Tag - grubhub

1
Anatomy of a Managed Marketplace
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Why the Micro-VC Surge Will Drive Innovation Across the US
3
Why Amazon Has Consumer Investors Bemused and Confused
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The Economics Underlying Chatbot Mania
5
The Market Has Spoken: Go Horizontal, Not Vertical

Anatomy of a Managed Marketplace

The following article was originally published on Techcrunch on May 25, 2017.

Managed marketplaces (also known as end-to-end or full-stack marketplaces) have been one of the hottest categories of venture investment over the past several years. Recent examples of high-flying managed marketplaces include The RealReal, Opendoor, Beepi, Luxe and thredUP, which have collectively raised nearly a billion dollars. They garner a lot of press because the consumer experiences are often radically different than what’s previously been available in the market.

But there is confusion over what a true “managed” marketplace is. It’s fairly easy to spot a true managed marketplace if you know what you’re looking for. Managed marketplaces typically adhere to the following characteristics:

  • A value-added intermediary (the “management” or “service”) that provides a superior experience versus more traditional peer-to-peer marketplaces, brick and mortar or even a legacy service provider.
  • An introduction of additional risk into the business model; examples might include pre-purchasing and holding inventory or via investing in services related to the buyer/seller that are an incremental, variable cost before any profits have been realized (money goes out before it comes in).
  • A take-rate (gross margin) that is a significant premium versus other buy/sell options in the market in order to offset the premium service level or risk transfer that has occurred.

It’s important to note that many of today’s ubiquitous marketplace companies such as Uber, Airbnb, Grubhub and others are “lightly” managed, by which I mean they invest resources in quality assurance, background checks and verifying reviews. But these services are typically a de minimis expense on the company’s overall operating cost structure — often even considered as part of the customer (or merchant) acquisition cost — and therefore do not classify as a fully managed service.

For Airbnb, these “light” costs might include the costs related to verifying a user’s home address, or the customer service costs of resolving disputes. For Grubhub, the light management might include the costs related to updating menus, but they are not fully managed in that they are not taking ownership of the food or food prep themselves (although Grubhub has begun rolling out delivery, which would qualify as a managed service). This infographic shows the primary marketplace categorizations:

In order to build a successful, sustainable managed marketplace, the take-rate margins must be high enough to support that value-added intermediary and the subsequent amount of services and risk the marketplace is providing. What makes these marketplaces so powerful is that they can drop a comparable amount of contribution margin to the bottom line while investing the higher take-rate revenues into customer experience, reducing friction and product improvements.

Additionally, if, over time, these marketplaces can develop technology that significantly reduces or eliminates the costs of providing these value-added managed services, they can continue to justify higher take-rates and build high-margin businesses that are worth a premium to their traditional service provider comparables or peer-to-peer businesses.

As a primer, here’s a quick chart of take-rates in the re-commerce industry amongst both managed marketplaces and traditional marketplaces. Can you guess which ones are actively managed?

Value innovation and risk

Now that we’ve identified that managed marketplaces are effectively business model innovations, it’s useful to go through a few on a case by case basis to identify each of these innovations and be able to properly identify managed marketplaces in the future.

Opendoor is a managed marketplace in the real estate industry that is an on-demand tool for selling your home. They utilize numerous data sources to offer real-time bids on a home, typically without ever stepping foot in it. Basically: Click a mouse, sell a house. They charge the typical 6 percent brokerage commission plus a risk-adjusted service fee (about 2-3 percent extra, on average, up to 6 percent).

Value-Add Innovation: A consumer no longer has to wait to sell their home. They don’t even so much as have to engage a real estate brokerage. Opendoor reduces the friction of selling a house from possibly months (and multiple showings) down to minutes. The company will also perform all maintenance/changes demanded by a licensed inspector.

Risk Innovation: Unlike brokerages such as RE/MAX or Century 21, which take zero capital risk on a transaction but collect 3 percent from each of the buy/sell sides of a transaction, Opendoor is buying inventory and holding it on their books. The effect of this is that they can offer an extraordinarily differentiated experience to their home sellers, who traditionally rely on peer-to-peer markets (typical MLS listings, with a realtor advising).

Take-Rate: To justify this level of risk (holding inventory) and service (managing maintenance), Opendoor charges a take-rate on average 50 percent higher than in a traditional real estate transaction. While a 50 percent premium may seem marginal given the delta in other categories, the large transaction sizes in real estate mean that the take-rate premium on a $500,000 house is $15,000 of incremental gross margin. That is a significant amount of money to manage maintenance and some risk.

