AI transcript
0:00:06 Hi everyone, welcome to the A6NZ Podcast. I’m Sonal. Today is part of our ongoing series
0:00:12 on consumer tech trends. We’re talking all about the category of consumer packaged goods
0:00:18 or CPG and where this fits with what’s going on in online and offline commerce trends overall,
0:00:23 including when it comes to the grocery business. We also talk about the trends of DTC or direct
0:00:29 to consumer and the concept of micro or emerging brands as well. Joining us to have this conversation,
0:00:34 we have A6NZ General Partner Jeff Jordan, who’s written a lot about competing with Amazon and
0:00:38 the future of e-commerce and marketplaces and has been on the front lines of this area both as
0:00:43 an operator and investor, witnessing firsthand from many angles a lot of changes in the industry.
0:00:48 And then we also have Ryan Kahlbeck of Circle Lab, an investment platform powered by data and
0:00:53 technology. He also talks a lot about innovation in the CPG space and more, which is why we
0:00:58 invited him to join this discussion. Please note that the content here is for informational purposes
0:01:03 only should not be taken as legal business tax or investment advice or be used to evaluate
0:01:09 any investment or security. It’s not directed at any investors or potential investors in any fund.
0:01:15 For more details, please also see A6NZ.com/disclosures. The broader question that we covered throughout
0:01:21 this episode is how does technology and especially the internet change and in some ways not change
0:01:26 the way we do things. Why do some of the traditional businesses in these industries, though full of
0:01:32 some of the smartest people, have trouble innovating and can tech really help? In fact, that’s where
0:01:37 we begin the conversation with the assertion that it’s been hard to bring tech to CPG, even though
0:01:45 there seem to be a lot of products trying out there. As a user, I have a hard time perceiving this
0:01:50 because I am constantly bombarded with consumer products that are techie, whether it’s like
0:01:54 a thousand beauty product lines, there’s a thousand even generics lines that I’m getting hit with.
0:01:58 So I have a hard time grokking that this is a reality. Tell me what’s happening there.
0:02:05 It’s a great point. So I think, first, one of the reasons that you see that is the D2C movement,
0:02:11 which is direct to consumers. A handful of tech VC firms, they’re putting a fair amount of money
0:02:17 into consumer product companies that sell just direct to consumer or predominantly direct to
0:02:23 consumer. That money is usually not used for innovation, for product innovation. It’s usually
0:02:28 used for marketing. I agree with Ryan that they’re largely marketing companies. It’s actually
0:02:32 derivative of Amazon, unfortunately. If you want to play any e-commerce in a post-Amazon
0:02:37 era, you cannot sell what Amazon sells successfully. I mean, early on, we tried a number of concepts
0:02:43 that some are around anymore that said, okay, I can kind of sell the same thing as Amazon with
0:02:47 a different distribution twist with something like this, but you can’t. So then the next wave
0:02:52 of companies was, okay, if I can’t sell, I can’t compete with Amazon directly skew by skew,
0:02:58 let me get proprietary skews. And so they’re formulating different products with different
0:03:05 branding, and they typically aren’t on Amazon or on other retail. But that is where a lot of the
0:03:11 direct to consumer stuff is happening. And frankly, some success, not a ton of success
0:03:14 in doing it. Why is that, by the way? At some point, you’re still competing with
0:03:21 legacy players. And what’s worse is they’re also competing with each other. So there are a half
0:03:29 dozen, a dozen brands all trying to find you. Early on, they find you at $20 acquisition cost
0:03:34 when 10 of them go at each other. They’re competing for you, 10 companies trying to grow,
0:03:39 competing for you. And then that also caps their ability to price. So one of the big
0:03:44 secrets in e-commerce is virtually no companies get big and make money in the United States on
0:03:51 e-commerce. I can name five e-commerce companies in the US after two decades of investing and
0:03:56 God knows how many tens of billions of dollars who are a billion dollars in sales and profitable.
0:04:01 Yeah, I mean, you’re making the point, particularly around the rise in CAC. We see a lot of
0:04:07 DTC companies raise money with a CAC, let’s call it $10, $30. And then over the course of
0:04:13 subsequent two years, it raises literally sometimes by an order of magnitude. And that is just killing
0:04:17 their profitability. And by that, just to quickly summarize, you mean CAC is on customer acquisition
0:04:20 costs and they’re using all that marketing dollars to acquire their customers.
0:04:26 Exactly. I think when DTC directed consumer businesses, I think a lot of folks look at it
0:04:31 from the outside and say, okay, we’re stripping out the middleman, the retailer, the offline
0:04:36 retailer. And because of that, we can put that margin that the retailer gets into our business.
0:04:40 And this is going to be a wonderful business. The problem is that you need to attract people to
0:04:47 your site, right? To get people to come to your startup, to come to your URL and buy something
0:04:51 is a really difficult thing. And so that’s what’s driving these customer acquisition costs up.
0:04:55 Now, there are some DTC companies, Native Deodorant was bought. They only raised
0:04:59 two or three million bucks in total, sold for $100 million to Unilever.
0:05:03 Why did Unilever want to buy that company? Why wouldn’t they just make their own in-house brand,
0:05:09 another brand? The CPG companies, large ones, have lost the ability to innovate. They innovate
0:05:13 through acquisition now and they buy early. So Unilever bought Dollar Shave Club. Unilever
0:05:18 doesn’t have a shaving business. I don’t know Unilever Deodorant offerings, but I’m guessing
0:05:24 they saw something in there. So it and Biotech are kind of the same. The big pharma companies are
0:05:28 buying their innovation. The big CPG companies are buying their innovation. Historically,
0:05:34 large CPG has been able to rely on their brands. Brands that have existed literally in some cases
0:05:40 for 50 or 100 years. Meg, Scott Cook, and Brian, Sweetie, and Steve Ballmer, we’re all at P&G
0:05:45 together. Right after I graduated from college, Meg was the brand manager, I believe, on Crest.
0:05:52 Wow. That’s awesome. But can you think of that cadre of talent in all analysts in Cincinnati?
0:05:56 CPG seems like, because I have a lot of friends that go through their career starting at Clorox.
0:05:59 And it seems like sort of a training, there’s always like a mafia and a training ground that
0:06:02 people get some fundamental skills in these companies. So what are they actually getting
0:06:06 out of these companies? There’s a quote in one of the Apple movies, if you can sell sugar water,
0:06:12 you can certainly sell. That was Steve John’s quote, like he tried recruiting John Scully.
0:06:16 I think there’s probably something to that, right? To be able to sell literally the same product
0:06:19 for 30 years in a row. Think about trying to do that in the technology space. That’d be
0:06:26 impossible. There’s a fun book by a Harvard dean called Different. And it basically says,
0:06:31 almost all consumer goods are these small incremental improvements that everyone copies
0:06:38 because that’s the improvement that wider mouths on the Crest toothpaste because that you go through
0:06:44 it faster. Oh, so Colgate will do wider mouths and Spearman and whitening and versus brands that
0:06:50 kind of just throw it out and just do it differently. She uses Harley. She uses Apple. She uses Red Bull.
0:06:56 And they just came to market with completely, we are going to be different. And it’s so interesting.
0:07:02 I love the book because 99% is exactly the same. And then the 1% is different.
0:07:05 That gets back to the point of like why these large brands are losing market share.
0:07:11 The large brands have not had to innovate. They’ve been able to rely on their brands on,
0:07:16 whether it’s Coke or Pepsi or whatever it is, the same product, just their brand name for decades.
0:07:22 Now these smaller upstart brands, these emerging brands are able to develop the innovation in
0:07:27 house and deliver that to the consumer. The consumer, on the other hand, for the first time
0:07:32 in history is saying, I demand products that meet my unique needs. Maybe the three of us used to
0:07:37 eat the same breakfast cereal. Now the three of us are eating different things. We’re demanding
0:07:43 products that meet our unique needs. That customer consumer demand is pulling forward the innovation
0:07:46 and giving it a market. That’s why though, I just want to push a little bit more on this DTC topic
0:07:51 though, because when I think of the theory of the internet, which, you know, it disintermediates this
0:07:56 intermediary, you can go direct to people, you create movements on the internet. I mean,
0:08:00 talk about meme culture. Like if a meme can monetize, why the hell can’t a product?
0:08:03 So I’m still having a hard time buying why DTC is so hard.
0:08:07 The internet enables a long tail. So all of a sudden everything’s discoverable,
0:08:11 where it used to be, there were three television networks and 10 magazines that mattered.
0:08:18 The world is different. It used to have, you know, very narrow portals to work, which was great for
0:08:25 big companies that have stable product lines. So you couldn’t do TV on a $5 million revenue line.
0:08:29 You can do internet on a $5 million revenue line. Right. But that’s exactly my point,
0:08:33 is we have a world where we do have a long tail discoverability. You have the ability to access,
0:08:38 find your niche audience. You also have a world where you can still make hits on that long tail.
0:08:42 So you just describe why there’s a proliferation of CPG companies.
0:08:45 But why does DTC not work? That’s a part I don’t get.
0:08:49 When we say it doesn’t work, I think it is an incredible channel for iterating on a product.
0:08:54 I think it drives innovation. I can find my consumer base and I can test a new product.
0:08:57 Next month, I can test a different product. That’s very different than the offline world,
0:09:00 where if I’m selling into Safeway or Whole Foods or Costco down the street,
0:09:05 it’s hard for me to switch the product out if it’s not working, to tweak a package, whatever it is.
0:09:09 People in the technology space take that kind of A/B testing for granted. In CPG, it’s much,
0:09:12 much harder because you literally… Because it’s physical product and offline space.
0:09:14 Yeah, you have atoms, you need to move, not just bits.
0:09:18 And so if you run a chain of stores, actually a couple of my… All the companies that are
0:09:23 getting challenged growing, continuing to grow DTC sales are turning to offline retail in different
0:09:27 forms. Every company I’ve worked with is trying to do that because incremental sales…
0:09:29 That’s actually rather counterintuitive.
0:09:33 It is. But the way store management work, I used to be CFO of the Disney store, is
0:09:40 you try products. Typically, you do two or four sets a year and you try products in a
0:09:44 significant subset of your stores because if it’s a bomb, you don’t want to buy
0:09:48 deep in it. So you’ll put it in five stores a test for the first six months.
0:09:52 And then they say, “That worked well. Let’s go to 50 stores for the next six months.”
0:09:56 And then by the time you get chain-wide, it literally is a couple of years later.
0:10:00 And so it’s really hard to grow your business.
0:10:03 And that’s for Disney stores where you have your own product in the store.
0:10:09 So if you think of the CPG products, they’re selling through a third party, the retailer.
0:10:14 Now, they have to make a much bigger bet. They can’t usually just start in five safe ways.
0:10:18 So they have to start in 200. Now when you start in 200, flipping that and changing that product,
0:10:21 if it didn’t work, it can kill the company.
0:10:26 When I was at Xerox PARC, one of the companies we partnered with was a large CPG company.
0:10:30 And their number one challenge was trying to figure out what happens after the consumer
0:10:33 buys the product. They had zero insights.
0:10:35 Oh, actually, it’s even worse. They have zero insight.
0:10:40 They know what they sell into the retail chains. They don’t know what’s sold where to who.
0:10:41 Right. Seriously?
0:10:41 No. It’s incredible.
0:10:42 It’s absolutely incredible.
0:10:44 That’s great. That’s crazy. How is that not possible?
0:10:47 So people who are listening to this will respond, “Well, what about credit card data?”
0:10:50 The problem with credit card data is it can tell you what the retailer is selling,
0:10:51 not what was bought at the retailer.
0:10:54 So I can see what Nordstrom.com sales for last month.
0:10:56 I can’t see what pairs of jeans were bought there.
0:10:58 Why not? Doesn’t it say?
0:10:58 They don’t sell.
0:11:00 Isn’t that the whole point of a skew?
0:11:03 No. Well, yeah, but these credit card companies don’t sell it.
0:11:08 And more importantly, back to Jeff’s point, they don’t tie those products to individual people.
0:11:16 Some retailers have loyalty card data, but there’s privacy issues with them selling that.
0:11:22 $84.51, a division of Kroger sells part of it, but not in the way that we’re talking about here.
0:11:26 They can say, “This person who I can, by the way, I can match Sonals,
0:11:29 what her purchasing power to your Instagram account, that is not done anywhere.”
0:11:33 Typically, CPG marketing is you buy a circular in the Sunday paper.
0:11:35 You buy an end cap, and you have no idea–
0:11:37 An end cap being the little display at the end of the grocery store.
0:11:38 At the end of the aisle in the grocery store.
0:11:42 And billions of dollars goes into those, and who knows if it works.
0:11:48 And they certainly don’t have any data beyond, “Oh, our total sales went up a little bit there.”
0:11:53 One of the key things that was compelling about Instacart to us is that they have a revenue
0:11:56 stream from the consumer, a revenue stream from the grocery retail partner,
0:12:00 and a revenue stream from CPG companies who are interested in accessing the consumer.
0:12:04 Why the CPG companies were so interested in that is,
0:12:06 it’s the first performance marketing they’ve ever seen.
0:12:09 On something like Instacart, they know everything I’ve ever bought.
0:12:15 And if they know I love Heineken beer and the product manager of Stella wants to try to convert me,
0:12:19 they can give me a Stella coupon, a Stella samples, a Stella, everything else.
0:12:21 And then see, did I change my behavior over time?
0:12:23 That’s the holy grail of marketing.
0:12:24 The holy grail for marketing.
0:12:26 I mean, performance marketing, like that type of data,
0:12:29 like closing that feedback loop is a big F-deal.
0:12:34 They also over time have the ability to kind of literally move the product on the page, right?
0:12:36 Which if you think about offline retail, you can’t do.
0:12:38 What do you mean by on the page?
0:12:43 Meaning when you’re looking at Instacart, what product you’re looking for can be moved physically.
0:12:47 Oh, like kind of personalized rearrange to your needs.
0:12:47 Exactly.
0:12:48 Which you cannot do in a physical way.
0:12:50 And it’s completely obvious in tech.
0:12:52 But for people that are in CPG, it’s a game changer.
0:12:57 So I was in a Safeway half a mile from here on Sand Hill six months ago,
0:12:59 and was buying some steak.
0:13:01 Steak was in the refrigerator.
0:13:04 Next to the steak in the refrigerator were wood chips.
0:13:06 The wood chips have no need to be refrigerated.
0:13:08 They’re literally just wood chips to put in a barbecue.
0:13:11 They’re in the refrigerator because they’re on sale.
0:13:13 And they want to put them next to the steak.
0:13:14 That’s it.
0:13:16 And so you’re refrigerating literally wood.
0:13:17 That’s crazy.
0:13:19 Because back to Jeff’s point, if I bought an end cap,
0:13:21 the end cap would have been 30 feet away.
0:13:23 Then you would have lost the consumers.
0:13:24 And they need to have that proximity.
0:13:26 That’s a crazy awesome example.
0:13:27 I love that.
0:13:30 Let’s talk about grocery for a little bit as an interesting category.
0:13:35 So first of all, is grocery going to go the way of malls and other retail?
0:13:37 So I’ve got a not very popular opinion on this.
0:13:38 Let’s hear it.
0:13:39 The more popular, the better.
0:13:43 I think grocery stores are here for the very, very long term.
0:13:46 Very long term, meaning next 20 years at least.
0:13:50 So taking a step back, D2C and e-commerce has been around for 20 plus years.
0:13:52 This is not a recent phenomenon.
0:13:55 Food is still, Jeff, you could tell me, I think 5% of sales.
0:13:56 Of digital?
0:13:56 Yeah.
