.
Yeah.
So which is why like the utility part of it's like, well, I know what I want, now buy this for me.
Like that seems like a no-brainer because that's a lot of what Google does.
Like Google.
I mean, I respect the hell out of that company, but they kind of are a tax on GDP, right?
It's like a lot of GDP happens, a lot of that is commerce, right?
A lot of consumer spending is a huge part of GDP.
Where do you start that spending journey with that little nice little search box?
And then they get a percentage of all that spend because they're charging per click or per impression or per action.
So that is somewhat imperiled.
That tax might just shift elsewhere.
Yeah.
Let's flesh out the piece now.
Let's get into what are some of the things that are going to be taken away from Google.
What are some of the things that are going to stay.
I also want to get into the different kinds of consumer spend as it relates to e-commerce.
Maybe, Alex, do you want to start with you?
Yeah, I mean.
Well, I think Google has been the canonical freemium business model forever.
Which is they built a better search engine.
Everybody knows that.
It started in 1998, and there was like the 47th search engine or something.
Ah, this isn't going to work.
But it was just so much better because of the way that they linked it.
It really kind of goes actually back to like research, which is like it's kind of like the H index, but for finding things.
Oh, everybody...
Like, when you search for bagel, everybody, like, hyperlinks to, like, this one site.
Like, that must have a high page rank.
Like, let's go show that first.
But most of the search is when Google started, because commerce was actually quite nascent on the internet at the time.
Like, it was all free.
It was all kind of information.
I remember using Google when it first came out and it was like oh, this is so much better than Hotbot and all the other things out there.
It was all free, non-monetizing.
They eventually basically copied the Overture business model which this guy, Bill Gross, came up with.
This was an Idea Lab company that eventually became part of Yahoo.
This is why Yahoo ended up owning part of Google, if you know the whole history.
And the entire thing that made Google this giant $2 trillion company was AdWords.
And actually the cool thing about it is that there are a lot of freemium business models where it's like ah, I don't want to pay for it.
Here it was freemium, but actually having relevant search results that are paid alongside search that is organic made the search better.
Like if I'm searching for tennis racket and somebody hadn't figured out how to page rank optimize and everything else, or SEO optimize.
It was very useful for them to be able to show ads here.
And then those ads wouldn't show up unless people clicked on them, because the relevance was never preordained.
It's like if people click on it, it's relevant.
If people don't click on it, it's not relevant.
So Google has always been freemium.
And that's kind of bearing out right now, which is like it's still freemium.
You search for lots and lots of things with no intent to buy.
But every now and then, it's like this is your default behavior.
It's like, hmm, I wonder about X. You go to Google.
Or sometimes you don't even go to Google, you go to Safari, because Apple makes tens of billions of dollars a year by sending all of those searches to Google.
So what is currently happening is they are starting to lose some of the free, but not any of the imium.
Right?
They're losing some of these informational queries, like, who won the Oscar in 1977?
Like, that's not a monetizable query, but, like, that's what you're going to want to know.
You're going to just ask ChatGPT, and people are doing this right now and ChatGPT has, you know, I think.
What is it?
800 million weekly active users.
A huge, huge number.
That's what they're doing with it, because they're not buying in ChatGPT.
We know that, because...
OpenAI is trying to build commerce, so clearly they haven't built it yet, so they're not buying directly in there.
But for the imium, the premium part of the freemium, that is happening in Google still.
And how do I know that?
Well, I can look at their financials.
And their financials.
The numbers are still going up, but we also know that search volume is actually going down.
So what are they losing if they're not losing revenue?
They're only starting to potentially lose some of the free searches.
And maybe they're, what I don't know is maybe they're directing some of those to Gemini.
But I think that's unlikely.
I think right now what's happening is it's like people are using paid for Google, no changes at all.
They're just going elsewhere with AI for free.
I think part of probably why that's been happening is like all LLMs but I'll use ChatGPT as the example because the most people use it had this really unfortunate and annoying problem of hallucinating around product recommendations that basically everyone experienced if you tried to use it for that.
I think you have this grand idea of like okay, I want to buy a pair of leggings and I'm going to go search in Google or I'm going to go search in Amazon and then I'm going to get the highest ranked pages.