Case in point is the below estimation of Opendoor’s revenue and cost structure on an average $220,000 home (their sweet spot) with a 9 percent brokerage fee, a 50 percent premium to market rates:

Source: Inside Opendoor: What 2 Years of Transactions Tell Us

For Opendoor, when all is said and done, their average net profit, $8,320, or 3.8 percent of the home’s original selling price, is still greater than the 3 percent an agent at a traditional brokerage earns. And, they are able to provide a substantially differentiated experience. It’s a powerful model.

TheRealReal is a managed marketplace in the luxury consignment space focused on clothing, jewelry, handbags, even art. The experience differs from eBay, for example, in that sellers need to provide zero effort other than sending their goods to a TRR warehouse (no photography, no descriptions, no customer interaction) and buyers take comfort in TheRealReal’s quality and authentication services, which they fully guarantee.

Value-Add Innovation: Rather than having to post online listings and photographs of items, pay for a third-party authentication or even deal with shipping, TheRealReal simply collects an item from a consignor and sends them a check once it sells. For sellers, it’s a true “set it and forget it” experience and is multiples more convenient than dealing with online auctions (or even price comparing between local thrift shops).

Risk Innovation: In order to provide a frictionless experience for the seller and an aesthetic, trusted experience for the buyer, TheRealReal is forced to frontload all those costs into their own overhead. They expense per-item charges for photography, copy writing and logistics before an item sells. If the item fails to sell, TheRealReal is forced to eat those overhead costs. Therefore, if they inaccurately forecast demand for certain items, they could end up burning more money than they’re able to recoup on sales.

Take-Rate: In order to justify its cost structure, TheRealReal (and other comparable marketplaces) command take-rates of 30 percent, effectively triple what non-managed, peer-to-peer marketplaces charge as a commission to sellers.

Luxe is a managed marketplace for drivers that reduces all friction associated with parking: finding a lot, searching for a spot, returning to the lot, paying the cashier and waiting to exit. Operating as an effective always-on, mobile valet service, drivers are met at their destination by a Luxe agent who takes the keys and parks a driver’s car. Upon leaving, the driver requests their car in-app and are met by a Luxe agent who delivers their car at their exit point.

Value-Add Innovation: Luxe fundamentally reimagines parking by providing any driver with an on-demand valet who will meet them across a large radius of major cities. Unlike traditional parking or even mobile parking marketplaces such as SpotHero* (which require a driver to park their own cars), Luxe reimagines driving to be destination-focused: drive to your ultimate end-point, not a parking lot. In theory, its product could save drivers time and enable them to avoid inclement weather.

Risk Innovation: In order to provide uninterrupted, on-demand service, Luxe is forced to employ numerous valets across each geography in which it operates. Irrespective of what these valets are actually paid, it is a considerable human capital cost that Luxe is forced to bear ahead of any realized demand. This is in contradistinction to a sharing economy marketplace model such as Airbnb or Uber who are not burdened with human capital costs, but rather pay transactional commissions on any given home-owner or driver.

Take-Rate: In order to counter-act the considerable human capital expense of staffing valets across a city, Luxe should be forced to charge a material premium compared to average hourly parking rates in a particular city. It is therefore quite surprising that they advertise an average of $5/hour for their service, especially when the average hourly rate in NYC, for instance, is $11-15/hour. Several months ago, reports from San Francisco suggested that prior rates of $5/hour have now increased to $15/hour or a $45 daily maximum and, as of this month, they have suspended the valet service. Given the considerable variance in parking costs by neighborhood, it is hard to assess their exact take-rate premium, but I’d estimate it would have had to have been about 200 percent of traditional parking take-rates to be profitable.

Each of these companies is built on the vision that technology will ultimately be able to deliver increased automation and better margins. For example, that one day TheRealReal’s item authentication will be entirely algorithmic or that Luxe will be able to predict the real-time flow of drivers, thereby reducing its human capital costs. Because these representative companies are all still relatively young startups, those tech-driven narratives have mostly only begun to play out.