0:13:57 Way under.
0:13:58 Yeah.
0:14:02 I don’t foresee a world in which everyone is just going to go online, A.
0:14:07 And B, when that happens or when it gets to be a much higher proportion of where you buy
0:14:13 your groceries, I still think that that grocery is going to be delivered locally.
0:14:18 But the core point is grocery today, 2%, 3% net margin business.
0:14:21 That’s hard to strip out a lot of costs from that.
0:14:21 There’s not a lot of room left to go.
0:14:23 You can’t do any cost cutting at all.
0:14:23 That’s right.
0:14:29 So you think about where technology has been particularly successful at killing other industries.
0:14:32 They tend to be industries where there’s a fair amount of profit, right?
0:14:35 It’s also like Bommel’s cost disease, too, if you think about it, eventually penetrating
0:14:39 health care and education, like things that are way more expensive than they need to be.
0:14:41 And technology is a vector to just cut right through that.
0:14:42 Absolutely.
0:14:46 But the safety down the street has a 1.5% net margin.
0:14:48 So what are we going to do to rip the cost of that?
0:14:52 Because that thing is already delivering a pretty good product to the people that live within a
0:14:53 mile and a half of here.
0:14:57 I mean, there was a set of companies that was trying to help physical retail compete
0:14:58 with the digital commerce.
0:14:59 And it was so interesting.
0:15:04 We didn’t invest in many of them at all because our internal reference was we’re shorting the
0:15:05 future.
0:15:08 You know, just so it’s not a long-term winning proposition and their margins are going to
0:15:10 get squeezed, so they’re going to squeed their vendors.
0:15:13 Then we made the Instacart investment in the belief that the grocery stores are there.
0:15:15 It’s distributed.
0:15:17 They have distributed little warehouses.
0:15:18 They provide service.
0:15:19 And it was interesting.
0:15:22 Fred Smith, the founder of FedEx, when the internet first came up said,
0:15:26 “I think a whole lot of goods are going to be delivered by FedEx.
0:15:27 Groceries ain’t going to be one of them.”
0:15:32 Because the concept that you’re going to load a truck in the morning and having
0:15:36 bouncing down the streets and this and that and deliver at 8.
0:15:40 It’s something at 8 p.m. that was put in the truck at 4.30 a.m.
0:15:42 And he just said, “I don’t think it works.”
0:15:47 Building up the shopper network is so hard to replicate for someone else going forward.
0:15:50 It’s not as simple as, “Let’s just hire FedEx to go do this thing.”
0:15:54 Oh, and the operational intensities observe.
0:15:58 We think in grocery, we think effectively there are a couple different dimensions
0:15:59 that grocery chains need to compete on.
0:16:01 We think it’s assortment.
0:16:03 We think it is convenience.
0:16:05 We think it is pricing and experience.
0:16:07 Pricing is a really, really hard place to compete on.
0:16:10 You’re competing with Amazon to a point that Jeff made earlier.
0:16:12 You’re competing with Walmart.
0:16:14 I think that’s just a really, really hard place to win.
0:16:15 Yeah, you can’t win on price.
0:16:18 Especially when you already have this 1% to 2% margin.
0:16:20 Exactly. The margins are already so low.
0:16:22 So let’s put pricing aside for a second.
0:16:28 I also think that grocery is, in some ways, an experience for some people.
0:16:33 An experience for the consumer to go in, perhaps with the family,
0:16:36 perhaps just buy a couple of things here and there.
0:16:38 They want the immediacy of that.
0:16:41 We don’t see that going away anytime soon.
0:16:43 I think it’s going to be hard to win, again,
0:16:47 because how do you invest into an experience if you have such low margins?
0:16:49 I will say one quick sidebar on experience,
0:16:50 such as if Connie were in this room,
0:16:52 she talks a lot about what happens in China.
0:16:55 And she talks about this incredibly fascinating phenomenon
0:16:59 where grocery stores in China have become destinations themselves
0:17:01 because there’s literally restaurants inside.
0:17:04 They’re doing all kinds of neat food chef things, etc.
0:17:06 Cooking on site, doing all these interesting things.
0:17:07 I mean, what should you take on that?
0:17:10 I was with the CEO of a large grocery chain about a month ago
0:17:12 who made that same point.
0:17:14 They are starting to experiment by putting restaurants,
0:17:18 effectively restaurants, inside their grocery chain.
0:17:22 The local Asian supermarkets almost all have restaurants forever.
0:17:23 Indian ones, too.
0:17:25 They have like samosas for $2.
0:17:25 Yeah.
0:17:30 I would say I think it is nice to have not a requirement to be successful.
0:17:33 I’m not convinced that that’s going to be the core differentiator going forward.
0:17:35 So what do you think is going to be the core differentiator?
0:17:35 You had one more dimension.
0:17:38 Well, convenience and assortment, those are the last two.
0:17:40 So convenience, to me, is delivery.
0:17:41 Delivery or in-store pickup.
0:17:45 I think that that will end up being table stakes, not a nice to have.
0:17:47 Meaning you need to have convenience.
0:17:50 Well, my question on this is why bother even having a grocery store
0:17:51 if you only need to deliver?
0:17:53 Why not keep warehouses then?
0:17:54 If experience isn’t going to win the thing.
0:17:56 Like why not just have a bunch of warehouses
0:17:57 that deliver food if delivery is the thing?
0:17:58 Yeah.
0:18:01 So to be frank, that could be the 50-year vision.
0:18:02 That really could.
0:18:04 In the UK, which for whatever cultural reason
0:18:06 has been doing grocery delivery for a long time
0:18:09 and it’s a much deeper state of penetration,
0:18:11 they’re starting to have what’s called dark stores,
0:18:14 where you basically, they look a lot like supermarkets.
0:18:16 They’re locally distributed.
0:18:17 They have inventory assortment,
0:18:19 but they’re not in high traffic parts of town,
0:18:22 which means the rents are much, much lower.
0:18:26 And so, as a result, you don’t have to make it pretty.
0:18:28 You don’t have to have the lights, lots of lights.
0:18:29 You don’t have to have high labor.
0:18:30 All you have to do is pick in them.
0:18:33 And so that is how grocery has been developing
0:18:36 in one of the most advanced digital grocery markets.
0:18:39 So it’ll be interesting if whether that happens in the US,
0:18:43 every argument that I can make on why grocery stores won’t
0:18:46 just be warehouses where it gets delivered from,
0:18:49 every argument that I can make is a short-term argument.
0:18:51 I can’t make a 50-year argument for that.
0:18:53 So I think that that could happen.
0:18:55 Over the next 10 years, I don’t think customer adoption
0:18:56 will be big enough to get rid of these stores.
0:18:59 These stores, these aren’t little mom and pops.
0:19:02 They’re Fortune 500 companies that would not go down
0:19:03 without a really big fight.
0:19:04 No, and I think there are destinations.
0:19:06 I mean, I see like families on the weekends all the time.
0:19:08 It’s like, it’s an outing to go to the grocery store,
0:19:10 which if they had like a daycare,
0:19:12 I think that would be a huge win, frankly.
0:19:14 That alone would be a big differentiator.
0:19:15 I would love that.
0:19:16 I know, I think everybody would take that.
0:19:18 I exclusively shop through Instagram.
0:19:20 I do our family’s grocery because I can’t bring the kids
0:19:23 to the grocery store because it’s too much of a disaster.
0:19:26 So I believe that convenience will be table stakes.
0:19:29 So then it comes down to what is the way grocery wins?
0:19:30 What are the way grocery store competes?
0:19:32 To me, it is just about assortment.
0:19:33 That’s your fourth dimension.
0:19:33 This is the fourth dimension.
0:19:36 After price, experience, convenience, and now assortment.
0:19:37 That’s right.
0:19:40 Assortment is what are the products that are on the shelf?
0:19:43 So if you think the last 80 years,
0:19:46 it has been, well, what’s Pepsi gonna give us this month?
0:19:49 Coke, General Mills, Unilever, Procter & Gamble, et cetera.
0:19:50 Today, as we’ve talked about,
0:19:53 consumers want brands and products to meet their unique needs.
0:19:57 The problem with that is that the buyer at the retailer,
0:20:00 meaning the person that selects, let’s say, the chocolate company,
0:20:03 the buyer at the retailer is still the same buyer
0:20:06 that lived there 20 years ago in some cases.
0:20:08 They don’t use a lot of data.
0:20:10 They’re literally trying chocolate bars
0:20:11 to decide what goes on the shelf.
0:20:13 That’s a really hard place to be in a market
0:20:16 that is trillions of dollars
0:20:19 to decide which of these emerging brands they want to work with.
0:20:23 So the default is, gosh, maybe I just rely on the big brands
0:20:24 to tell me who to work with.
0:20:25 That’s a real example.
0:20:27 Sometimes the big brands literally say,
0:20:29 work with these emerging brands.
0:20:30 Maybe I work with the distributor,
0:20:33 who, by the way, has paid more than by the larger brands.
0:20:35 But there isn’t really a good solution
0:20:38 for a lot of these Fortune 500 retailers
0:20:41 on how to optimize their assortment.
0:20:45 The data that exists for these grocery chains is pretty poor.
0:20:48 You’ve got a couple retail-level sales providers
0:20:51 that on average track 20,000, 30,000 products,
0:20:53 or companies, rather, each.
0:20:56 There’s about a million and a half out there.
0:20:58 A million and a half, and they cover less than 5% of them.
0:21:00 And even the grocery and food shows, aren’t they?
0:21:03 Sort of like, I’m thinking of the equivalent in fashion
0:21:03 and boutiques.
0:21:05 You essentially have a fashion show
0:21:07 to curate all the brands, the emerging brands,
0:21:09 the existing brands, new product lines.
0:21:11 Why isn’t there an anthropology of grocery stores?
0:21:13 Because when I think of anthropology as a retailer,
0:21:16 they have assortment because they go around the world
0:21:17 to find a variety of designs.
0:21:20 So it works very well for a certain demographic of women,
0:21:22 like in their 20s, 30s, et cetera.
0:21:25 Then you have to say, which of these will my consumers
0:21:27 respond to at the rate price?
0:21:29 So you get exposed to the million,
0:21:33 but then I can only carry X,000 in my store.
0:21:34 How do I figure that out?
0:21:36 Online might actually help,
0:21:38 because you can put infinite selection online
0:21:39 and see what’s selling.
0:21:42 So if you’re a grocer, I’d be looking at my online sales
0:21:44 just to inform my offline sales.
0:21:46 Like, oh, wow, that’s a breakout hit online.
0:21:48 Why wouldn’t it be a breakout hit offline?
0:21:51 Interestingly, then, you might come back to a customer
0:21:53 acquisition challenge for the CPG companies,
0:21:56 which is if we have a ton of products online,
0:21:57 how do we then stand out?
0:21:59 That comes back into advertising.
0:22:00 This kind of vicious circle.
0:22:01 Or virtuous.
0:22:02 Or virtuous.
0:22:03 It’s a skewed sample, too.
0:22:05 Like what happens online and offline sometimes.
0:22:05 It’s definitely skewed.
0:22:08 But if you’re in a complete information vacuum,
0:22:09 which essentially these guys are, at least you have something.
0:22:11 Even, by the way, loyalty cards are a really skewed sample.
0:22:14 That’s a very self-selected, self-interested group.
0:22:16 You’re not really getting the huge untapped space
0:22:16 of what people want.
0:22:19 You’re not, but you’re actually finally getting data
0:22:21 on a per person basis to kind of understand what’s there.
0:22:22 Exactly.
0:22:26 It’s hard to understate how blind most buyers
0:22:29 at most physical retailers are right now.
0:22:31 Yeah, they’re just kind of, it’s instinct.
0:22:33 It’s, you optimize the current assortment.
0:22:36 But then how do you layer in new things is,
0:22:38 and there’s a plethora of new things.
0:22:39 Or just everything that you don’t know
0:22:41 people have the taste for.
0:22:41 Exactly.
0:22:42 So you think about that you’ve got a buyer
0:22:44 for the chocolate category, right?
0:22:47 And that could be an older, candidly white male
0:22:49 who’s making a decision on the entire category.
0:22:50 For a very diverse audience.
0:22:53 By the way, not diverse racially by age,
0:22:57 a certain gender, demographic, location.
0:22:59 So should we be selling the same thing in LA
0:23:00 that we do in Vermont?
0:23:02 So how are people going to get this data?
0:23:03 Because right now Jeff is describing
0:23:04 that they’re desperate for data.
0:23:06 So they have to rely on these,
0:23:07 they have to get data somewhere.
0:23:09 But that’s still adverse selection type data.
0:23:11 It’s not like the true opportunity space of data.
0:23:12 So where does the data come?
0:23:15 Broadly speaking, in consumer,
0:23:16 there’s a really beautiful thing
0:23:17 that a lot of people that don’t live and breathe
0:23:19 this space, they don’t recognize,
0:23:21 which is there is a tremendous amount of data
0:23:22 that’s out there in the world.
0:23:26 Meaning I can already see where a product is sold,
0:23:28 how many SKUs a company has,
0:23:30 meaning how many products that company sells,
0:23:32 what the price points of the products are,
0:23:33 what the end users think of the product.
0:23:34 And if I’m tracking it,
0:23:37 I can see how all those things change every single month
0:23:39 and how they compare to every other company in the category.
0:23:43 Those factors have been shown to be predictive of success.
0:23:46 People can aggregate those.
0:23:47 Now the challenge,
0:23:48 and this is where it gets really tricky.
0:23:51 The challenge is that you’re consolidating information
0:23:53 across literally hundreds of unstructured data sources.
0:23:55 It’s extremely intensive,
0:23:57 extremely intense and very difficult.
0:23:59 Sounds like a deal for an AI solution.
0:23:59 Yeah, it is.
0:24:00 It is.
0:24:01 But the data is out there is my point.
0:24:05 We think that that data is going to start getting consolidated
0:24:08 by data providers, technology companies,
0:24:11 that then sell it to the CBG companies,
0:24:13 or in this case, the grocery chains.
0:24:15 So the data opportunity, do you believe that?
0:24:15 Yeah, no.
0:24:17 We actually have seen a ton of companies trying to do it.
0:24:23 The interesting part is how hard they have to work to get the data.
0:24:24 There have been a whole bunch of them
0:24:28 that are trying to incent consumers to take pictures of their receipts
0:24:29 and submit the pictures.
0:24:32 And they do Optical Character Direct Edition on the picture
0:24:34 to try to reverse engineer.
0:24:36 What did Jeff buy?
0:24:37 We’ve seen multiple companies trying to do that.
0:24:39 There are other approaches too.
0:24:42 There was an on-demand,
0:24:45 they’d send armies of people with smartphones
0:24:46 to take pictures of shelves
0:24:48 so that they know the competitive pricing.
0:24:53 Oh, look, Crest is $2.29 and Colgate is $3.15.
0:24:54 What happened to sales?
0:24:57 But they don’t know what Colgate and Crest is,
0:24:58 and so they don’t know.
0:25:03 All they know is my philosophy in the southern region slowed down.
0:25:04 Or it’s sped up and you don’t know why,
0:25:05 which is equally problematic actually.
0:25:07 In the case of the receipts companies,
0:25:08 we’ve seen a lot of those too.
0:25:10 The challenge has been many of them tap out
0:25:13 at five, 10 million consumers, at least here in the US.
0:25:16 The problem with that level is that then,
0:25:18 that’s such a small portion of the overall population
0:25:21 that you’re not capturing the long tail of companies.
0:25:25 The chances that the $5 million popcorn company
0:25:29 is bought in a population that small is relatively low.