But what I really want to know is I'm doing this specific type of hiking and this is what the weather is going to be like, and I want to know, specifically for my needs, what is the best legging?
It might not be the best overall legging, right?
And so a lot of people, I think especially I saw a lot of young women trying this were like great, I'll go to ChatGPT.
It can take all my information in natural language.
It can make a recommendation.
It can spit out products.
And then they would find that a lot of the products it recommended did not exist or previously existed, but did not exist in a current form, or the amount that they were charging was way different than it said, which I think drove a lot of people who experimented with it sort of back to.
You know, I'm going to return my searches to Google or Amazon and wait until ChatGPT figures out this commerce thing.
My take is people are like, as we know, OpenAI is working on commerce and they're trying to integrate it more into the experience and have actually like real relevant, up-to-date information on products.
Google will probably be at risk of losing some queries.
But I totally agree with Alex that we have not really seen that behavior at any sort of scale today.
Well, the biggest problem right now for the internet writ large is, I would say, the and I remember I've talked to John Lilly who was the original.
He was the CEO of Firefox back in the day and kind of an early web stalwart.
The internet is, or the web, the worldwide web is unhealthy right now.
Everything was just on the open web.
There was no concept of a walled garden.
I mean, like search has already been fractured, by the way.
It didn't happen with ChatGPT.
It's like, if you want real-time search, you go to Twitter or X.
You want search for your friends?
Well, you go to Facebook.
None of that is on.
You can't search for Google in terms of stuff that's happening amongst your friend group.
That's walled off there.
So you have all of these different walled gardens.
So that's unhealthy part number one.
Unhealthy part number two is just the commercialization of the internet, which is not bad.
I'm a capitalist.
I like commercialization.
But so much of... If you look for what is the best sneaker...
Like, who are the people that are writing content about great sneakers?
Like, in 1995, if you had a blog, well, number one, you just hosted it on your own site.
You set up Apache on your own server.
That you racked yourself, and then you just did it for the love of the game.
And then affiliate links provided the monetization model, but they really polluted the internet.
That was still open because, like so much is like oh, top 10.
Like, a lot of these top 10 sites are out there.
It's like top 10 running shoes.
You know what that is?
That's top 10 affiliate revenue to me.
And I pay somebody in India to go write gobbledygook and then SEO the heck out of that to make money.
Contrast this with, like pre-internet, where there's a publication it's still around today called Consumer Reports.
And the really cool thing about Consumer Reports is they were the only publication that refused to take advertising.
It was entirely subscription-based.
And the idea was that you could trust the actual reviews.
And they would do things like they were, like the Ralph Nader of consumer products, where it's like.
You know, this thing is terrible.
Don't buy this blender or it'll chop off your finger.
Like, do buy this thing.
Like, they would really, really review everything.
We kind of need that.
And that entire business model just went away.
Craigslist killed almost all of traditional media.
Maybe they deserved to die, maybe they didn't, but they made money from two things.
They made money because they had a monopoly on information.
They charged for ads there, but a big part of the monetization model was the local classifieds.
All of that went away, which is why newspapers have been dying.
And you could imagine a newspaper would have a do-gooder thing where it's like oh, let's review all the blenders.
And we're obviously not going to show blenders that cut off your fingers.
That's bad.
That whole thing went away.
So the summarization of the open internet is tough because there's less open internet than there used to be as a percentage of all the content being generated.
A lot of it is walled off.
And then the stuff that is not walled off is just pervaded by junk.
And that's why what we talk about in the piece is you can't turn shilled junk into honest analysis.
So I don't know how we solve that.
Like no matter how good, like no more hallucination, like everything is awesome.
But like most of the things on the internet are crap.
And they're crap.
And we know that they're crap, but the SEO optimized crap in order to earn affiliate commissions.
And like summarizing that crap is not helpful.
So how do you de-crapify that?
And that's quite challenging.
I think honestly, what I've seen in terms of the channels where you see the least crap is actually video.
Because if you're a creator now, it's due to the death of traditional media.
There's now creators who go out and review 10 different shoes for running, and we'll specifically make it very clear in the video either this is sponsored by this specific brand or the better ones obviously, are completely non-sponsored.