Beepi versus Carmax

Beepi, a managed marketplace for used cars, recently closed its doors after burning through nearly $300 million in the span of two years. Unlike eBay Motors, which is a peer-to-peer experience, offering no concierge services (although it does offer some self-service options such as free Carfax reports), Beepi was a full-service platform promising rigorous inspections on cars, a 10-day no-questions return policy for a purchased car and, for sellers, a promise that if one’s car didn’t sell in 30 days, Beepi would buy it outright for the appraised value.

The seller fees for this risk-free service? Approximately 9 percent with Beepi… versus a $125 fee for eBay motors, or about 1.25 percent on a $10,000 car, nearly an 800 percent differential.

So with a premium 9 percent take-rate, how did Beepi fail?

The best insight into their failure may come from a similar model with considerable success. It turns out that the nation’s largest retailer of used cars is also arguably one of the most recognized managed marketplaces in the world: Carmax. Give Carmax 30 minutes to inspect your car and they will buy it, even if you’re not purchasing one of theirs, with a “no-haggle,” take it or leave it offer. Thirty minutes is pretty efficient, pretty darn close to on demand.

The extraordinary thing about Carmax is that the Company’s gross profit per used car sold basically doesn’t change even when the year’s average price per car sold moves up or down by 5 percent in any given year. Which means that Carmax is actually less focused on their take-rate per car, but instead focused on their profit per car; their commission is a function of the profit they expect to earn.

Rationally, this makes sense as well — consumers value convenience but have a cognitive dollar limit they are willing to trade for that convenience. By inverting their take-rate to be a function of their profit expectations, Carmax is able to offer more for higher-end cars where a 10 percent difference between the car’s BlueBook value and Carmax’s offer would likely be too extreme for a customer to accept. For high-priced assets, a flat tax is fundamentally unlikely to work.

Used cars are curious assets in that they depreciate so quickly that even 60 days can have a demonstrable impact on value. This is where Carmax excels. In their most recent annual reporting, Carmax notes having sold more than 600,000 cars in the prior year with (then) present inventories at about 55,000. That’s a retail turn of about 11, meaning that a car moves off Carmax’s lot every 35 days or so, allowing them to more accurately price cars andmake higher offers, being less exposed to the less predictable volatility of depreciation.

In a post-mortem on Beepi, Carlypso founder Chris Coleman suggests that in addition to the noted reasons (depreciation effects, and cognitive pricing differential), the approach was inherently flawed from a customer acquisition perspective. Specifically, that while there are customers looking to simply sell their car for cash, most car owners are looking to trade-in a car, because they still need a car and there are tax benefits to doing so; a platform that has to pay marketing costs for both the buyer and seller in all transactions is at a significant disadvantage.

At the end of the day, a managed marketplace model for used cars does work. Carmax is only one of thousands of proof points: tens of thousands of dealerships across the country hold inventory, inspect cars and reap a profit. Beepi’s failings appear to be the result of poor execution, mispricings and maybe even some bad luck around a financing that fell through.

Automation and Shutterstock

Because managed marketplaces involve a heavy “service” component to improve the overall experience, one of the expectations of the sector is that as artificial intelligence and automation continue to evolve, the human capital cost of providing the service will decrease if software can assume more of those responsibilities.

But an area of struggle with managed marketplaces is that very few digital managed marketplaces are actually public companies, reducing the visibility into their overall economics and processes — and making it hard to test the assumption that service costs should come down over time. Luckily, there’s at least one: Shutterstock (NYSE: SSTK), a marketplace for photographers to sell their images, bills itself as a “trusted, actively managed marketplace,” in that “each image is individually examined by [their] team of trained reviewers.”

On the spectrum of managed marketplaces, Shutterstock is undoubtedly on the lighter end — with the financial risk from its active management being only the human capital cost of its QA reviewers. Nevertheless, it would seem like this hypothesis is an ideal one to test on a company such as Shutterstock, which isn’t dependent on an unproven technology such as self-driving cars to reduce their cost of providing a service, but could presumably leverage proven, inexpensive image recognition technologies to do much of the quality assurance, copyright detection and tagging that the human reviewers do.

Yet, that doesn’t appear to be borne out by Shutterstock’s financials. To test the automation hypothesis, I decided to look at the company’s revenue versus the cost to generate that revenue. Shutterstock defines their costs of revenue as “royalties paid to contributors, credit card processing fees, content review costs, customer service expenses, infrastructure and hosting costs…and associated employee compensation.” I would assume that credit card processing fees as a percentage of revenue are relatively flat (if not slightly reduced year over year) and that cloud-hosting fees also scale mostly proportionately to demand (revenue). I’ve defined “True COGS” below as the aforementioned expenses to providing their service, minus the contributor royalties:

Surprisingly, rather than decreasing over time, these True COG costs appear to be increasing. Meaning that the same picture that used to take 10.5 percent of revenues to process now costs nearly 15 percent.