0:25:30 They’re going to be buying
0:25:31 the Procter & Gamble’s General Mills of the world,
0:25:33 but then you’re just getting more data
0:25:34 on the larger companies.
0:25:35 They need it on the smaller ones.
0:25:37 Exactly, they need data on the long tail.
0:25:40 Okay, so in this world, this long tail world,
0:25:42 this world of offline and online distribution,
0:25:44 and those are the two distribution broadly
0:25:45 that we’re talking about.
0:25:47 We are seeing a lot of microbrands,
0:25:48 and we didn’t talk about that
0:25:50 when we were talking about direct-to-consumer.
0:25:51 I mean, there’s a whole lot of media pieces
0:25:53 dissecting this phenomenon.
0:25:54 First of all, what is a microbrand
0:25:57 and why does it matter, or is it just a hypey thing?
0:25:59 Yeah, so let me just clarify.
0:26:02 By microbrand, you mean an emerging consumer product company
0:26:05 typically called less than $10 or $15 million in revenue.
0:26:08 So yes, but I think you’re the one who argues
0:26:10 that it denotes size, not channel,
0:26:12 because the way I’ve read it in the media,
0:26:13 it does talk about it as well.
0:26:15 Yeah, so the recent Economist article
0:26:16 kind of confused the two.
0:26:17 They started talking about microbrands,
0:26:19 and then they said, basically implied
0:26:21 that microbrands means D to C.
0:26:24 Micro to me, unless I’m missing something,
0:26:26 denotes size, not channel.
0:26:28 So I don’t really love that term to be candid with you.
0:26:29 Why didn’t you like it?
0:26:30 Well, for the same reason,
0:26:32 I would imagine that the entrepreneurs around here
0:26:35 wouldn’t like it if we called them micro technology companies.
0:26:36 They’re starting companies
0:26:37 because they want to build something big.
0:26:41 And I think that sometimes that comes across
0:26:43 as a little bit high and mighty, perhaps,
0:26:46 but especially if it’s just an ice cream company.
0:26:47 But look, I’ll be frank with you.
0:26:51 The ice cream company that’s able to strip out
0:26:53 fat and calories from the ice cream
0:26:54 and still deliver great products,
0:26:56 to me, is having a bigger impact on the world.
0:26:57 This is like Halo, right?
0:26:59 Halo Top, yeah, it’s exactly right.
0:27:03 So when we talk about them as emerging brands,
0:27:07 so emerging brands can be sold certainly offline or online.
0:27:09 But what’s happening,
0:27:12 these brands are growing very, very quickly right now.
0:27:14 In every single category in consumer,
0:27:17 large brands are losing share to emerging brands.
0:27:19 And the large brands are just terrified by this.
0:27:20 So why is it happening?
0:27:22 We think three primary reasons.
0:27:25 First is what we talked about
0:27:27 before the personalization of the consumer.
0:27:29 Consumers are demanding products that meet their unique needs.
0:27:31 Two other reasons that are pretty relevant
0:27:32 to this conversation.
0:27:36 One is decline in distribution costs.
0:27:39 Really, instead of just saying it’s a decline,
0:27:41 it’s really a shift from fixed costs
0:27:43 to variable costs.
0:27:44 And that’s because of the internet,
0:27:46 like the entry point to be able to buy,
0:27:47 get up a business up and running.
0:27:50 The internet is part of the driver,
0:27:52 but I don’t want to imply that that is the key driver.
0:27:55 In my view, it’s more that the offline retailers
0:27:58 are hungry to work with the small brands.
0:27:59 They’re struggling to figure out how to do it.
0:28:01 And so what we’re seeing is many of the offline retailers
0:28:04 are eliminating or lowering slotting fees.
0:28:07 Slotting fees are the cost to get your product on the shelf.
0:28:08 So if I want to launch a new chocolate bar
0:28:09 to get on the shelf of Safeway,
0:28:12 it is literally $50 to $100,000 just to get it on the shelf.
0:28:13 Think about that for a second.
0:28:15 If it’s the Apple App Store to launch an app,
0:28:18 it’s $100,000, it’d be a huge buried entry.
0:28:21 That fixed cost is declining rapidly
0:28:22 over the last five or 10 years.
0:28:23 Because these big brands are eager for–
0:28:25 The grocery stores are eager for these smaller brands.
0:28:27 More assortment, actually.
0:28:27 That’s right.
0:28:29 The third driver for why these emerging brands
0:28:32 have been so successful over the last five or 10 years
0:28:33 is marketing costs.
0:28:36 And that does get back to your point about the internet.
0:28:39 So marketing costs have also flipped from fixed to variable.
0:28:41 Fixed, meaning it used to be, let’s buy an ad in us weekly.
0:28:42 It cost me $100,000.
0:28:43 Or Jeff’s circular example.
0:28:44 Circular example is a great one.
0:28:47 Today, it is, let’s say, it’s the dollar-shaped flood YouTube ad.
0:28:50 And that’s an extreme example.
0:28:52 But you’re able to at least get your product out there
0:28:54 on a variable cost basis.
0:28:57 Because the flick fixed to variable transition,
0:29:00 these smaller brands, these emerging brands,
0:29:02 are able to grow much more effectively
0:29:03 than they could have 10 years ago.
0:29:05 So it literally is a variable cost.
0:29:07 When I was managing eBay, we were doing TV
0:29:09 and it was $1 million to produce an ad.
0:29:13 And then $10 million to distribute it with a frequency
0:29:15 that the brand people thought was efficient.
0:29:20 So $11 million was the ante to go on television for eBay at the time.
0:29:24 And so now you can go buy a $10,000 of Facebook ads
0:29:26 and try to reach your core audience.
0:29:28 So when you think about where this goes
0:29:30 in terms of innovation in the consumer space,
0:29:33 we think that over the next 10, 15, 20 years,
0:29:36 the brands that win, there will be more of them,
0:29:39 but they will get to a smaller level.
0:29:41 So what I mean is in the last 10 or 15 years,
0:29:44 the brands that won, Chabani, et cetera,
0:29:47 you can build multi-billion-dollar businesses.
0:29:51 I’m skeptical if that’s true in CPG going forward.
0:29:52 I mean, it’s almost math
0:29:56 because the total grocery market’s growing one or 2% a year.
0:29:58 If the number of brands proliferate,
0:30:00 the average revenue per brand should come down.
0:30:01 That’s exactly right.
0:30:04 But there’s no possibility for a player
0:30:08 like with Coke or Pepsi or white vitamin water or LaCroix.
0:30:10 So there’s certainly some very, very smart people
0:30:12 that disagree with me on this point.
0:30:17 I don’t see a world in which consumers want less options
0:30:19 where they’re saying, “Look, I want to go to the grocery store.
0:30:20 I want to go on Instacart.
0:30:22 And I only want to see one chocolate bar.
0:30:25 I don’t want to see something that’s different
0:30:27 for Sonal versus Ryan versus Jeff.
0:30:28 We don’t foresee that happening.”
0:30:31 Yeah, my view on that whole debate always comes down
0:30:34 to when people talk about more choice versus less choice.
0:30:36 Always comes down to actually what is the right choice for me.
0:30:38 And that does go to your point about personalization.
0:30:41 But the nuance I would say and data
0:30:42 is that it doesn’t necessarily have to do
0:30:43 with how many choices you have,
0:30:45 but that the right choices are presented to you.
0:30:45 Absolutely.
0:30:47 And that’s going to be a huge challenge.
0:30:49 Whoever the grocery chain or in this case,
0:30:50 or in the case of Instacart,
0:30:53 is to be able to present the right choices to you.
0:30:55 But we don’t think that the answer is going to be,
0:30:57 “Let’s strip out the choices altogether.”
0:30:57 Right.
0:31:01 And in 20 years ago, the choice was Coke or Pepsi.
0:31:03 But if now you go into the beverage aisle
0:31:06 and there’s things that I don’t even recognize where I am.
0:31:06 Right.
0:31:07 You know, just saying you’re just like–
0:31:08 I really don’t even understand
0:31:09 still why people love LaCroix so much.
0:31:12 It’s just like water with like a little hint of a taste.
0:31:12 I still don’t get it.
0:31:13 It is passion fruit.
0:31:16 I’m so confused over this.
0:31:17 Well, let’s talk about data then.
0:31:19 So we’ve been scooting around this topic of data for a while.
0:31:20 The biggest thing I’ve heard so far
0:31:23 as we talk about online to offline
0:31:25 is that in the offline world,
0:31:27 it has been nearly impossible to get the data we want.
0:31:29 On one hand, I’ve heard you say, Ryan,
0:31:31 that there are many data sources out there
0:31:32 that are really good proxies
0:31:34 and that we can do a lot.
0:31:36 But Jeff, you’ve also said that people are starved for data,
0:31:38 that things are missing.
0:31:40 So tell me what the status is in the world of CPG and data.
0:31:43 Like where are we right now really on where–
0:31:46 how far data– what data can do in this world?
0:31:47 Well, so I think both are true.
0:31:49 Both that there is a lot of data
0:31:51 and that people are starved for data.
0:31:54 And the bridge there is that while there is an outrageous amount
0:31:56 of data in this industry,
0:31:58 the data is very hard to pull together.
0:32:01 And in some cases, impossible.
0:32:04 It’s just impossible to actually go get it.
0:32:08 So the data that’s out there around distribution,
0:32:09 around product uniqueness,
0:32:11 how unique a product is relative to its competitive set,
0:32:14 on what the user thinks of the product,
0:32:17 on the competitive set of that product, et cetera,
0:32:19 all that data is out there in the world.
0:32:20 And if you begin to kind of think about
0:32:22 where would I get that data?
0:32:24 Well, most brands are not trying to hide.
0:32:26 There’s no concept of living in stealth in consumers.
0:32:29 Yeah, you can’t really, like, hide your toothpaste.
0:32:32 That’s right. When I launch in my chocolate bar in the Whole Foods,
0:32:34 Whole Foods wants you to know that you can buy the Whole Foods,
0:32:36 and I want you to know you can buy the Whole Foods.
0:32:39 Similarly, I want you to know what’s in the product.
0:32:40 How you have an ingredient deck and nutritional panel
0:32:43 that’s mandated by the FDA, but it’s out there.
0:32:46 Then consumers talk about my chocolate bar.
0:32:47 That’s also key.
0:32:50 So people can begin to understand what people think of it.
0:32:53 They get the sentiment analysis of the data of the chocolate bar.
0:32:55 So if you think about, you know,
0:32:58 rewind to the first year slack was in existence, right?
0:33:00 So if you could see every customer that used slack,
0:33:03 what they paid for it, what the end users thought of the product,
0:33:05 and how all of those things changed every single month,
0:33:08 that’d be pretty valuable data for a lot of people to have.
0:33:12 You have that data on every single CPG company in existence.
0:33:13 It’s out there.
0:33:13 Who has it?
0:33:15 Well, that’s the challenge, right?
0:33:19 So the challenge is basically it’s out there living somewhere on Google.
0:33:22 Meaning if you Google the smallest brand you can find,
0:33:24 you can see everything that I just said.
0:33:29 The challenge, though, is how do you pull all that unstructured data together
0:33:30 and then normalize it?
0:33:32 So I see a brand on Amazon.
0:33:36 I see the same brand being sold and Whole Foods being talked about on Instagram, etc.
0:33:39 So a process that we call entity resolution.
0:33:42 I remember this from NLP where you have to essentially find the same entity
0:33:43 with different variations or names on it,
0:33:46 but be able to resolve that it is the same entity.
0:33:47 It’s an incredibly hard problem.
0:33:49 Right. It’s a lot harder than people think.
0:33:50 Yeah. And then on top of that,
0:33:55 you also have the problem of how do you know that that product is a chocolate bar
0:33:56 and not a pair of shoes?
0:33:57 That sounds like an easy problem.
0:34:00 I have eaten chocolate bars that taste like a bar of shoes.
0:34:03 You’re right. Chocolate bars do taste like shoes.
0:34:04 Not that I’ve actually eaten shoes.
0:34:06 I mean, have you eaten shoes?
0:34:07 You’re a basketball player.
0:34:08 I always put my foot in my mouth.
0:34:11 So that’s another challenge.
0:34:13 Is that now you think about the people that want to consume this data.
0:34:20 Grocery chains, large CPG companies, they’re not equipped to pull all that data
0:34:24 and structure data in, normalize it, make sense of it, match it together.
0:34:25 That’s not a core competency for them.
0:34:29 That’s why I strongly believe it’ll be a technology company that does that
0:34:31 and then sells that data to others.
0:34:34 Right. So that’s where you believe that CPG companies can compete
0:34:38 and where technology has a place to play by providing that data.
0:34:43 There is a ton of data, and yet people are running blind.
0:34:47 It’s not the data they need.
0:34:52 There’s data around. It’s not helping to make the important decisions
0:34:53 that are moving the needle.
0:34:56 In some cases, it’s not the data that they need.
0:34:58 In other cases, they’re not equipped to digest the data.
0:35:03 And you think of, okay, so at the grocery store, the chocolate buyer,
0:35:07 going back to that example, that’s trying to pick what chocolate bars are on their shelves,
0:35:11 they are used to, for their entire career,
0:35:14 basing it off of either A, their own taste, literally.
0:35:17 That’s how they try product or that’s how they decide products.
0:35:20 Or B, a small amount of retail-level sales,
0:35:23 bought from a very structured data source over and over again.
0:35:25 And that’s not competitive, right?
0:35:26 Because every company has access to that same data.
0:35:28 Every grocery store has access to that same data.
0:35:31 Everyone’s got this commoditized data.
0:35:32 Everyone’s using the exact same thing.
0:35:34 So now when you go to them and you say,
0:35:37 well, actually there’s this whole universe of data out there,
0:35:42 covers 30 to 50 times as many companies as your existing data source does.
0:35:42 Do you want to use it?
0:35:44 The answer is yes, but.
0:35:47 And the but is, well, how do I digest that?
0:35:51 I’m stuck in Excel, Windows 95.
0:35:53 That’s what I’m stuck using here.
0:35:55 How do I digest all of this data?
0:35:56 Who’s going to pull this together for me?
0:35:58 Because by the way, I’ve got literally one engineer
0:36:02 that works at the entire company, entire division that I’m in right now.
0:36:03 How am I going to do this?
0:36:05 That’s why we think it’s an outsource provider.
0:36:08 We think grocery stores and CBG companies
0:36:10 are either going to be buying it from a technology company
0:36:12 or they’ll have to buy that technology company,
0:36:13 bring it in-house.
0:36:16 It makes me think a little bit of automotive and traditional
0:36:19 Detroit car companies trying to become autonomous car companies.
0:36:22 And I think it’s fascinating because they could potentially
0:36:23 win on that front if the right competency is.
0:36:25 There are some really smart people in the grocery business.
0:36:26 Yeah, exactly.
0:36:27 Walmart’s diving in.
0:36:31 They’re also in top line sales right now in stores.
0:36:33 That said, it’s hard.
0:36:36 A lot of the best engineers might want to work for a grocery store
0:36:38 and might not want to live in Bentonville, Arkansas.
0:36:41 And then they’re incredibly low margin businesses.
0:36:44 So how do you hire a ton of really expensive engineers?
0:36:46 I give Walmart credit for making the bet.
0:36:47 They bought jet.
0:36:49 They bought a number of small–
0:36:50 They also have their own labs.
0:36:52 Like Walmart is known to be a little bit more innovative
0:36:54 with internal R&D than some of the other CBG players
0:36:55 that we’re talking about here.
0:36:58 But it’s not that the grocers aren’t capable
0:37:00 and don’t understand it.