But they get ad revenue from Google, from YouTube, from people watching the video.
And so honestly, when I want an honest review of, like someone has looked at, five different blow dryers for this sort of hair, I will go to an unsponsored YouTube video, which often have a lot of views, because there's a lot of people having similar queries.
But the sense I have is that Google is not, because it's a video and it's not skimmable, and they're not automatically generating transcripts for every video.
That information does not appear in traditional search.
And I think we're starting to see some companies say hey look, we should turn all of those high-quality videos into transcripts that an LLM can then read and review and make recommendations.
But that doesn't seem to have hit the traditional Google part of the internet yet.
Yep, I agree with that.
Yeah.
New York Times recently bought Wirecutter, which may be an example of what you're talking about.
Well, but I think, yes and no.
I mean, it's like everything's affiliate linked.
Like, is it really true?
Like.
It's so suspicious that, like almost every item that they recommend, always has an affiliate link.
Yeah.
Isn't that odd?
Yeah.
Right, like, does that mean, like, you know, is that, like, a sampling bias thing?
Is that true?
Like, so I'm quite skeptical of a lot of these things.
And again, like, the Consumer Reports era was just a little bit different.
I mean, you might have the biases, like maybe the person reviewing things for Consumer Reports like just hates this one company and is taking out their bias.
Like, this is always possible.
But you would think, with all these algorithms and everything else, if you could get like true objective feedback, this would be fantastic.
I mean, a lot of, I mean, Amazon actually is a giant search engine.
Right.
And like that thing is polluted to crap as well, because what happens is a lot of the sellers on Amazon.
What they do is they go on this site called AliExpress.
And AliExpress.
I mean, this has changed a little bit with tariffs, but like they'll buy like 400 of some gizmo that shows up six weeks later and they'll buy it for 2 each.
They'll slap their logo on it, now they'll sell it for $25.
It actually goes back to this latency point that I was making before.
Like how many people want something six weeks from now versus how many people want something tomorrow?
So a lot of what Amazon was is they would just arbitrage that.
Turns out they're very useful.
There are like 9000 different pairs of heated socks that all have the same OEM, the original equipment manufacturer.
And it's like, And they all have bogus reviews.
And part of the bogusness, and Amazon should fix this, but they have no incentive to do so.
It's like I used to sell a rock on Amazon.
I get five-star rock reviews.
Now I switch the skew from rock to heated socks, and I trade off my five-star review.
And it's like, how does Amazon, and again, Amazon just wants to sell more crap.
So like they're totally fine with this but, like most things, if you're willing to wait, you're so much better off buying on AliExpress than Amazon.
And it's just like this polluted sea of crap.
Like my favorite business model for commerce by far is Costco.
I think Costco is the greatest company in the world because Costco refuses to sell bad things.
They refuse to take a high gross margin.
Like why would they refuse?
It doesn't make any sense.
Why would they refuse to take a high gross margin?
Know why?
Do you know why?
Because they want pass back to customers.
No no, it's because it degrades the value of the membership.
They make money from the membership.
So they'll charge you like something like 100 a year to join costco and if you look at their net income, it's basically the number of memberships that, like they have like 50 plus million members, it's some huge number times the price of the membership.
That's their net income.
And then everything else just kind of is a wash.
And if you are making a 50 gross margin on a shirt, they're like that's too much.
You're fired.
Like, you can't make that much money.
It devalues the membership.
So, I mean, they'll do crazy things.
Like, you know, the hot dog is still $1.50.
They started their own chicken farm because the rotisserie chicken like the costs were going too high.
It's like, that's how they run the business.
And they refuse to sell anything that they are not proud of.
And the generic brand is just as good, like you know, Kirkland wine, Kirkland beer, Kirkland shirts.
They're getting sued by Lululemon right now because they made pants that were better than Lulu's pants that are much, much cheaper, but they're actually much better.
So Costco is the greatest thing.
And like.
That's why Costco has been like the like for everything we talked about in commerce like pre-internet, like internet AI, like Costco is immune to all of this because it's like.
They're like the consumer reports plus like the like.
It's just they treat customers incredibly well.
And that's why this company is worth hundreds of billions of dollars today.
And people really trust them.