There are a number of possible explanations here. It’s certainly possible that these increased costs are because the company is investing heavily into automation, the effects of which simply haven’t been borne out yet while they streamline their QA process. It’s also possible that the number of photos the company maintains makes it more expensive to process each incremental picture — for any variety of reasons.

The learning from this Shutterstock case study, a company which is now 14 years old, is that it’s improper to simply assume that the substantial service-related costs that managed marketplaces incur in their early stages will decrease with “scale,” either through execution or software automation. As with any company, there is always room for improvement, but the above analysis of Shutterstock would imply that it’s nowhere near as easy as flipping a switch.

Takeaways

Managed marketplaces are a quintessential venture investment, allowing entrepreneurs to recast consumer experiences while leveraging venture capital subsidies to hold much of the risk inherent in these managed models.

From a unit economic perspective, the potential automation of much of the service labor that goes into these platforms could be significant. Investors and operators need to remain sensitive that it is ultimately the technology, not heavy services, that will long-term cultivate highly desired business models and margins. But, that future automation could also lower the barriers and defensibility of these companies, allowing peer-to-peer players to launch a comparable offering with similar software.

In my mind, the sustaining managed marketplaces will not only re-imagine the experience they’re approaching, but be focused from the outset on building a data moat around their product, thereby ensuring that they remain the platform of choice, even if software innovation begins to level the overall playing field.

Special thanks to Josh Breinlinger and Rebecca Kaden for their feedback on this article.

*Chicago Ventures is an investor in SpotHero.

Why the Micro-VC Surge Will Drive Innovation Across the US

The following was co-authored by Ezra Galston of Chicago Ventures(@ezramogee) and Samir Kaji (@samirkaji) of First Republic Bank.

Over the last several years much has been made of the opportunity, or perceived lack thereof in technology centers outside of the Bay Area and NYC. From Steve Case’s Rise of The Rest Tour, to Google for Entrepreneurs, to Brad Feld’s Building an Entrepreneurial Ecosystem , the discussion has consistently been overwhelmingly positive.

It’s easy to understand the stance as who wouldn’t want to support entrepreneurship, irrespective of geography? However, it’s hard to discern whether these opinions were borne out of a utopian desire or a sincere belief of true financial viability in markets outside of NYC and the Bay Area.

In Fred Wilson’s widely discussed (and debated) piece “Second and Third Tier Markets and Beyond,” he suggested that the opportunity outside of the Bay Area was significant, citing the successes of USV in New York, Upfront Ventures in LA and Foundry Group in Boulder:

“The truth is you can build a startup in almost any city in the US today. But it is harder. Harder to build the team. Harder to get customers. Harder to get attention. And harder to raise capital. Which is a huge opportunity for VCs who are willing to get on planes or cars and get to these places.

There is a supremacism that exists in the first and second tiers of the startup world. I find it annoying and always have. So waking up in a place like Nashville feels really good to me. It is a reminder that entrepreneurs exist everywhere and that is a wonderful thing.”

In an effort to move past anecdotes however, we wanted to explore one of the components that helps drive and catalyze early entrepreneurial activity in any localized geography — the availability of early stage funding.

Simply put, non-core US tech hubs are reliant on local early stage capital to subsist since seed stage fund sizes often make remote investing impractical (by contrast growth stage investors who manage large funds and have significant resources can easily invest in breakout companies outside their region).

With the hypothesis that quality local seed capital is needed to foster a strong entrepreneurial ecosystem, our analysis is centered on whether the MicroVC surge, has provided (or may provide) a material impact to these “2nd and 3rd” tier US geographies.

Fortunately, there’s good news for entrepreneurs everywhere. Of all of the Micro-VC funds raised since 2010 (this number includes firms currently raising funds), over 40% of Micro-VC’s formed were based outside of the country’s largest tech centers of SF, LA, NYC and Boston, a number we found quite surprising.

In total, those Micro-VC funds raised outside of the four core tech centers since 2010 represent $6.7B in investable capital, the vast majority of which have driven significant investment dollars in their geographies.