0:37:02 They’re a bit of a prisoner’s dilemma.
0:37:05 There are extremely, extremely smart people working at both
0:37:08 large CBG companies and large grocery stores
0:37:10 that are in a really difficult position.
0:37:13 You think about what would you do if you were in their position?
0:37:14 Well, they’re out of business.
0:37:18 That’s, in the case of grocery, 2% net margin business.
0:37:20 How do they then say to their boss,
0:37:23 let’s go hire 150 engineers to go build this thing?
0:37:26 By the way, it’s not going to pay back for two or three years.
0:37:28 That’s a really, really hard proposition to make.
0:37:31 So I think incredibly talented smart people that work there,
0:37:33 it’s a hard position to be in.
0:37:35 One of the smartest people I’ve ever met in business
0:37:39 was the CEO of one of the largest consumer package companies.
0:37:42 And she came to Silicon Valley and wanted to sit down.
0:37:43 And I’m like, why are you here?
0:37:45 We believe software’s eating the world.
0:37:47 How is software eating snacks?
0:37:50 She came up with this very lucid argument of two things.
0:37:53 One is all of a sudden, there’s promotional transparency.
0:37:57 I used to move, gain share by going on special on knob,
0:38:00 Hills food one day and then special at Safeway.
0:38:02 Now the consumer knows exactly where I’m on special.
0:38:04 So I’ve lost the share moving thing,
0:38:08 all I’m doing is discounting and then nutritional transparency.
0:38:11 And so she says, I have to retool my company
0:38:15 because the two bedrocks that it was built on, software eight.
0:38:17 The challenge with that, and I, by the way,
0:38:19 I totally agree with that diagnosis.
0:38:22 The challenge then is that I don’t think that the CEOs
0:38:24 of these large CPG companies or large grocery chains
0:38:26 are given enough runway to go do that.
0:38:28 So there’s this, what we call 3G effect,
0:38:30 large financial institution down in South America
0:38:35 that has been investing into or buying public CPG companies,
0:38:36 basically stripping costs out.
0:38:39 And delivering shareholder value.
0:38:42 Problem with that is when you’re stripping the costs out,
0:38:44 one of the first things to go is R&D.
0:38:46 So you already had a problem for these large CPG companies.
0:38:48 What’s the percentage of R&D that they have?
0:38:51 So today, large CPG spends about 2% of sales in R&D.
0:38:52 Are you kidding?
0:38:55 Tech spends about 14% of sales in R&D.
0:38:57 CPG spends nothing on R&D.
0:39:01 And so- You have low margins, like 1.5 to 2% R&D.
0:39:01 That’s right.
0:39:03 So when you strip out costs,
0:39:06 I can deliver shareholder value and hit quarterly numbers
0:39:08 for the next, let’s say, year or two years.
0:39:10 But you look five, seven years out.
0:39:11 It’s not going to last long-term.
0:39:12 How far can you cut?
0:39:13 It’s like the activist investor problem, right?
0:39:14 That’s exactly right.
0:39:18 And so what we’re seeing is that many of these companies,
0:39:20 regardless of whether they’re doing that cost cutting or not,
0:39:23 they’re saying, look, we were already spending almost nothing on R&D.
0:39:24 How do we get the innovation?
0:39:26 And this goes back to a point Jeff made earlier.
0:39:27 That’s why CPG is beginning to look a lot
0:39:29 like Big Pharma has for the past 20 years.
0:39:31 So one last question then,
0:39:34 just to think about more on the data and innovation side.
0:39:36 All of us in this room are in the world of investing.
0:39:38 How does this change the investing game?
0:39:42 So in terms of how I think the investing landscape will change,
0:39:49 we have a pretty strong thesis that in CPG specifically,
0:39:52 there will be quantitative VC firms.
0:39:54 So what I mean by that is if you think of the public markets,
0:39:58 there are systematic quant funds that have historically,
0:40:00 over the last 20 years or so, in some cases 30 years,
0:40:05 invested into public companies basically just using technology.
0:40:07 It’s very different than a discretionary hedge fund
0:40:09 where you’ve got a team of really smart people
0:40:12 that research a stock for six months and make a decision.
0:40:14 In the case of a systematic quant fund,
0:40:17 they’ve got a lot of really, really smart engineers and data scientists
0:40:18 who are building algorithms to evaluate the company
0:40:20 and then make an investment decision.
0:40:23 We think that that is possible in some industries in the private markets.
0:40:26 We don’t think it’s possible in tech.
0:40:27 Why do you think that’s possible in CPG?
0:40:30 So there’s two main reasons that CPG is beautiful.
0:40:33 First, the business models are basically the same.
0:40:36 So what I mean is if I’m selling shampoo, dog food, or water,
0:40:37 the margins are different,
0:40:39 but I’m making a product and I’m selling the product.
0:40:40 It’s very different than tech.
0:40:42 In tech, I might give away the product for five years.
0:40:43 You might do a freemium, right?
0:40:44 I might do a SaaS business, et cetera.
0:40:45 Very different business models.
0:40:47 Because it’s the same business model,
0:40:49 it’s the same game of chess over and over again.
0:40:50 Interesting.
0:40:54 The second reason that there’s just an outrageous amount of data in this space,
0:40:59 but many of the dimensions that are predictive of success of a consumer company
0:41:01 are not data that you can get externally.
0:41:04 It’s hard to get information from afar.
0:41:05 In consumer, you can get it from afar
0:41:07 without ever talking to the company.
0:41:09 We have gone private financials on thousands of companies.
0:41:11 That acts as our training data.
0:41:13 The training data is private financials on thousands of companies.
0:41:15 And is that kind of providing the ground truth
0:41:16 in order to sort of compare the decisions again?
0:41:17 That’s exactly right.
0:41:18 Yeah, so it’s the ground truth.
0:41:23 So I need to know what success and failure looks like in order to predict it.
0:41:25 If you look at a SaaS company, a consumer company,
0:41:28 and an infrastructure company in tech, you can’t compare them.
0:41:31 Whereas if you’ve got two beverage companies,
0:41:38 and one is selling 20 units per Whole Foods per week at a 60% margin,
0:41:42 another selling 10 units per Whole Food per week at a 30% margin,
0:41:44 it’s pretty obvious which is the better company.
0:41:48 But also in CPG, I can find that company
0:41:50 just by using publicly available information.
0:41:52 So I can see that one of the two companies
0:41:55 started in one Whole Foods six months ago,
0:41:58 and now is in 400 Whole Foods and added 300 targets.
0:42:01 There isn’t really an equivalent in, let’s say, the SaaS world.
0:42:04 Going back to the SaaS world, while there might be structured metrics to look at,
0:42:06 and those metrics might be predictive of success,
0:42:08 almost all of them, not all, but almost all of them,
0:42:10 are only available once you start talking to the company
0:42:11 and you already know who to focus on.
0:42:14 I do wonder because when I watch a show like Billions,
0:42:16 you know, they have, they use data like empty parking lots
0:42:19 and aerial shots of an empty parking lot for retail
0:42:22 to be able to make a decision on whether to pull a trigger on a company or not.
0:42:24 The equivalent in SaaS might be developer heat,
0:42:28 like viral developer activity or the adoption rate among developers.
0:42:30 There’s various heat maps and sources.
0:42:32 The part that I have to ask on the big question
0:42:35 of quant investing in general, and especially in this case,
0:42:37 and even in our world, Jeff, which is more tech than CPG,
0:42:41 doesn’t it miss the outlier, the outsize winners?
0:42:42 It’s a great point.
0:42:43 It’s a great point.
0:42:43 Yeah.
0:42:46 So we, that’s another reason we struggle to believe
0:42:47 that it is possible in tech.
0:42:50 You think about many of the massive home runs in tech.
0:42:51 Exactly.
0:42:55 There weren’t prior examples that did something very similar.
0:42:56 No, they’re all, they’re all a priori.
0:42:57 Right. Yeah.
0:42:59 And so, so that’s why I really struggled to believe
0:43:00 that that’s possible in tech.
0:43:02 When you look at the winners and consumer,
0:43:04 the previous winners looked really similar.
0:43:06 That might have been a different,
0:43:07 might have been a different magnitude,
0:43:08 but they grew in really, really similar ways.
0:43:11 So this might be the one case where that phrase pattern recognition
0:43:13 that people throw around so wildly in the valley actually applies.
0:43:17 But who the winner was, wasn’t that still an irrational
0:43:20 behavioral thing versus something programmable?
0:43:24 So we’ve been able to show that there are some common themes
0:43:29 between both in A, why something wins and how it wins.
0:43:29 So here’s what I mean.
0:43:31 So you’re nuanceifying the two, which is really important.
0:43:31 That’s right.
0:43:36 So why typically the winners have, and look, to be clear,
0:43:37 this is not perfect.
0:43:39 There are holes, there are inaccuracies.
0:43:42 Typically the winners have brand intensity with the consumer.
0:43:44 So think of vitamin water 15 years ago,
0:43:49 kind bar 10 years ago, the brand really resonates with the consumer.
0:43:51 The second thing that is common amongst the winners in CPG
0:43:55 is the product has uniqueness that matters.
0:43:55 Interesting.
0:43:58 So kind bar is actually a pretty good example here.
0:43:59 When it first came out, everyone said,
0:44:00 “This is a really crowded category.”
0:44:03 By the way, everyone always says every CPG category is crowded.
0:44:06 Because they are, because they are, but they’re also massive.
0:44:08 Right, crowded but massive.
0:44:09 I like that distinction.
0:44:12 So kind bar, at the time though, what people missed was,
0:44:15 there’s Nature’s Valley, there’s Cliff Bar, a number of others.
0:44:18 When you look at those products, they didn’t look like real food.
0:44:21 Kind bar had an insight, which was,
0:44:23 “Let’s make a product that actually just looks like real food.”
0:44:24 That’s actually why I’m drawn to them.
0:44:26 I don’t feel like I’m eating a crappy processed bar.
0:44:28 Yep, and they actually show the food.
0:44:30 The biggest innovation for Guy Bar from my perspective is,
0:44:33 it’s see-through and you can see that there’s real food.
0:44:33 So you can see a whole lot to that.
0:44:35 And it’s not symmetrical.
0:44:35 Yeah, that’s exactly right.
0:44:36 Like it’s not this perfect rectangle.
0:44:38 It’s got like jagged edges where you can see it’s real.
0:44:39 It’s not processed.
0:44:41 Exactly, exactly, exactly.
0:44:45 So in that case, you know, you can build an algorithm
0:44:47 which evaluates the picture of the package.
0:44:49 And literally just says, “Is this different?”
0:44:51 So we’ve done that in the case of snack bars.
0:44:52 We track about 3,000 snack bars.
0:44:54 So you answer that question of, “Is it different?”
0:44:54 “Is it different?”
0:44:57 And then, now I could put fish in my snack bar
0:44:57 and it’d be different then,
0:44:59 but it may not resonate with the consumer.
0:44:59 Right, that would be great.
0:45:01 So those are two kind of orthogonal dimensions.
0:45:03 One is does it resonate with the consumer
0:45:05 and is the product unique?
0:45:08 The ones that have one tended to be high in both.
0:45:11 Then there’s the question of how it wins, right?
0:45:13 So why it wins and then how it wins.
0:45:16 The how it wins is typically distribution gains.
0:45:17 Distribution gains.
0:45:18 Meaning–
0:45:20 It’s because it’s not the one of Alex’s famous lines.
0:45:22 Like it’s always about distribution.
0:45:24 Yeah, yeah, it’s, and that is very true in CBG.
0:45:26 So there aren’t a lot of big winners
0:45:28 that have only been sold in five stores.
0:45:30 That’s not a thing.
0:45:31 So then if you think about,
0:45:34 okay, if it’s number of, it’s breadth and quality of doors,
0:45:35 meaning TG Max not as valuable
0:45:37 as let’s say Whole Foods or Costco.
0:45:40 So how do you measure breadth and quality?
0:45:41 That data is out there.
0:45:44 Where the product is being sold is out there in the world.
0:45:45 Whole Foods wants you to know it.
0:45:46 The brand wants you to know it.
0:45:48 Now it’s just aggregating that information
0:45:49 and making sense of it.
0:45:50 But that’s the how it wins.
0:45:52 And you can also get into price points.
0:45:53 You can get into skew count,
0:45:54 number of other things.
0:45:56 But marrying those two things together is the foundation.
0:45:58 But it’s basically one business model.
0:46:00 A couple of the differences in tech.
0:46:02 We’ve been trying to figure out,
0:46:04 how do you leverage data in the decision-making process?
0:46:05 Is this a holy grail?
0:46:09 Yes, we can probably define a dozen, two dozen,
0:46:12 three dozen different worlds of,
0:46:15 you know, universes of tech companies that are unique.
0:46:18 You have SaaS and open source and consumer.
0:46:20 And then within consumer, you have social and e-commerce.
0:46:23 So, you know, just by definition, comparison’s hard.
0:46:26 And then the other part you have is what you said,
0:46:28 most of the huge winners are lightning strikes.
0:46:30 Facebook was the second or third social network.
0:46:32 But, you know, no one was thinking social networks
0:46:35 when they talk about a trillion-dollar company.
0:46:40 eBay was collectibles online, weird, Facebook hot or not.
0:46:44 You know, these things, I mean, the Airbnb sleep on someone’s couch.
0:46:47 You know, these things don’t present as monster companies.
0:46:51 They start, hit a chord and are expanded
0:46:53 by their community of users.
0:46:54 And the thing I would add to that, by the way,
0:46:56 is that there’s a complexity math to this,
0:46:57 which is a little bit like the Brian Arthur,
0:46:59 we had Brian Arthur on the podcast.
0:47:00 And he’s the father of network effects
0:47:02 and network effects theory.
0:47:05 And the point of when that tipping point hits,
0:47:07 you don’t know when it tips.
0:47:07 That’s the hard one.
0:47:08 Yeah, yeah.
0:47:10 Like the when it seems like the really tough question.
0:47:11 Will it.
0:47:12 Then when, yeah, so it’s good.
0:47:14 And if you think of Jeff’s point,
0:47:15 like when Facebook hit,
0:47:17 there was two other social networks and maybe three.
0:47:17 Yeah.
0:47:19 There weren’t 300 or 3000.
0:47:20 Right.
0:47:21 There were very few examples.
0:47:24 You don’t have 40 or 400 examples
0:47:26 to begin to look at pattern recognition.
0:47:26 Right.
0:47:28 The n equals three or the CPG.
0:47:30 You’ve got massive data set.
0:47:33 So now I can compare certainly one ice cream company
0:47:34 to the many others that have hit.
0:47:36 But the difference between ice cream companies
0:47:37 and snack bars is not great enough
0:47:40 that you can’t compare the two and begin to see patterns.
0:47:42 Well, that was a fascinating discussion.
0:47:45 Ryan, Jeff, thank you for joining the ice cream company.
0:47:46 It’s a pleasure.
0:47:46 Thank you.
0:47:47 Thank you.
0:47:57 [BLANK_AUDIO]
0:00:12 on consumer tech trends. We’re talking all about the category of consumer packaged goods
0:00:18 or CPG and where this fits with what’s going on in online and offline commerce trends overall,
0:00:23 including when it comes to the grocery business. We also talk about the trends of DTC or direct
0:00:29 to consumer and the concept of micro or emerging brands as well. Joining us to have this conversation,
0:00:34 we have A6NZ General Partner Jeff Jordan, who’s written a lot about competing with Amazon and
0:00:38 the future of e-commerce and marketplaces and has been on the front lines of this area both as
0:00:43 an operator and investor, witnessing firsthand from many angles a lot of changes in the industry.