My mom has been a Costco member for forever, and now she gets her glasses at Costco.
Every time I want to go get flights or something, she's like, log in and use the Costco thing.
Because she always thinks that Costco is going to have the best option at the best price, and she's usually right.
That is sacrosanct to them.
They refuse to violate that because they can make so much more money if they decided to.
And Amazon.
It's interesting because, like normally, I remember, there's a speech by Jeff Bezos where he talks about this.
Like, you know, there are two business models.
There's like how, what's the most that we could get away with in terms of charging?
Like that's Apple.
It's like oh, let's charge 1600 for this iPhone 25 that we're going to come out with, that has 18 cameras.
Can we even get away with $1,700?
They have very high gross margins.
There are other companies like, how do we charge the least amount possible?
That's kind of Amazon.
Let's have this sea of crap, but whatever.
Why would we curate the crap?
That's up to the consumer.
We'll have the reviews and everything else, but they don't do a great job on the reviews.
And like, those are the extremes, right?
Like, you know, Android and Apple are like, you know, there are so many examples of this.
There's like the Premier provider, right?
There's like the Mercedes, the Ferrari, whatever.
And like, they just want to show like high-end stuff.
And then there's like the mass-produced, like, you know, low-end stuff.
And then there's this very, very unique business model that is very hard to replicate called Costco, because normally it doesn't work, Because it's like hey, just trust me because I'm the best.
Well, you have to have like many, many decades of trust, such that Justine's mom is like I don't know what it is, but if it's sold at Costco it's good.
Yes.
And if you were CEO of Costco, would you further leverage that trust to do other things, or would that risk the whole enterprise?
I think it risks the whole enterprise, but there's a lot that they can.
I mean it's funny.
We've met with the one of my partners, met with the Costco board and like pitched them on financial services, because it's like you know what.
Everybody's trying, every bank is trying to rip you off, right?
They're trying to overcharge you for loans or like underpay you on your deposits.
And like the Costco loan would just be like the cheapest possible.
Like they're trying to make no money on that because they make money on the membership.
So they probably could expand it quite a bit.
But yes, it's hard.
There's some modernization that they could probably do, because it still is this very warehouse thing that like closes at 5 pm and I wish it were open later and everything like this.
And like their shipping isn't great if you want to order stuff.
But it is a very, very unique business model that is somewhat of a, it will stand the test of time.
And I think it's AI proof.
Yeah.
Justine, why don't we get into other ways in which AI will change commerce?
You outlined a few different types of purchases that they might get, Ian.
Yeah.
So we kind of looked at the range of purchases from like the impulse buys which I think used, I mean still, they still are like the Coke thing, the Coke bottle on the aisle.
But often now for like a lot of people.
They're like the TikTok shop thing where you're watching a video and it shows up and you're like that t-shirt looks cool.
I'm going to buy it.
All the way to like really considered purchases like a house or like a wedding venue or like a car, where you're spending like a significant chunk of your income.
It's like a one or a multi-time thing.
And you're like doing a lot of research.
And I think the, so both ends of the spectrum, I think are harder for AI to disrupt.
I think the impulse buy because, like there's no research in advance and you're not going anywhere specific to buy it, like by its nature, you are making the decision to buy it immediately when you see it.
And so you know algorithms will get better and better to target you with the shirt that shows up on your TikTok feed that somehow has your dog's name, and you're going to buy that more than the other thing.
But that's sort of not the generative AI that we're talking about.
And then sort of the most consideration end of the purchase.
I think it's hard to have that be fully AI end to end.
Because, while you may start doing your research online on ChatGBT or Gemini or any sort of new AI native property that shows up, the purchase is so significant that you're probably going to want to have some sort of in-person experience where you're seeing the thing, touching the thing, experiencing the thing, talking to another human expert about it, right.
And so that means there's this whole range of products in the middle that I think we believe the purchasing behavior could be disrupted by AI in a couple of different ways.
So one is obviously like the research way of.
Like you know, I'm trying to find the best my handbag wore out that I bring when I travel all the time.
Like I need the best one that fits a laptop can fit a big water bottle.
All this sort of stuff can be fine in the overhead part of a plane.