More important to note is that the opportunity in these secondary ecosystems is unequivocally noteworthy. Using M&A activity as an evaluation metric, these ecosystems, despite a relative dearth of funding, have performed quite well:

In each year dating back to 2010, the percentage of Micro-VC funds raised outside of SF, LA, NYC and Boston materially lags the volume of M&A activity, on % basis, in those same areas. This suggest that Micro-VC funds located in secondary markets face less competition — and proportionally more opportunity — for strong financial outcomes by betting on that delta. Now, it’s true that these opportunities are a bit geographically dispersed, however it’s clear that certain cities (Seattle, Boulder, Austin, Salt Lake, Chicago) have made great strides in developing great entrepreneurial talent.

This dislocation in M&A proportionality is of course amplified by the concentration of funds in the Bay Area and NYC. Because coastal deals are more competitive due to an oversupply of capital, they boast higher entry prices (valuations) than do deals in secondary or third tier markets — and the effect on a returns basis may also be material. Case in point: according to Angelist, the mean valuation for deals in Silicon Valley since 2010 is $5.1M. That compares to $4.5M in Chicago, $4M in Indianapolis, and $3.7M in Detroit — offering Midwest investors anywhere from a 10–30% discount at entry.

There are other ways of interpreting the data. One could argue that Bay Area deals deserve to be higher priced due to a premium in the quality of founding teams. Or that the pure volume of M&A in the Bay Area and Boston de-risk the level of returns variance for any particular fund. Those arguments may be with merit but are also balanced by data released by Pitchbook that show cities such as Chicago, Seattle and Washington D.C effectively comparable on a multiple of returns basis:

It is nearly indisputable that large technology companies are being built and enormous value is being created outside of the coastal venture markets: examples include Grubhub, Groupon, Domo, Qualtrics, ExactTarget and HomeAway. But these markets will require more patience for company maturity, a willingness by fund Limited Partners to accept greater short-term volatility, and conviction that key talent will stay in non-core markets due to a desire of staying local and the avoidance of the high cost of living present in the major US tech centers.

While the rhetoric around non-core markets has been historically positive, it appears that the early stage capital surge through Micro-VC funds may be a major factor in these areas actualizing on their potential.

Extra special thanks to Peter Christman for his tireless work in helping to analyze, aggregate and process the data underlying this article.

Why Amazon Has Consumer Investors Bemused and Confused

Amazon’s recent entries into home servicesfood deliveryprivate label clothes & shoes, as well as a wide range of private label home items represent its most brazen efforts ever to attack the entire retail stack as well as penetrate seemingly defensible network effect businesses.

Over the past couple of years, Chicago Ventures has made a number of investments in service-enabled (concierge) commerce businesses believing that their service layer provides a real defensibility against Amazon’s low (no) margin approach. Writing in TechCrunch this past December in “The Middleman Strikes Back,” I noted then:

“If you sell practically any physical good online, Amazon, the Internet’s most powerful retailer, is a perpetual threat. With their distribution, leverage and logistics expertise, they have the wherewithal to undercut on price, and process and deliver products faster than practically any startup — not to mention, they can operate at a loss if necessary.

So where is Amazon exposed? On a services level.

Amazon’s operating margins — already tight at 1.3 percent — don’t allow for much room to train and mobilize a large human concierge force. Which means that building a human-focused, relationship-driven personalization platform actually provides for a tangible differentiator against Amazon — one of the few ways to effectively compete against the giant (and, perhaps more importantly, one of the few ways to build defensibility in a commerce segment traditionally dependent on “brand” as its only de facto moat).

One further point: Amazon is predominantly a destination for directed search – either on a specific product or specific category basis. But as purchasing increasingly shifts to mobile, it turns out that it continues to be difficult to search, discover and catalogue individual items. Concierges – especially when leveraged via a mobile interaction point – reduce that friction and enable a new purchasing behavior.”

But outside of these concierge commerce businesses – which by the very nature of their human capital costs will inherently be lower margin businesses[1] – are there still opportunities to build consumer businesses in a world increasingly dominated (or potentially undercut) by Amazon?