0:00:48 And then we also have Ryan Kahlbeck of Circle Lab, an investment platform powered by data and
0:00:53 technology. He also talks a lot about innovation in the CPG space and more, which is why we
0:00:58 invited him to join this discussion. Please note that the content here is for informational purposes
0:01:03 only should not be taken as legal business tax or investment advice or be used to evaluate
0:01:09 any investment or security. It’s not directed at any investors or potential investors in any fund.
0:01:15 For more details, please also see A6NZ.com/disclosures. The broader question that we covered throughout
0:01:21 this episode is how does technology and especially the internet change and in some ways not change
0:01:26 the way we do things. Why do some of the traditional businesses in these industries, though full of
0:01:32 some of the smartest people, have trouble innovating and can tech really help? In fact, that’s where
0:01:37 we begin the conversation with the assertion that it’s been hard to bring tech to CPG, even though
0:01:45 there seem to be a lot of products trying out there. As a user, I have a hard time perceiving this
0:01:50 because I am constantly bombarded with consumer products that are techie, whether it’s like
0:01:54 a thousand beauty product lines, there’s a thousand even generics lines that I’m getting hit with.
0:01:58 So I have a hard time grokking that this is a reality. Tell me what’s happening there.
0:02:05 It’s a great point. So I think, first, one of the reasons that you see that is the D2C movement,
0:02:11 which is direct to consumers. A handful of tech VC firms, they’re putting a fair amount of money
0:02:17 into consumer product companies that sell just direct to consumer or predominantly direct to
0:02:23 consumer. That money is usually not used for innovation, for product innovation. It’s usually
0:02:28 used for marketing. I agree with Ryan that they’re largely marketing companies. It’s actually
0:02:32 derivative of Amazon, unfortunately. If you want to play any e-commerce in a post-Amazon
0:02:37 era, you cannot sell what Amazon sells successfully. I mean, early on, we tried a number of concepts
0:02:43 that some are around anymore that said, okay, I can kind of sell the same thing as Amazon with
0:02:47 a different distribution twist with something like this, but you can’t. So then the next wave
0:02:52 of companies was, okay, if I can’t sell, I can’t compete with Amazon directly skew by skew,
0:02:58 let me get proprietary skews. And so they’re formulating different products with different
0:03:05 branding, and they typically aren’t on Amazon or on other retail. But that is where a lot of the
0:03:11 direct to consumer stuff is happening. And frankly, some success, not a ton of success
0:03:14 in doing it. Why is that, by the way? At some point, you’re still competing with
0:03:21 legacy players. And what’s worse is they’re also competing with each other. So there are a half
0:03:29 dozen, a dozen brands all trying to find you. Early on, they find you at $20 acquisition cost
0:03:34 when 10 of them go at each other. They’re competing for you, 10 companies trying to grow,
0:03:39 competing for you. And then that also caps their ability to price. So one of the big
0:03:44 secrets in e-commerce is virtually no companies get big and make money in the United States on
0:03:51 e-commerce. I can name five e-commerce companies in the US after two decades of investing and
0:03:56 God knows how many tens of billions of dollars who are a billion dollars in sales and profitable.
0:04:01 Yeah, I mean, you’re making the point, particularly around the rise in CAC. We see a lot of
0:04:07 DTC companies raise money with a CAC, let’s call it $10, $30. And then over the course of
0:04:13 subsequent two years, it raises literally sometimes by an order of magnitude. And that is just killing
0:04:17 their profitability. And by that, just to quickly summarize, you mean CAC is on customer acquisition
0:04:20 costs and they’re using all that marketing dollars to acquire their customers.
0:04:26 Exactly. I think when DTC directed consumer businesses, I think a lot of folks look at it
0:04:31 from the outside and say, okay, we’re stripping out the middleman, the retailer, the offline
0:04:36 retailer. And because of that, we can put that margin that the retailer gets into our business.
0:04:40 And this is going to be a wonderful business. The problem is that you need to attract people to
0:04:47 your site, right? To get people to come to your startup, to come to your URL and buy something
0:04:51 is a really difficult thing. And so that’s what’s driving these customer acquisition costs up.
0:04:55 Now, there are some DTC companies, Native Deodorant was bought. They only raised
0:04:59 two or three million bucks in total, sold for $100 million to Unilever.
0:05:03 Why did Unilever want to buy that company? Why wouldn’t they just make their own in-house brand,
0:05:09 another brand? The CPG companies, large ones, have lost the ability to innovate. They innovate
0:05:13 through acquisition now and they buy early. So Unilever bought Dollar Shave Club. Unilever
0:05:18 doesn’t have a shaving business. I don’t know Unilever Deodorant offerings, but I’m guessing
0:05:24 they saw something in there. So it and Biotech are kind of the same. The big pharma companies are
0:05:28 buying their innovation. The big CPG companies are buying their innovation. Historically,
0:05:34 large CPG has been able to rely on their brands. Brands that have existed literally in some cases
0:05:40 for 50 or 100 years. Meg, Scott Cook, and Brian, Sweetie, and Steve Ballmer, we’re all at P&G
0:05:45 together. Right after I graduated from college, Meg was the brand manager, I believe, on Crest.
0:05:52 Wow. That’s awesome. But can you think of that cadre of talent in all analysts in Cincinnati?
0:05:56 CPG seems like, because I have a lot of friends that go through their career starting at Clorox.
0:05:59 And it seems like sort of a training, there’s always like a mafia and a training ground that
0:06:02 people get some fundamental skills in these companies. So what are they actually getting
0:06:06 out of these companies? There’s a quote in one of the Apple movies, if you can sell sugar water,
0:06:12 you can certainly sell. That was Steve John’s quote, like he tried recruiting John Scully.
0:06:16 I think there’s probably something to that, right? To be able to sell literally the same product
0:06:19 for 30 years in a row. Think about trying to do that in the technology space. That’d be
0:06:26 impossible. There’s a fun book by a Harvard dean called Different. And it basically says,
0:06:31 almost all consumer goods are these small incremental improvements that everyone copies
0:06:38 because that’s the improvement that wider mouths on the Crest toothpaste because that you go through
0:06:44 it faster. Oh, so Colgate will do wider mouths and Spearman and whitening and versus brands that
0:06:50 kind of just throw it out and just do it differently. She uses Harley. She uses Apple. She uses Red Bull.
0:06:56 And they just came to market with completely, we are going to be different. And it’s so interesting.
0:07:02 I love the book because 99% is exactly the same. And then the 1% is different.
0:07:05 That gets back to the point of like why these large brands are losing market share.
0:07:11 The large brands have not had to innovate. They’ve been able to rely on their brands on,
0:07:16 whether it’s Coke or Pepsi or whatever it is, the same product, just their brand name for decades.
0:07:22 Now these smaller upstart brands, these emerging brands are able to develop the innovation in
0:07:27 house and deliver that to the consumer. The consumer, on the other hand, for the first time
0:07:32 in history is saying, I demand products that meet my unique needs. Maybe the three of us used to
0:07:37 eat the same breakfast cereal. Now the three of us are eating different things. We’re demanding
0:07:43 products that meet our unique needs. That customer consumer demand is pulling forward the innovation
0:07:46 and giving it a market. That’s why though, I just want to push a little bit more on this DTC topic
0:07:51 though, because when I think of the theory of the internet, which, you know, it disintermediates this
0:07:56 intermediary, you can go direct to people, you create movements on the internet. I mean,
0:08:00 talk about meme culture. Like if a meme can monetize, why the hell can’t a product?
0:08:03 So I’m still having a hard time buying why DTC is so hard.
0:08:07 The internet enables a long tail. So all of a sudden everything’s discoverable,
0:08:11 where it used to be, there were three television networks and 10 magazines that mattered.
0:08:18 The world is different. It used to have, you know, very narrow portals to work, which was great for
0:08:25 big companies that have stable product lines. So you couldn’t do TV on a $5 million revenue line.
0:08:29 You can do internet on a $5 million revenue line. Right. But that’s exactly my point,
0:08:33 is we have a world where we do have a long tail discoverability. You have the ability to access,
0:08:38 find your niche audience. You also have a world where you can still make hits on that long tail.
0:08:42 So you just describe why there’s a proliferation of CPG companies.
0:08:45 But why does DTC not work? That’s a part I don’t get.
0:08:49 When we say it doesn’t work, I think it is an incredible channel for iterating on a product.
0:08:54 I think it drives innovation. I can find my consumer base and I can test a new product.
0:08:57 Next month, I can test a different product. That’s very different than the offline world,
0:09:00 where if I’m selling into Safeway or Whole Foods or Costco down the street,
0:09:05 it’s hard for me to switch the product out if it’s not working, to tweak a package, whatever it is.
0:09:09 People in the technology space take that kind of A/B testing for granted. In CPG, it’s much,
0:09:12 much harder because you literally… Because it’s physical product and offline space.
0:09:14 Yeah, you have atoms, you need to move, not just bits.
0:09:18 And so if you run a chain of stores, actually a couple of my… All the companies that are
0:09:23 getting challenged growing, continuing to grow DTC sales are turning to offline retail in different
0:09:27 forms. Every company I’ve worked with is trying to do that because incremental sales…
0:09:29 That’s actually rather counterintuitive.
0:09:33 It is. But the way store management work, I used to be CFO of the Disney store, is
0:09:40 you try products. Typically, you do two or four sets a year and you try products in a
0:09:44 significant subset of your stores because if it’s a bomb, you don’t want to buy
0:09:48 deep in it. So you’ll put it in five stores a test for the first six months.
0:09:52 And then they say, “That worked well. Let’s go to 50 stores for the next six months.”
0:09:56 And then by the time you get chain-wide, it literally is a couple of years later.
0:10:00 And so it’s really hard to grow your business.
0:10:03 And that’s for Disney stores where you have your own product in the store.
0:10:09 So if you think of the CPG products, they’re selling through a third party, the retailer.
0:10:14 Now, they have to make a much bigger bet. They can’t usually just start in five safe ways.
0:10:18 So they have to start in 200. Now when you start in 200, flipping that and changing that product,
0:10:21 if it didn’t work, it can kill the company.
0:10:26 When I was at Xerox PARC, one of the companies we partnered with was a large CPG company.
0:10:30 And their number one challenge was trying to figure out what happens after the consumer
0:10:33 buys the product. They had zero insights.
0:10:35 Oh, actually, it’s even worse. They have zero insight.
0:10:40 They know what they sell into the retail chains. They don’t know what’s sold where to who.
0:10:41 Right. Seriously?
0:10:41 No. It’s incredible.
0:10:42 It’s absolutely incredible.
0:10:44 That’s great. That’s crazy. How is that not possible?
0:10:47 So people who are listening to this will respond, “Well, what about credit card data?”
0:10:50 The problem with credit card data is it can tell you what the retailer is selling,
0:10:51 not what was bought at the retailer.
0:10:54 So I can see what Nordstrom.com sales for last month.
0:10:56 I can’t see what pairs of jeans were bought there.
0:10:58 Why not? Doesn’t it say?
0:10:58 They don’t sell.
0:11:00 Isn’t that the whole point of a skew?
0:11:03 No. Well, yeah, but these credit card companies don’t sell it.
0:11:08 And more importantly, back to Jeff’s point, they don’t tie those products to individual people.
0:11:16 Some retailers have loyalty card data, but there’s privacy issues with them selling that.
0:11:22 $84.51, a division of Kroger sells part of it, but not in the way that we’re talking about here.
0:11:26 They can say, “This person who I can, by the way, I can match Sonals,
0:11:29 what her purchasing power to your Instagram account, that is not done anywhere.”
0:11:33 Typically, CPG marketing is you buy a circular in the Sunday paper.
0:11:35 You buy an end cap, and you have no idea–
0:11:37 An end cap being the little display at the end of the grocery store.
0:11:38 At the end of the aisle in the grocery store.
0:11:42 And billions of dollars goes into those, and who knows if it works.
0:11:48 And they certainly don’t have any data beyond, “Oh, our total sales went up a little bit there.”
0:11:53 One of the key things that was compelling about Instacart to us is that they have a revenue
0:11:56 stream from the consumer, a revenue stream from the grocery retail partner,
0:12:00 and a revenue stream from CPG companies who are interested in accessing the consumer.
0:12:04 Why the CPG companies were so interested in that is,
0:12:06 it’s the first performance marketing they’ve ever seen.
0:12:09 On something like Instacart, they know everything I’ve ever bought.
0:12:15 And if they know I love Heineken beer and the product manager of Stella wants to try to convert me,
0:12:19 they can give me a Stella coupon, a Stella samples, a Stella, everything else.
0:12:21 And then see, did I change my behavior over time?
0:12:23 That’s the holy grail of marketing.
0:12:24 The holy grail for marketing.
0:12:26 I mean, performance marketing, like that type of data,
0:12:29 like closing that feedback loop is a big F-deal.
0:12:34 They also over time have the ability to kind of literally move the product on the page, right?
0:12:36 Which if you think about offline retail, you can’t do.
0:12:38 What do you mean by on the page?
0:12:43 Meaning when you’re looking at Instacart, what product you’re looking for can be moved physically.
0:12:47 Oh, like kind of personalized rearrange to your needs.
0:12:47 Exactly.
0:12:48 Which you cannot do in a physical way.
0:12:50 And it’s completely obvious in tech.
0:12:52 But for people that are in CPG, it’s a game changer.
0:12:57 So I was in a Safeway half a mile from here on Sand Hill six months ago,
0:12:59 and was buying some steak.
0:13:01 Steak was in the refrigerator.
0:13:04 Next to the steak in the refrigerator were wood chips.
0:13:06 The wood chips have no need to be refrigerated.
0:13:08 They’re literally just wood chips to put in a barbecue.
0:13:11 They’re in the refrigerator because they’re on sale.
0:13:13 And they want to put them next to the steak.
0:13:14 That’s it.
0:13:16 And so you’re refrigerating literally wood.
0:13:17 That’s crazy.
0:13:19 Because back to Jeff’s point, if I bought an end cap,
0:13:21 the end cap would have been 30 feet away.
0:13:23 Then you would have lost the consumers.
0:13:24 And they need to have that proximity.
0:13:26 That’s a crazy awesome example.
0:13:27 I love that.
0:13:30 Let’s talk about grocery for a little bit as an interesting category.
0:13:35 So first of all, is grocery going to go the way of malls and other retail?
0:13:37 So I’ve got a not very popular opinion on this.
0:13:38 Let’s hear it.
0:13:39 The more popular, the better.
0:13:43 I think grocery stores are here for the very, very long term.
0:13:46 Very long term, meaning next 20 years at least.
0:13:50 So taking a step back, D2C and e-commerce has been around for 20 plus years.
0:13:52 This is not a recent phenomenon.
0:13:55 Food is still, Jeff, you could tell me, I think 5% of sales.
0:13:56 Of digital?
0:13:56 Yeah.
0:13:57 Way under.
0:13:58 Yeah.
0:14:02 I don’t foresee a world in which everyone is just going to go online, A.
0:14:07 And B, when that happens or when it gets to be a much higher proportion of where you buy
0:14:13 your groceries, I still think that that grocery is going to be delivered locally.
0:14:18 But the core point is grocery today, 2%, 3% net margin business.
0:14:21 That’s hard to strip out a lot of costs from that.
0:14:21 There’s not a lot of room left to go.
0:14:23 You can’t do any cost cutting at all.
0:14:23 That’s right.
0:14:29 So you think about where technology has been particularly successful at killing other industries.
0:14:32 They tend to be industries where there’s a fair amount of profit, right?