And if you're busy you don't have a ton of time to do that research yourself, and you might ask an AI agent that can watch all the TikToks for you, read all of the Reddit posts and pull in the kind of real consumer feedback and then make a recommendation.
And you might want to do some of your own sort of clicking through to look at options.
But I would say in that case it's like decently likely that if there's then a good integration to purchase, you might do it through an AI agent.
There's also sort of just things you already know you want, like Alex has mentioned, where you want the best price.
And so I think AI agents can do a lot around price optimization.
Like if you always buy a specific type of laundry detergent, it can find across the internet where is this laundry detergent best priced?
And it can also probably know, hey, I should scan this daily.
And if it's 30% less on this specific site than it usually is anywhere else.
And it's going to arrive in a reasonable amount of time.
I should probably just buy this and they can store an extra box of laundry detergent because, based on what I know about the consumer, that's worth it to them.
As you move sort of up the consideration stack, there's another sort of purchase that I think will be sort of AI intermediated but maybe have some human impact.
Things like maybe bikes or couches, like a little bit of higher value purchases laptops, where you want to feel like someone has taken the time to really understand all of your criteria and help you make the best decision about what you should buy.
This is probably an item that you're going to be using for years and it's important to you that it works and that it's the best option and doesn't kind of immediately become obsolete.
And today, I think the only way that this has happened is people will go super deep into these Reddit threads on the Buy It For Life forum and all of these different places, or they have a brand they really trust, like Apple, and they're willing to pay the premium.
I think in the future it's fun to think about having an AI agent that really kind of deeply understands you, where you can have a more in-depth conversation about that sort of thing, like maybe even a phone call, where they're asking you a bunch of questions, dynamically back and forth, and providing them with the information they need to go back, do the research and decide.
So that's kind of some of the things that we've considered about how AI could impact purchase behavior.
And there's another kind of lens.
There are many different ways of cutting this but, like does the product that you're buying have a UPC or no?
UPC is a universal product code, and that's the little scannable thing.
It's kind of the successor to the ISBN, which is for books.
And if it doesn't have a UPC, actually a lot of the commerce that has worked.
Kind of post-Internet 10, like you know how did Wayfair work?
Why did Wayfair work well?
Well, like, they're selling things like bar stools.
You know, like, I want a bar stool, but there's no UPC on this.
So it's like, well, here's a bar stool.
It fits the right dimensions, but there's no scannable code.
If there is a UPC, you can run this little algorithm of get me the lowest price.
And pre-AI, you would just run this algorithm on your own, and you'd probably end up at Amazon.
So everybody who was in Amazon just got killed, and Amazon did well.
I'm oversimplifying a little bit.
If it doesn't have a UPC, then that's a little bit of a different process than if it does.
Because if it has a UPC, then the algorithm that I was describing is exponentially better with AI.
Because, before you'd have this, some people value time more than money and some people value money more than time.
And if I value money more than time, I am the algorithm.
I need to find the best coupon.
I need to find the best cashback site.
All of these cashback sites are out there on the internet which lots of people money more than time they do this.
All of that will be automated away or automated for the benefit of the consumer if, and only if, you have something where you have determined the SKU or the UPC.
The SKU has a UPC, you feed it in there, good.
If it doesn't have that, then that's another lens where it's like okay, I'm probably I can't feed whatever, like again kind of impulse to highly considered.
AI is going to help you on the highly considered side, but not help you buy it.
But if it spits out something with a UPC or a SKU, then this part of the AI will just automate that.
So if it's bike, sure, I don't know what bike to buy.
But if it's a specialized bike and here's the thing, it has a UPC on it, boom.
Why wouldn't you feed it to this part of the thing as this gets developed?
Because that's just going to buy it for you with the best shipping, the best terms, the best whatever.
And right now, the reason why that doesn't happen, it does happen, but it happens manually.
And the people that have time valued more for them than money.
They don't do any of that stuff.
Putting this all together, we were talking about how, over the last decade, there hasn't been a ton of net new, you know big winners in the space, and all the gains have gone to the aggregators.
Why why do we believe that over the next decade there's some opportunities for for net new big, big and durable companies and and maybe the share what, what types of companies those could exist that we're excited about, that that could exist?