At an event today in Chicago, Amazon employees from nearby fulfillment centers packed 2,000 care packages to send to soldiers abroad who are not able to come home for the holidays Friday, December 4, 2015. Since 2010, Amazon has shipped more than 12 million packages to APO and FPO addresses. The Amazon care packages for the troops included holiday chocolates and snacks alongside an Amazon Fire tablet. The care packages for soldiers headed off in an Amazon branded trailer—one of thousands that Amazon has started to roll-out to increase capacity in the supply chain. Amazon’s Vice President of North America Operations Mike Roth said, “I couldn’t be more pleased that our very first Amazon trailer headed out on the road carrying such special packages—thousands of boxes filled with beloved holiday items and Amazon Fire devices to support troops abroad this holiday season.  (Photo by Peter Wynn Thompson/AP Images for Amazon)

Although many investors and operators I’ve asked privately have expressed mostly bemusement or skepticism about Amazon’s recent efforts, I’ll admit that Amazon has me perpetually on edge.

On Brand Authenticity

On a recent swing through the West Coast I asked several experienced e-commerce entrepreneurs (generated hundreds of millions in annual revenue, raised hundreds of millions of dollars from bulge bracket VC firms) the Amazon question.

The responses were similar: that it is fundamentally unlikely for Amazon to win a branding war in many product categories. For example, one founder noted, Proctor & Gamble or Johnson & Johnson, both of whom are seeing many of their product categories be unbundled by startups, lack the credibility to build authentic new brands in today’s social and content based environments.

How can a corporation claim to represent certain values as underpinning its products when its entire history of operations has been largely antithetical to those same values? Consumers, he argued, are simply too well informed now to be tricked by that ruse.

That strikes me as true – in certain categories. Here’s my view on how many product categories break down from a consumer’s perspective on importance. For context, I believe that purchasing decisions primarily hinge on four variables: Recall Impact is the speed at which a name brand is immediately recognized by a consumer, Authenticity Impact is the natural fit between company (or founders) and its product and messaging, while Review Impact refers to the import of 3rd party or peer-to-peer product reviews.

AmazonConfused4

The takeaway is that authenticity matters – but not always. Bargain shoppers are focused less on company values and story and a lot more on trusted brands who will provide a consistent quality of product at a low price point. Whereas mid-tier buyers care a lot less about traditional household brand names and base far more of their purchasing on crowd sourced information and reviews. This trend is more eloquently described by Itamar Simonson, a Professor at Stanford GSB who argues that we’ve reached “the decline of consumer irrationality,” that is, a large segment of consumers are less malleable to high level branding than in the past.

Amazon’s platform allows it to potentially excel within reviews, recall and price. Reviews, because it has habituated its customers to checking peer reviews before purchasing (and if its products warrant positive reviews, consumers will take note), and Recall, because the Amazon name is effectively ubiquitous with quality and convenience.

What this means is that Amazon has a very credible case to steal market share from bargain brands and mid-tier brands, but will face resistance as it moves into categories where authenticity matters a lot or if its product is subpar, irrespective of price. This is likely why its AmazonBasics line has fared well (low cost, commodity products, mostly electronics), whereas its initial line of diapers was pulled from the market. I am personally suspect that its forthcoming “Mama Bear” line of baby products and organics will be successful

On Irrationality and Execution

As an investor, my job is to pick and help businesses that I believe can execute on models that are defensible and sustainable. But Amazon has shown an unwillingness to accept any network effect as impenetrable and a preference for building, rather than acquiring.

That said, the questions I wanted to unpack are: (a) Is Amazon likely to out-execute a focused, fast growing startup and (b) Are they rational?

Let’s start with (b) – are they rational? I asked a respected consultant to the Fortune500 on strategy and corporate development with deep experience in retail. His thoughts:

“Amazon has always had a very unusual way to do strategy, breaking many of our rules.  But along the way, they have also proved that it is a very bad idea to do that.  How do I know that?  Look at the profit margin per sales dollar, the profit margin per employee, and simply the lack of net profit over the many years.  They are masters at “trading dollars” rather than making money.  Until very recently, profits have been essentially zero.  Never before in history has a major retailer grown without making buckets of money all along the way.

Along the way, to provide the appearance of dynamic growth, they have aggressively been crashing into markets and selling things at or below their real cost (including all true costs of operations).  How do I know that?  They make no money in the end, and that shows me their true costs, which they work very hard to hide in the individual business sectors.

Amazon does appear to act irrationally, and it is only the superior irrationality of the stock market that allows them to have the capital to do that.  Can the profit from AWS actually support the entire enterprise?  I have no idea.  But I would not want to compete with Amazon in any product space.”