0:14:35 It’s also like Bommel’s cost disease, too, if you think about it, eventually penetrating
0:14:39 health care and education, like things that are way more expensive than they need to be.
0:14:41 And technology is a vector to just cut right through that.
0:14:42 Absolutely.
0:14:46 But the safety down the street has a 1.5% net margin.
0:14:48 So what are we going to do to rip the cost of that?
0:14:52 Because that thing is already delivering a pretty good product to the people that live within a
0:14:53 mile and a half of here.
0:14:57 I mean, there was a set of companies that was trying to help physical retail compete
0:14:58 with the digital commerce.
0:14:59 And it was so interesting.
0:15:04 We didn’t invest in many of them at all because our internal reference was we’re shorting the
0:15:05 future.
0:15:08 You know, just so it’s not a long-term winning proposition and their margins are going to
0:15:10 get squeezed, so they’re going to squeed their vendors.
0:15:13 Then we made the Instacart investment in the belief that the grocery stores are there.
0:15:15 It’s distributed.
0:15:17 They have distributed little warehouses.
0:15:18 They provide service.
0:15:19 And it was interesting.
0:15:22 Fred Smith, the founder of FedEx, when the internet first came up said,
0:15:26 “I think a whole lot of goods are going to be delivered by FedEx.
0:15:27 Groceries ain’t going to be one of them.”
0:15:32 Because the concept that you’re going to load a truck in the morning and having
0:15:36 bouncing down the streets and this and that and deliver at 8.
0:15:40 It’s something at 8 p.m. that was put in the truck at 4.30 a.m.
0:15:42 And he just said, “I don’t think it works.”
0:15:47 Building up the shopper network is so hard to replicate for someone else going forward.
0:15:50 It’s not as simple as, “Let’s just hire FedEx to go do this thing.”
0:15:54 Oh, and the operational intensities observe.
0:15:58 We think in grocery, we think effectively there are a couple different dimensions
0:15:59 that grocery chains need to compete on.
0:16:01 We think it’s assortment.
0:16:03 We think it is convenience.
0:16:05 We think it is pricing and experience.
0:16:07 Pricing is a really, really hard place to compete on.
0:16:10 You’re competing with Amazon to a point that Jeff made earlier.
0:16:12 You’re competing with Walmart.
0:16:14 I think that’s just a really, really hard place to win.
0:16:15 Yeah, you can’t win on price.
0:16:18 Especially when you already have this 1% to 2% margin.
0:16:20 Exactly. The margins are already so low.
0:16:22 So let’s put pricing aside for a second.
0:16:28 I also think that grocery is, in some ways, an experience for some people.
0:16:33 An experience for the consumer to go in, perhaps with the family,
0:16:36 perhaps just buy a couple of things here and there.
0:16:38 They want the immediacy of that.
0:16:41 We don’t see that going away anytime soon.
0:16:43 I think it’s going to be hard to win, again,
0:16:47 because how do you invest into an experience if you have such low margins?
0:16:49 I will say one quick sidebar on experience,
0:16:50 such as if Connie were in this room,
0:16:52 she talks a lot about what happens in China.
0:16:55 And she talks about this incredibly fascinating phenomenon
0:16:59 where grocery stores in China have become destinations themselves
0:17:01 because there’s literally restaurants inside.
0:17:04 They’re doing all kinds of neat food chef things, etc.
0:17:06 Cooking on site, doing all these interesting things.
0:17:07 I mean, what should you take on that?
0:17:10 I was with the CEO of a large grocery chain about a month ago
0:17:12 who made that same point.
0:17:14 They are starting to experiment by putting restaurants,
0:17:18 effectively restaurants, inside their grocery chain.
0:17:22 The local Asian supermarkets almost all have restaurants forever.
0:17:23 Indian ones, too.
0:17:25 They have like samosas for $2.
0:17:25 Yeah.
0:17:30 I would say I think it is nice to have not a requirement to be successful.
0:17:33 I’m not convinced that that’s going to be the core differentiator going forward.
0:17:35 So what do you think is going to be the core differentiator?
0:17:35 You had one more dimension.
0:17:38 Well, convenience and assortment, those are the last two.
0:17:40 So convenience, to me, is delivery.
0:17:41 Delivery or in-store pickup.
0:17:45 I think that that will end up being table stakes, not a nice to have.
0:17:47 Meaning you need to have convenience.
0:17:50 Well, my question on this is why bother even having a grocery store
0:17:51 if you only need to deliver?
0:17:53 Why not keep warehouses then?
0:17:54 If experience isn’t going to win the thing.
0:17:56 Like why not just have a bunch of warehouses
0:17:57 that deliver food if delivery is the thing?
0:17:58 Yeah.
0:18:01 So to be frank, that could be the 50-year vision.
0:18:02 That really could.
0:18:04 In the UK, which for whatever cultural reason
0:18:06 has been doing grocery delivery for a long time
0:18:09 and it’s a much deeper state of penetration,
0:18:11 they’re starting to have what’s called dark stores,
0:18:14 where you basically, they look a lot like supermarkets.
0:18:16 They’re locally distributed.
0:18:17 They have inventory assortment,
0:18:19 but they’re not in high traffic parts of town,
0:18:22 which means the rents are much, much lower.
0:18:26 And so, as a result, you don’t have to make it pretty.
0:18:28 You don’t have to have the lights, lots of lights.
0:18:29 You don’t have to have high labor.
0:18:30 All you have to do is pick in them.
0:18:33 And so that is how grocery has been developing
0:18:36 in one of the most advanced digital grocery markets.
0:18:39 So it’ll be interesting if whether that happens in the US,
0:18:43 every argument that I can make on why grocery stores won’t
0:18:46 just be warehouses where it gets delivered from,
0:18:49 every argument that I can make is a short-term argument.
0:18:51 I can’t make a 50-year argument for that.
0:18:53 So I think that that could happen.
0:18:55 Over the next 10 years, I don’t think customer adoption
0:18:56 will be big enough to get rid of these stores.
0:18:59 These stores, these aren’t little mom and pops.
0:19:02 They’re Fortune 500 companies that would not go down
0:19:03 without a really big fight.
0:19:04 No, and I think there are destinations.
0:19:06 I mean, I see like families on the weekends all the time.
0:19:08 It’s like, it’s an outing to go to the grocery store,
0:19:10 which if they had like a daycare,
0:19:12 I think that would be a huge win, frankly.
0:19:14 That alone would be a big differentiator.
0:19:15 I would love that.
0:19:16 I know, I think everybody would take that.
0:19:18 I exclusively shop through Instagram.
0:19:20 I do our family’s grocery because I can’t bring the kids
0:19:23 to the grocery store because it’s too much of a disaster.
0:19:26 So I believe that convenience will be table stakes.
0:19:29 So then it comes down to what is the way grocery wins?
0:19:30 What are the way grocery store competes?
0:19:32 To me, it is just about assortment.
0:19:33 That’s your fourth dimension.
0:19:33 This is the fourth dimension.
0:19:36 After price, experience, convenience, and now assortment.
0:19:37 That’s right.
0:19:40 Assortment is what are the products that are on the shelf?
0:19:43 So if you think the last 80 years,
0:19:46 it has been, well, what’s Pepsi gonna give us this month?
0:19:49 Coke, General Mills, Unilever, Procter & Gamble, et cetera.
0:19:50 Today, as we’ve talked about,
0:19:53 consumers want brands and products to meet their unique needs.
0:19:57 The problem with that is that the buyer at the retailer,
0:20:00 meaning the person that selects, let’s say, the chocolate company,
0:20:03 the buyer at the retailer is still the same buyer
0:20:06 that lived there 20 years ago in some cases.
0:20:08 They don’t use a lot of data.
0:20:10 They’re literally trying chocolate bars
0:20:11 to decide what goes on the shelf.
0:20:13 That’s a really hard place to be in a market
0:20:16 that is trillions of dollars
0:20:19 to decide which of these emerging brands they want to work with.
0:20:23 So the default is, gosh, maybe I just rely on the big brands
0:20:24 to tell me who to work with.
0:20:25 That’s a real example.
0:20:27 Sometimes the big brands literally say,
0:20:29 work with these emerging brands.
0:20:30 Maybe I work with the distributor,
0:20:33 who, by the way, has paid more than by the larger brands.
0:20:35 But there isn’t really a good solution
0:20:38 for a lot of these Fortune 500 retailers
0:20:41 on how to optimize their assortment.
0:20:45 The data that exists for these grocery chains is pretty poor.
0:20:48 You’ve got a couple retail-level sales providers
0:20:51 that on average track 20,000, 30,000 products,
0:20:53 or companies, rather, each.
0:20:56 There’s about a million and a half out there.
0:20:58 A million and a half, and they cover less than 5% of them.
0:21:00 And even the grocery and food shows, aren’t they?
0:21:03 Sort of like, I’m thinking of the equivalent in fashion
0:21:03 and boutiques.
0:21:05 You essentially have a fashion show
0:21:07 to curate all the brands, the emerging brands,
0:21:09 the existing brands, new product lines.
0:21:11 Why isn’t there an anthropology of grocery stores?
0:21:13 Because when I think of anthropology as a retailer,
0:21:16 they have assortment because they go around the world
0:21:17 to find a variety of designs.
0:21:20 So it works very well for a certain demographic of women,
0:21:22 like in their 20s, 30s, et cetera.
0:21:25 Then you have to say, which of these will my consumers
0:21:27 respond to at the rate price?
0:21:29 So you get exposed to the million,
0:21:33 but then I can only carry X,000 in my store.
0:21:34 How do I figure that out?
0:21:36 Online might actually help,
0:21:38 because you can put infinite selection online
0:21:39 and see what’s selling.
0:21:42 So if you’re a grocer, I’d be looking at my online sales
0:21:44 just to inform my offline sales.
0:21:46 Like, oh, wow, that’s a breakout hit online.
0:21:48 Why wouldn’t it be a breakout hit offline?
0:21:51 Interestingly, then, you might come back to a customer
0:21:53 acquisition challenge for the CPG companies,
0:21:56 which is if we have a ton of products online,
0:21:57 how do we then stand out?
0:21:59 That comes back into advertising.
0:22:00 This kind of vicious circle.
0:22:01 Or virtuous.
0:22:02 Or virtuous.
0:22:03 It’s a skewed sample, too.
0:22:05 Like what happens online and offline sometimes.
0:22:05 It’s definitely skewed.
0:22:08 But if you’re in a complete information vacuum,
0:22:09 which essentially these guys are, at least you have something.
0:22:11 Even, by the way, loyalty cards are a really skewed sample.
0:22:14 That’s a very self-selected, self-interested group.
0:22:16 You’re not really getting the huge untapped space
0:22:16 of what people want.
0:22:19 You’re not, but you’re actually finally getting data
0:22:21 on a per person basis to kind of understand what’s there.
0:22:22 Exactly.
0:22:26 It’s hard to understate how blind most buyers
0:22:29 at most physical retailers are right now.
0:22:31 Yeah, they’re just kind of, it’s instinct.
0:22:33 It’s, you optimize the current assortment.
0:22:36 But then how do you layer in new things is,
0:22:38 and there’s a plethora of new things.
0:22:39 Or just everything that you don’t know
0:22:41 people have the taste for.
0:22:41 Exactly.
0:22:42 So you think about that you’ve got a buyer
0:22:44 for the chocolate category, right?
0:22:47 And that could be an older, candidly white male
0:22:49 who’s making a decision on the entire category.
0:22:50 For a very diverse audience.
0:22:53 By the way, not diverse racially by age,
0:22:57 a certain gender, demographic, location.
0:22:59 So should we be selling the same thing in LA
0:23:00 that we do in Vermont?
0:23:02 So how are people going to get this data?
0:23:03 Because right now Jeff is describing
0:23:04 that they’re desperate for data.
0:23:06 So they have to rely on these,
0:23:07 they have to get data somewhere.
0:23:09 But that’s still adverse selection type data.
0:23:11 It’s not like the true opportunity space of data.
0:23:12 So where does the data come?
0:23:15 Broadly speaking, in consumer,
0:23:16 there’s a really beautiful thing
0:23:17 that a lot of people that don’t live and breathe
0:23:19 this space, they don’t recognize,
0:23:21 which is there is a tremendous amount of data
0:23:22 that’s out there in the world.
0:23:26 Meaning I can already see where a product is sold,
0:23:28 how many SKUs a company has,
0:23:30 meaning how many products that company sells,
0:23:32 what the price points of the products are,
0:23:33 what the end users think of the product.
0:23:34 And if I’m tracking it,
0:23:37 I can see how all those things change every single month
0:23:39 and how they compare to every other company in the category.
0:23:43 Those factors have been shown to be predictive of success.
0:23:46 People can aggregate those.
0:23:47 Now the challenge,
0:23:48 and this is where it gets really tricky.
0:23:51 The challenge is that you’re consolidating information
0:23:53 across literally hundreds of unstructured data sources.
0:23:55 It’s extremely intensive,
0:23:57 extremely intense and very difficult.
0:23:59 Sounds like a deal for an AI solution.
0:23:59 Yeah, it is.
0:24:00 It is.
0:24:01 But the data is out there is my point.
0:24:05 We think that that data is going to start getting consolidated
0:24:08 by data providers, technology companies,
0:24:11 that then sell it to the CBG companies,
0:24:13 or in this case, the grocery chains.
0:24:15 So the data opportunity, do you believe that?
0:24:15 Yeah, no.
0:24:17 We actually have seen a ton of companies trying to do it.
0:24:23 The interesting part is how hard they have to work to get the data.
0:24:24 There have been a whole bunch of them
0:24:28 that are trying to incent consumers to take pictures of their receipts
0:24:29 and submit the pictures.
0:24:32 And they do Optical Character Direct Edition on the picture
0:24:34 to try to reverse engineer.
0:24:36 What did Jeff buy?
0:24:37 We’ve seen multiple companies trying to do that.
0:24:39 There are other approaches too.
0:24:42 There was an on-demand,
0:24:45 they’d send armies of people with smartphones
0:24:46 to take pictures of shelves
0:24:48 so that they know the competitive pricing.
0:24:53 Oh, look, Crest is $2.29 and Colgate is $3.15.
0:24:54 What happened to sales?
0:24:57 But they don’t know what Colgate and Crest is,
0:24:58 and so they don’t know.
0:25:03 All they know is my philosophy in the southern region slowed down.
0:25:04 Or it’s sped up and you don’t know why,
0:25:05 which is equally problematic actually.
0:25:07 In the case of the receipts companies,
0:25:08 we’ve seen a lot of those too.
0:25:10 The challenge has been many of them tap out
0:25:13 at five, 10 million consumers, at least here in the US.
0:25:16 The problem with that level is that then,
0:25:18 that’s such a small portion of the overall population
0:25:21 that you’re not capturing the long tail of companies.
0:25:25 The chances that the $5 million popcorn company
0:25:29 is bought in a population that small is relatively low.
0:25:30 They’re going to be buying
0:25:31 the Procter & Gamble’s General Mills of the world,
0:25:33 but then you’re just getting more data
0:25:34 on the larger companies.
0:25:35 They need it on the smaller ones.
0:25:37 Exactly, they need data on the long tail.
0:25:40 Okay, so in this world, this long tail world,
0:25:42 this world of offline and online distribution,
0:25:44 and those are the two distribution broadly
0:25:45 that we’re talking about.
0:25:47 We are seeing a lot of microbrands,
0:25:48 and we didn’t talk about that
0:25:50 when we were talking about direct-to-consumer.
0:25:51 I mean, there’s a whole lot of media pieces
0:25:53 dissecting this phenomenon.
0:25:54 First of all, what is a microbrand
0:25:57 and why does it matter, or is it just a hypey thing?