I mean obviously, ChatGPT is.
I mean they are an upstart to a certain extent, but it's not Amazon, it's not Shopify.
It's a net new company that clearly will have a role in commerce.
The question is, will there be specialized subsegments?
And I do think that the hyper-optimized I know you very well and Camel Camel Camel is an independent company that's probably very, very profitable.
As far as I know, they've never raised venture capital.
A lot of people use them.
A lot of these cashback sites.
These things that have always been like, you value money more than time.
There was a site called Ebates that was bought by Rakuten a while ago.
There's a company in the UK called Quidco, which is very, very similar.
These kind of things.
You can imagine them going much, much more mainstream and being very, very specialized shopping agents, particularly not on the heavy research side, but on this one little tiny vector that might actually be very big, going back to how most companies can't really figure out attribution.
It's like, we are going to be the last click.
The last click of the 21st century post-AI is going to be AI companies that know how to do this, And it might not be ChatGPT because they're like this horizontal everything, but it's like, I'm going to give you all of my credit cards.
You're actually going to even figure out which credit card you use for this particular purchase, because this one has higher cash back than that one for this type of good.
And you're going to integrate affiliate tracking where you give me cash back, like Ebates does or Rakuten does.
You're going to do all the coupon stuff.
And not all of this will be good for merchants, by the way.
But you can imagine and again, it doesn't require a lot to imagine this, because there already are a lot of companies that do this but they have been somewhat of a niche space because they only appeal to the people and there are plenty of people that are like this, by the way, that value money more than time and are somewhat technical.
So it's actually not just money more than time.
It's like my mom might want to use one of these.
Probably would value money more than time because she's retired, so why not?
But it's just too complicated to use.
And if you make it so easy, I mean, that's the other thing.
It's like we talked about like how if you make something show up right now, that's going to have a bigger market than if something shows up five weeks from now.
Like that makes sense.
If you make something so painfully easy to use that it's more of an IQ test.
It's like do you want to pay less for something or more for something?
And, like, everybody, of course, would say, I want to pay less for something.
But it's like, oh, but you have to do these 18 things, download, like, ah, that's too complicated.
I can't figure out how to do that.
But if it's so easy, I think that that's one area where you could.
I mean, this is where startups have lived, because it's clearly not going to be Amazon, because it's like Amazon wants you to shop at Amazon.
Amazon.
By the way, the other thing that they're somewhat imperiled by, Amazon has a giant revenue and profit line item from advertising.
You go to the Amazon website and then you click on an ad that takes you away from the Amazon website.
That's 100 gross margin for Amazon.
They'd rather sell you that than sell you a product where they have to deliver it, God forbid.
The best SKU that they sell is the advertising SKU, and that's going to be imperiled if they no longer control the presentation layer because AI intermediates it.
But I think it's like this kind of money more than time, expand that to the entire universe.
There's certainly a there there.
Yeah, I think there's sort of two sides.
So I think there's the consumer side, right?
Which is if we go back to my conversation earlier about you want to have a really in-depth conversation about what bike to get, you could imagine someone fine-tuning a model.
That is much better on tons of conversations between bike experts and people to actually know the right questions to ask, to give you a much better buying experience and better, better outcome than ChatGPT could.
So that's one way that, like consumer distribution could be disrupted beyond the ChatGPT disruption that will happen.
Then I think there's the merchant side of things, which is like what are the implications if we suddenly have a ton of AI agents browsing your site and potentially even making decisions on behalf of consumers and hitting the purchase button instead of people?
Like how do websites, How should websites change to make themselves more browsable, more easy to interact with, more easy to find what the agent is looking for?
What sort of infrastructure do we need on the financial side for AI agents to actually be able to make a purchase on behalf of someone and use their credit card?
The entire infrastructure and merchant-facing side of it is probably going to change quite a bit.
And I think that will be just as big as the consumer side of the market.
It's a good place to wrap.
Alex, Justine, thanks so much for the great conversation.
Thank you.
Thanks for having us.
Thanks for listening to the A16Z podcast.
If you enjoyed the episode, let us know by leaving a review at ratethispodcast.com slash A16Z.
We've got more great conversations coming your way.
See you next time.
Thank you so much for having me.