0:25:59 Yeah, so let me just clarify.
0:26:02 By microbrand, you mean an emerging consumer product company
0:26:05 typically called less than $10 or $15 million in revenue.
0:26:08 So yes, but I think you’re the one who argues
0:26:10 that it denotes size, not channel,
0:26:12 because the way I’ve read it in the media,
0:26:13 it does talk about it as well.
0:26:15 Yeah, so the recent Economist article
0:26:16 kind of confused the two.
0:26:17 They started talking about microbrands,
0:26:19 and then they said, basically implied
0:26:21 that microbrands means D to C.
0:26:24 Micro to me, unless I’m missing something,
0:26:26 denotes size, not channel.
0:26:28 So I don’t really love that term to be candid with you.
0:26:29 Why didn’t you like it?
0:26:30 Well, for the same reason,
0:26:32 I would imagine that the entrepreneurs around here
0:26:35 wouldn’t like it if we called them micro technology companies.
0:26:36 They’re starting companies
0:26:37 because they want to build something big.
0:26:41 And I think that sometimes that comes across
0:26:43 as a little bit high and mighty, perhaps,
0:26:46 but especially if it’s just an ice cream company.
0:26:47 But look, I’ll be frank with you.
0:26:51 The ice cream company that’s able to strip out
0:26:53 fat and calories from the ice cream
0:26:54 and still deliver great products,
0:26:56 to me, is having a bigger impact on the world.
0:26:57 This is like Halo, right?
0:26:59 Halo Top, yeah, it’s exactly right.
0:27:03 So when we talk about them as emerging brands,
0:27:07 so emerging brands can be sold certainly offline or online.
0:27:09 But what’s happening,
0:27:12 these brands are growing very, very quickly right now.
0:27:14 In every single category in consumer,
0:27:17 large brands are losing share to emerging brands.
0:27:19 And the large brands are just terrified by this.
0:27:20 So why is it happening?
0:27:22 We think three primary reasons.
0:27:25 First is what we talked about
0:27:27 before the personalization of the consumer.
0:27:29 Consumers are demanding products that meet their unique needs.
0:27:31 Two other reasons that are pretty relevant
0:27:32 to this conversation.
0:27:36 One is decline in distribution costs.
0:27:39 Really, instead of just saying it’s a decline,
0:27:41 it’s really a shift from fixed costs
0:27:43 to variable costs.
0:27:44 And that’s because of the internet,
0:27:46 like the entry point to be able to buy,
0:27:47 get up a business up and running.
0:27:50 The internet is part of the driver,
0:27:52 but I don’t want to imply that that is the key driver.
0:27:55 In my view, it’s more that the offline retailers
0:27:58 are hungry to work with the small brands.
0:27:59 They’re struggling to figure out how to do it.
0:28:01 And so what we’re seeing is many of the offline retailers
0:28:04 are eliminating or lowering slotting fees.
0:28:07 Slotting fees are the cost to get your product on the shelf.
0:28:08 So if I want to launch a new chocolate bar
0:28:09 to get on the shelf of Safeway,
0:28:12 it is literally $50 to $100,000 just to get it on the shelf.
0:28:13 Think about that for a second.
0:28:15 If it’s the Apple App Store to launch an app,
0:28:18 it’s $100,000, it’d be a huge buried entry.
0:28:21 That fixed cost is declining rapidly
0:28:22 over the last five or 10 years.
0:28:23 Because these big brands are eager for–
0:28:25 The grocery stores are eager for these smaller brands.
0:28:27 More assortment, actually.
0:28:27 That’s right.
0:28:29 The third driver for why these emerging brands
0:28:32 have been so successful over the last five or 10 years
0:28:33 is marketing costs.
0:28:36 And that does get back to your point about the internet.
0:28:39 So marketing costs have also flipped from fixed to variable.
0:28:41 Fixed, meaning it used to be, let’s buy an ad in us weekly.
0:28:42 It cost me $100,000.
0:28:43 Or Jeff’s circular example.
0:28:44 Circular example is a great one.
0:28:47 Today, it is, let’s say, it’s the dollar-shaped flood YouTube ad.
0:28:50 And that’s an extreme example.
0:28:52 But you’re able to at least get your product out there
0:28:54 on a variable cost basis.
0:28:57 Because the flick fixed to variable transition,
0:29:00 these smaller brands, these emerging brands,
0:29:02 are able to grow much more effectively
0:29:03 than they could have 10 years ago.
0:29:05 So it literally is a variable cost.
0:29:07 When I was managing eBay, we were doing TV
0:29:09 and it was $1 million to produce an ad.
0:29:13 And then $10 million to distribute it with a frequency
0:29:15 that the brand people thought was efficient.
0:29:20 So $11 million was the ante to go on television for eBay at the time.
0:29:24 And so now you can go buy a $10,000 of Facebook ads
0:29:26 and try to reach your core audience.
0:29:28 So when you think about where this goes
0:29:30 in terms of innovation in the consumer space,
0:29:33 we think that over the next 10, 15, 20 years,
0:29:36 the brands that win, there will be more of them,
0:29:39 but they will get to a smaller level.
0:29:41 So what I mean is in the last 10 or 15 years,
0:29:44 the brands that won, Chabani, et cetera,
0:29:47 you can build multi-billion-dollar businesses.
0:29:51 I’m skeptical if that’s true in CPG going forward.
0:29:52 I mean, it’s almost math
0:29:56 because the total grocery market’s growing one or 2% a year.
0:29:58 If the number of brands proliferate,
0:30:00 the average revenue per brand should come down.
0:30:01 That’s exactly right.
0:30:04 But there’s no possibility for a player
0:30:08 like with Coke or Pepsi or white vitamin water or LaCroix.
0:30:10 So there’s certainly some very, very smart people
0:30:12 that disagree with me on this point.
0:30:17 I don’t see a world in which consumers want less options
0:30:19 where they’re saying, “Look, I want to go to the grocery store.
0:30:20 I want to go on Instacart.
0:30:22 And I only want to see one chocolate bar.
0:30:25 I don’t want to see something that’s different
0:30:27 for Sonal versus Ryan versus Jeff.
0:30:28 We don’t foresee that happening.”
0:30:31 Yeah, my view on that whole debate always comes down
0:30:34 to when people talk about more choice versus less choice.
0:30:36 Always comes down to actually what is the right choice for me.
0:30:38 And that does go to your point about personalization.
0:30:41 But the nuance I would say and data
0:30:42 is that it doesn’t necessarily have to do
0:30:43 with how many choices you have,
0:30:45 but that the right choices are presented to you.
0:30:45 Absolutely.
0:30:47 And that’s going to be a huge challenge.
0:30:49 Whoever the grocery chain or in this case,
0:30:50 or in the case of Instacart,
0:30:53 is to be able to present the right choices to you.
0:30:55 But we don’t think that the answer is going to be,
0:30:57 “Let’s strip out the choices altogether.”
0:30:57 Right.
0:31:01 And in 20 years ago, the choice was Coke or Pepsi.
0:31:03 But if now you go into the beverage aisle
0:31:06 and there’s things that I don’t even recognize where I am.
0:31:06 Right.
0:31:07 You know, just saying you’re just like–
0:31:08 I really don’t even understand
0:31:09 still why people love LaCroix so much.
0:31:12 It’s just like water with like a little hint of a taste.
0:31:12 I still don’t get it.
0:31:13 It is passion fruit.
0:31:16 I’m so confused over this.
0:31:17 Well, let’s talk about data then.
0:31:19 So we’ve been scooting around this topic of data for a while.
0:31:20 The biggest thing I’ve heard so far
0:31:23 as we talk about online to offline
0:31:25 is that in the offline world,
0:31:27 it has been nearly impossible to get the data we want.
0:31:29 On one hand, I’ve heard you say, Ryan,
0:31:31 that there are many data sources out there
0:31:32 that are really good proxies
0:31:34 and that we can do a lot.
0:31:36 But Jeff, you’ve also said that people are starved for data,
0:31:38 that things are missing.
0:31:40 So tell me what the status is in the world of CPG and data.
0:31:43 Like where are we right now really on where–
0:31:46 how far data– what data can do in this world?
0:31:47 Well, so I think both are true.
0:31:49 Both that there is a lot of data
0:31:51 and that people are starved for data.
0:31:54 And the bridge there is that while there is an outrageous amount
0:31:56 of data in this industry,
0:31:58 the data is very hard to pull together.
0:32:01 And in some cases, impossible.
0:32:04 It’s just impossible to actually go get it.
0:32:08 So the data that’s out there around distribution,
0:32:09 around product uniqueness,
0:32:11 how unique a product is relative to its competitive set,
0:32:14 on what the user thinks of the product,
0:32:17 on the competitive set of that product, et cetera,
0:32:19 all that data is out there in the world.
0:32:20 And if you begin to kind of think about
0:32:22 where would I get that data?
0:32:24 Well, most brands are not trying to hide.
0:32:26 There’s no concept of living in stealth in consumers.
0:32:29 Yeah, you can’t really, like, hide your toothpaste.
0:32:32 That’s right. When I launch in my chocolate bar in the Whole Foods,
0:32:34 Whole Foods wants you to know that you can buy the Whole Foods,
0:32:36 and I want you to know you can buy the Whole Foods.
0:32:39 Similarly, I want you to know what’s in the product.
0:32:40 How you have an ingredient deck and nutritional panel
0:32:43 that’s mandated by the FDA, but it’s out there.
0:32:46 Then consumers talk about my chocolate bar.
0:32:47 That’s also key.
0:32:50 So people can begin to understand what people think of it.
0:32:53 They get the sentiment analysis of the data of the chocolate bar.
0:32:55 So if you think about, you know,
0:32:58 rewind to the first year slack was in existence, right?
0:33:00 So if you could see every customer that used slack,
0:33:03 what they paid for it, what the end users thought of the product,
0:33:05 and how all of those things changed every single month,
0:33:08 that’d be pretty valuable data for a lot of people to have.
0:33:12 You have that data on every single CPG company in existence.
0:33:13 It’s out there.
0:33:13 Who has it?
0:33:15 Well, that’s the challenge, right?
0:33:19 So the challenge is basically it’s out there living somewhere on Google.
0:33:22 Meaning if you Google the smallest brand you can find,
0:33:24 you can see everything that I just said.
0:33:29 The challenge, though, is how do you pull all that unstructured data together
0:33:30 and then normalize it?
0:33:32 So I see a brand on Amazon.
0:33:36 I see the same brand being sold and Whole Foods being talked about on Instagram, etc.
0:33:39 So a process that we call entity resolution.
0:33:42 I remember this from NLP where you have to essentially find the same entity
0:33:43 with different variations or names on it,
0:33:46 but be able to resolve that it is the same entity.
0:33:47 It’s an incredibly hard problem.
0:33:49 Right. It’s a lot harder than people think.
0:33:50 Yeah. And then on top of that,
0:33:55 you also have the problem of how do you know that that product is a chocolate bar
0:33:56 and not a pair of shoes?
0:33:57 That sounds like an easy problem.
0:34:00 I have eaten chocolate bars that taste like a bar of shoes.
0:34:03 You’re right. Chocolate bars do taste like shoes.
0:34:04 Not that I’ve actually eaten shoes.
0:34:06 I mean, have you eaten shoes?
0:34:07 You’re a basketball player.
0:34:08 I always put my foot in my mouth.
0:34:11 So that’s another challenge.
0:34:13 Is that now you think about the people that want to consume this data.
0:34:20 Grocery chains, large CPG companies, they’re not equipped to pull all that data
0:34:24 and structure data in, normalize it, make sense of it, match it together.
0:34:25 That’s not a core competency for them.
0:34:29 That’s why I strongly believe it’ll be a technology company that does that
0:34:31 and then sells that data to others.
0:34:34 Right. So that’s where you believe that CPG companies can compete
0:34:38 and where technology has a place to play by providing that data.
0:34:43 There is a ton of data, and yet people are running blind.
0:34:47 It’s not the data they need.
0:34:52 There’s data around. It’s not helping to make the important decisions
0:34:53 that are moving the needle.
0:34:56 In some cases, it’s not the data that they need.
0:34:58 In other cases, they’re not equipped to digest the data.
0:35:03 And you think of, okay, so at the grocery store, the chocolate buyer,
0:35:07 going back to that example, that’s trying to pick what chocolate bars are on their shelves,
0:35:11 they are used to, for their entire career,
0:35:14 basing it off of either A, their own taste, literally.
0:35:17 That’s how they try product or that’s how they decide products.
0:35:20 Or B, a small amount of retail-level sales,
0:35:23 bought from a very structured data source over and over again.
0:35:25 And that’s not competitive, right?
0:35:26 Because every company has access to that same data.
0:35:28 Every grocery store has access to that same data.
0:35:31 Everyone’s got this commoditized data.
0:35:32 Everyone’s using the exact same thing.
0:35:34 So now when you go to them and you say,
0:35:37 well, actually there’s this whole universe of data out there,
0:35:42 covers 30 to 50 times as many companies as your existing data source does.
0:35:42 Do you want to use it?
0:35:44 The answer is yes, but.
0:35:47 And the but is, well, how do I digest that?
0:35:51 I’m stuck in Excel, Windows 95.
0:35:53 That’s what I’m stuck using here.
0:35:55 How do I digest all of this data?
0:35:56 Who’s going to pull this together for me?
0:35:58 Because by the way, I’ve got literally one engineer
0:36:02 that works at the entire company, entire division that I’m in right now.
0:36:03 How am I going to do this?
0:36:05 That’s why we think it’s an outsource provider.
0:36:08 We think grocery stores and CBG companies
0:36:10 are either going to be buying it from a technology company
0:36:12 or they’ll have to buy that technology company,
0:36:13 bring it in-house.
0:36:16 It makes me think a little bit of automotive and traditional
0:36:19 Detroit car companies trying to become autonomous car companies.
0:36:22 And I think it’s fascinating because they could potentially
0:36:23 win on that front if the right competency is.
0:36:25 There are some really smart people in the grocery business.
0:36:26 Yeah, exactly.
0:36:27 Walmart’s diving in.
0:36:31 They’re also in top line sales right now in stores.
0:36:33 That said, it’s hard.
0:36:36 A lot of the best engineers might want to work for a grocery store
0:36:38 and might not want to live in Bentonville, Arkansas.
0:36:41 And then they’re incredibly low margin businesses.
0:36:44 So how do you hire a ton of really expensive engineers?
0:36:46 I give Walmart credit for making the bet.
0:36:47 They bought jet.
0:36:49 They bought a number of small–
0:36:50 They also have their own labs.
0:36:52 Like Walmart is known to be a little bit more innovative
0:36:54 with internal R&D than some of the other CBG players
0:36:55 that we’re talking about here.
0:36:58 But it’s not that the grocers aren’t capable
0:37:00 and don’t understand it.
0:37:02 They’re a bit of a prisoner’s dilemma.
0:37:05 There are extremely, extremely smart people working at both
0:37:08 large CBG companies and large grocery stores
0:37:10 that are in a really difficult position.
0:37:13 You think about what would you do if you were in their position?
0:37:14 Well, they’re out of business.
0:37:18 That’s, in the case of grocery, 2% net margin business.
0:37:20 How do they then say to their boss,
0:37:23 let’s go hire 150 engineers to go build this thing?
0:37:26 By the way, it’s not going to pay back for two or three years.
0:37:28 That’s a really, really hard proposition to make.
0:37:31 So I think incredibly talented smart people that work there,
0:37:33 it’s a hard position to be in.
0:37:35 One of the smartest people I’ve ever met in business
0:37:39 was the CEO of one of the largest consumer package companies.
0:37:42 And she came to Silicon Valley and wanted to sit down.
0:37:43 And I’m like, why are you here?
0:37:45 We believe software’s eating the world.
0:37:47 How is software eating snacks?
0:37:50 She came up with this very lucid argument of two things.
0:37:53 One is all of a sudden, there’s promotional transparency.
0:37:57 I used to move, gain share by going on special on knob,
0:38:00 Hills food one day and then special at Safeway.
0:38:02 Now the consumer knows exactly where I’m on special.
0:38:04 So I’ve lost the share moving thing,
0:38:08 all I’m doing is discounting and then nutritional transparency.
0:38:11 And so she says, I have to retool my company
0:38:15 because the two bedrocks that it was built on, software eight.
0:38:17 The challenge with that, and I, by the way,
0:38:19 I totally agree with that diagnosis.
0:38:22 The challenge then is that I don’t think that the CEOs
0:38:24 of these large CPG companies or large grocery chains
0:38:26 are given enough runway to go do that.
0:38:28 So there’s this, what we call 3G effect,
0:38:30 large financial institution down in South America
0:38:35 that has been investing into or buying public CPG companies,
0:38:36 basically stripping costs out.
0:38:39 And delivering shareholder value.
0:38:42 Problem with that is when you’re stripping the costs out,
0:38:44 one of the first things to go is R&D.
0:38:46 So you already had a problem for these large CPG companies.
0:38:48 What’s the percentage of R&D that they have?
0:38:51 So today, large CPG spends about 2% of sales in R&D.
0:38:52 Are you kidding?
0:38:55 Tech spends about 14% of sales in R&D.
0:38:57 CPG spends nothing on R&D.
0:39:01 And so- You have low margins, like 1.5 to 2% R&D.
0:39:01 That’s right.
0:39:03 So when you strip out costs,
0:39:06 I can deliver shareholder value and hit quarterly numbers
0:39:08 for the next, let’s say, year or two years.
0:39:10 But you look five, seven years out.
0:39:11 It’s not going to last long-term.
0:39:12 How far can you cut?
0:39:13 It’s like the activist investor problem, right?
0:39:14 That’s exactly right.
0:39:18 And so what we’re seeing is that many of these companies,
0:39:20 regardless of whether they’re doing that cost cutting or not,
0:39:23 they’re saying, look, we were already spending almost nothing on R&D.
0:39:24 How do we get the innovation?
0:39:26 And this goes back to a point Jeff made earlier.
0:39:27 That’s why CPG is beginning to look a lot
0:39:29 like Big Pharma has for the past 20 years.
0:39:31 So one last question then,
0:39:34 just to think about more on the data and innovation side.
0:39:36 All of us in this room are in the world of investing.
0:39:38 How does this change the investing game?
0:39:42 So in terms of how I think the investing landscape will change,
0:39:49 we have a pretty strong thesis that in CPG specifically,
0:39:52 there will be quantitative VC firms.
0:39:54 So what I mean by that is if you think of the public markets,
0:39:58 there are systematic quant funds that have historically,
0:40:00 over the last 20 years or so, in some cases 30 years,
0:40:05 invested into public companies basically just using technology.
0:40:07 It’s very different than a discretionary hedge fund
0:40:09 where you’ve got a team of really smart people
0:40:12 that research a stock for six months and make a decision.
0:40:14 In the case of a systematic quant fund,
0:40:17 they’ve got a lot of really, really smart engineers and data scientists
0:40:18 who are building algorithms to evaluate the company
0:40:20 and then make an investment decision.
0:40:23 We think that that is possible in some industries in the private markets.
0:40:26 We don’t think it’s possible in tech.
0:40:27 Why do you think that’s possible in CPG?
0:40:30 So there’s two main reasons that CPG is beautiful.
0:40:33 First, the business models are basically the same.
0:40:36 So what I mean is if I’m selling shampoo, dog food, or water,
0:40:37 the margins are different,
0:40:39 but I’m making a product and I’m selling the product.
0:40:40 It’s very different than tech.
0:40:42 In tech, I might give away the product for five years.
0:40:43 You might do a freemium, right?
0:40:44 I might do a SaaS business, et cetera.
0:40:45 Very different business models.
0:40:47 Because it’s the same business model,
0:40:49 it’s the same game of chess over and over again.
0:40:50 Interesting.
0:40:54 The second reason that there’s just an outrageous amount of data in this space,
0:40:59 but many of the dimensions that are predictive of success of a consumer company
0:41:01 are not data that you can get externally.
0:41:04 It’s hard to get information from afar.
0:41:05 In consumer, you can get it from afar
0:41:07 without ever talking to the company.
0:41:09 We have gone private financials on thousands of companies.
0:41:11 That acts as our training data.
0:41:13 The training data is private financials on thousands of companies.
0:41:15 And is that kind of providing the ground truth
0:41:16 in order to sort of compare the decisions again?
0:41:17 That’s exactly right.
0:41:18 Yeah, so it’s the ground truth.
0:41:23 So I need to know what success and failure looks like in order to predict it.
0:41:25 If you look at a SaaS company, a consumer company,
0:41:28 and an infrastructure company in tech, you can’t compare them.
0:41:31 Whereas if you’ve got two beverage companies,
0:41:38 and one is selling 20 units per Whole Foods per week at a 60% margin,
0:41:42 another selling 10 units per Whole Food per week at a 30% margin,
0:41:44 it’s pretty obvious which is the better company.
0:41:48 But also in CPG, I can find that company
0:41:50 just by using publicly available information.
0:41:52 So I can see that one of the two companies
0:41:55 started in one Whole Foods six months ago,
0:41:58 and now is in 400 Whole Foods and added 300 targets.
0:42:01 There isn’t really an equivalent in, let’s say, the SaaS world.
0:42:04 Going back to the SaaS world, while there might be structured metrics to look at,
0:42:06 and those metrics might be predictive of success,
0:42:08 almost all of them, not all, but almost all of them,
0:42:10 are only available once you start talking to the company
0:42:11 and you already know who to focus on.
0:42:14 I do wonder because when I watch a show like Billions,
0:42:16 you know, they have, they use data like empty parking lots
0:42:19 and aerial shots of an empty parking lot for retail
0:42:22 to be able to make a decision on whether to pull a trigger on a company or not.
0:42:24 The equivalent in SaaS might be developer heat,
0:42:28 like viral developer activity or the adoption rate among developers.
0:42:30 There’s various heat maps and sources.
0:42:32 The part that I have to ask on the big question
0:42:35 of quant investing in general, and especially in this case,
0:42:37 and even in our world, Jeff, which is more tech than CPG,
0:42:41 doesn’t it miss the outlier, the outsize winners?
0:42:42 It’s a great point.
0:42:43 It’s a great point.
0:42:43 Yeah.
0:42:46 So we, that’s another reason we struggle to believe
0:42:47 that it is possible in tech.
0:42:50 You think about many of the massive home runs in tech.
0:42:51 Exactly.
0:42:55 There weren’t prior examples that did something very similar.
0:42:56 No, they’re all, they’re all a priori.
0:42:57 Right. Yeah.
0:42:59 And so, so that’s why I really struggled to believe
0:43:00 that that’s possible in tech.
0:43:02 When you look at the winners and consumer,
0:43:04 the previous winners looked really similar.
0:43:06 That might have been a different,
0:43:07 might have been a different magnitude,
0:43:08 but they grew in really, really similar ways.
0:43:11 So this might be the one case where that phrase pattern recognition
0:43:13 that people throw around so wildly in the valley actually applies.
0:43:17 But who the winner was, wasn’t that still an irrational
0:43:20 behavioral thing versus something programmable?
0:43:24 So we’ve been able to show that there are some common themes
0:43:29 between both in A, why something wins and how it wins.
0:43:29 So here’s what I mean.
0:43:31 So you’re nuanceifying the two, which is really important.
0:43:31 That’s right.
0:43:36 So why typically the winners have, and look, to be clear,
0:43:37 this is not perfect.
0:43:39 There are holes, there are inaccuracies.
0:43:42 Typically the winners have brand intensity with the consumer.
0:43:44 So think of vitamin water 15 years ago,
0:43:49 kind bar 10 years ago, the brand really resonates with the consumer.
0:43:51 The second thing that is common amongst the winners in CPG
0:43:55 is the product has uniqueness that matters.
0:43:55 Interesting.
0:43:58 So kind bar is actually a pretty good example here.
0:43:59 When it first came out, everyone said,
0:44:00 “This is a really crowded category.”
0:44:03 By the way, everyone always says every CPG category is crowded.
0:44:06 Because they are, because they are, but they’re also massive.
0:44:08 Right, crowded but massive.
0:44:09 I like that distinction.
0:44:12 So kind bar, at the time though, what people missed was,
0:44:15 there’s Nature’s Valley, there’s Cliff Bar, a number of others.
0:44:18 When you look at those products, they didn’t look like real food.
0:44:21 Kind bar had an insight, which was,
0:44:23 “Let’s make a product that actually just looks like real food.”
0:44:24 That’s actually why I’m drawn to them.
0:44:26 I don’t feel like I’m eating a crappy processed bar.
0:44:28 Yep, and they actually show the food.
0:44:30 The biggest innovation for Guy Bar from my perspective is,
0:44:33 it’s see-through and you can see that there’s real food.
0:44:33 So you can see a whole lot to that.
0:44:35 And it’s not symmetrical.
0:44:35 Yeah, that’s exactly right.
0:44:36 Like it’s not this perfect rectangle.
0:44:38 It’s got like jagged edges where you can see it’s real.
0:44:39 It’s not processed.
0:44:41 Exactly, exactly, exactly.
0:44:45 So in that case, you know, you can build an algorithm
0:44:47 which evaluates the picture of the package.
0:44:49 And literally just says, “Is this different?”
0:44:51 So we’ve done that in the case of snack bars.
0:44:52 We track about 3,000 snack bars.
0:44:54 So you answer that question of, “Is it different?”
0:44:54 “Is it different?”
0:44:57 And then, now I could put fish in my snack bar
0:44:57 and it’d be different then,
0:44:59 but it may not resonate with the consumer.
0:44:59 Right, that would be great.
0:45:01 So those are two kind of orthogonal dimensions.
0:45:03 One is does it resonate with the consumer
0:45:05 and is the product unique?
0:45:08 The ones that have one tended to be high in both.
0:45:11 Then there’s the question of how it wins, right?
0:45:13 So why it wins and then how it wins.
0:45:16 The how it wins is typically distribution gains.
0:45:17 Distribution gains.
0:45:18 Meaning–
0:45:20 It’s because it’s not the one of Alex’s famous lines.
0:45:22 Like it’s always about distribution.
0:45:24 Yeah, yeah, it’s, and that is very true in CBG.
0:45:26 So there aren’t a lot of big winners
0:45:28 that have only been sold in five stores.
0:45:30 That’s not a thing.
0:45:31 So then if you think about,
0:45:34 okay, if it’s number of, it’s breadth and quality of doors,
0:45:35 meaning TG Max not as valuable
0:45:37 as let’s say Whole Foods or Costco.
0:45:40 So how do you measure breadth and quality?
0:45:41 That data is out there.
0:45:44 Where the product is being sold is out there in the world.
0:45:45 Whole Foods wants you to know it.
0:45:46 The brand wants you to know it.
0:45:48 Now it’s just aggregating that information
0:45:49 and making sense of it.
0:45:50 But that’s the how it wins.
0:45:52 And you can also get into price points.
0:45:53 You can get into skew count,
0:45:54 number of other things.
0:45:56 But marrying those two things together is the foundation.
0:45:58 But it’s basically one business model.
0:46:00 A couple of the differences in tech.
0:46:02 We’ve been trying to figure out,
0:46:04 how do you leverage data in the decision-making process?
0:46:05 Is this a holy grail?
0:46:09 Yes, we can probably define a dozen, two dozen,
0:46:12 three dozen different worlds of,
0:46:15 you know, universes of tech companies that are unique.
0:46:18 You have SaaS and open source and consumer.
0:46:20 And then within consumer, you have social and e-commerce.
0:46:23 So, you know, just by definition, comparison’s hard.
0:46:26 And then the other part you have is what you said,
0:46:28 most of the huge winners are lightning strikes.
0:46:30 Facebook was the second or third social network.
0:46:32 But, you know, no one was thinking social networks
0:46:35 when they talk about a trillion-dollar company.
0:46:40 eBay was collectibles online, weird, Facebook hot or not.
0:46:44 You know, these things, I mean, the Airbnb sleep on someone’s couch.
0:46:47 You know, these things don’t present as monster companies.
0:46:51 They start, hit a chord and are expanded
0:46:53 by their community of users.
0:46:54 And the thing I would add to that, by the way,
0:46:56 is that there’s a complexity math to this,
0:46:57 which is a little bit like the Brian Arthur,
0:46:59 we had Brian Arthur on the podcast.
0:47:00 And he’s the father of network effects
0:47:02 and network effects theory.
0:47:05 And the point of when that tipping point hits,
0:47:07 you don’t know when it tips.
0:47:07 That’s the hard one.
0:47:08 Yeah, yeah.
0:47:10 Like the when it seems like the really tough question.
0:47:11 Will it.
0:47:12 Then when, yeah, so it’s good.
0:47:14 And if you think of Jeff’s point,
0:47:15 like when Facebook hit,
0:47:17 there was two other social networks and maybe three.
0:47:17 Yeah.
0:47:19 There weren’t 300 or 3000.
0:47:20 Right.
0:47:21 There were very few examples.
0:47:24 You don’t have 40 or 400 examples
0:47:26 to begin to look at pattern recognition.
0:47:26 Right.
0:47:28 The n equals three or the CPG.
0:47:30 You’ve got massive data set.
0:47:33 So now I can compare certainly one ice cream company
0:47:34 to the many others that have hit.
0:47:36 But the difference between ice cream companies
0:47:37 and snack bars is not great enough
0:47:40 that you can’t compare the two and begin to see patterns.
0:47:42 Well, that was a fascinating discussion.
0:47:45 Ryan, Jeff, thank you for joining the ice cream company.
0:47:46 It’s a pleasure.
0:47:46 Thank you.
0:47:47 Thank you.
0:47:57 [BLANK_AUDIO]
with Ryan Caldbeck (@ryan_caldbeck), Jeff Jordan (@jeff_jordan), and Sonal Chokshi (@smc90)
It’s clear that all kinds of commerce companies and consumer products have been disrupted — or enabled — by tech. Yet for certain categories, like consumer packaged goods (CPG), it seems like tech hasn’t changed things very much. How is the rise of so-called ”micro-brands” (or emerging brands) playing out here?
And, how is it possible that ”real” — different — innovation isn’t really happening in the CPG industry, despite the tremendous legacy of brand, talent, and more in the space? How are CPG companies tackling grocery, which represents the perfect end-capsule and case study of challenges — and opportunities — in going from offline to online, from online to offline, and more? As for grocery itself, stores themselves (in the U.S. at least) haven’t changed very much due to tech, either… is it a last-mile delivery thing; could we also possibly move to distribution-only centers in the future?
Finally, while the holy grail of performance marketing and personalization remains elusive for the industry — let’s face it, most brands are still guessing in the dark (and forget trying to customize offerings!) — even going direct-to-consumer (DTC) hasn’t been shining as much of a light here as one might expect. Or so argue the guests in this episode of the a16z Podcast, featuring Ryan Caldbeck of CircleUp, along with a16z general general partner Jeff Jordan, in conversation with Sonal Chokshi. Cuz this episode is all about CPG, DTC; micro-brands, yah you know, all kinds of commerce.