Irrespective of whether one is an Amazon bull or bear (and I think it’s important to learn Chamath Palihapitiya’s take on the bull case) it does appear that their actions in any given business unit are highly experimental, to the point of appearing irrational (though employees will tell you Amazon is extraordinarily data driven). As an operating business, they are either fools or geniuses – both of which are reasonable perspectives – but many of their business launches do appear irrational. For example, Handmade, a direct Etsy competitor announced more than a year ago, has yet to launch and seems an odd market to attack given that Etsy’s market cap at $1.1B, or 33bps of Amazon’s, is downright immaterial.

The second question worth exploring is whether Amazon is likely to out-execute a more nimble startup. Amazon’s past is riddled with failures such as the Fire phone, Amazon Local (its investment in Living Social was also unsuccessful), and others. Whereas its successes, led by Amazon Web Services, Prime, and Echo are undeniably game changing. The reality, like most of life is likely grey – that Amazon’s outliers are outnumbered by its hundreds of somewhat successful experiments

Insights From Public Markets

To date, Amazon’s aggressive low cost pricing and capex-intensive logistic arsenal has most visibly punished traditional brick & mortar retailers. Sears, Macy’s, Nordstrom, Williams-Sonoma, Kohl’s and others have all lagged the S&P 500, often precipitously, for more than five years. In the following two graphs, the S&P 500 is the blue line.

AmazonConfused6

AmazonConfused5

But there’s one glaring exception (in the second graph). Off-price retailers, led by TJ Maxx & Ross Stores have surged, doubling the return of the S&P500 over the same period, and trading at multiples double to triple those of traditional retailers:

AmazonConfused7

In fact, the three brick & mortar retailers with the highest multiples: TJ Maxx, Ross Stores and Michael’s share one unique characteristic: they have effectively zero e-commerce. In fact, the retailer with the next highest multiple is Costco – who do not rank in SEO and whose e-commerce gated and exclusive to annual members.

So what’s the logic? Has Wall Street simply lost its mind & just hates online shoppers?

No. Each of the retailers in the high multiple bucket shares a commonality: a perception of being Amazon-proof. Off-price retailers have a particularly complex business model: frequently changing merchandise, material inventory differences on a store-by-store and geographic basis [3], and opaque relationships with the brands themselves. Those are complexities that are difficult to productize online because of the fast changing nature of the inventory – and for the time being the street assigns a premium to that non-commoditized revenue. [4]

The same is true of both Costco and Michaels. Costco, historically, has enjoyed a structural moat against other retailers because of its membership club and unique approach to high volume/bulk items. That, of course, may be changing – sales were flat for the first time in six years in the last quarter – and it’s possible that slowdown is related to Amazon’s Subscribe & Save. Michael’s stores, the behemoth craft superstore also trades at a material premium to most retailers, presumably because of a combination of (a) its custom framing business, a major revenue driver, has been reluctant to transition online and (b) over 50% of the store’s product revenue comes from private label brands, insulating itself from selling purely commoditized supplies.

High level – these are the insights investors and entrepreneurs should be focusing on when innovating in direct to consumer businesses. With an effectively infinite war-chest and a fearless leader, Amazon’s willingness to compete, even with mid-cap companies such as Etsy and Grubhub is unprecedented and its potential impact, significant. Those insights suggest a focus on building deeply authentic products, innovating in product mixes that are not naturally leveraged by Amazon’s existing logistics, and/or focusing on defensible transactional network effects businesses[5] – while avoiding mid-tier, commoditized product tiers or businesses that compete on logistics.

[1] There may be exceptions. There’s a reason Stitchfix has been investing heavily in data science, reportedly employing 60 FT data scientists. Data, even if only partially automated, is they key to reducing these concierge related overhead costs.[2]

[2] The paradoxical element of it all is that if a concierge commerce business (such as Stitchfix) becomes a purely data/AI personalized retailer, then they have unknowingly just played into some of Amazon’s greatest strengths: data leveraged personalization. It would seem there is a balance to be struck in this cycle.

[3] As an aside, one of the amusing nuances of the off-price retailers is that because of their changing inventory, and store-to-store inventory differences, each visit provides a sense of surprise and often delight – that same “surprise” many of the e-commerce based curators have tried to recreate online with mixed success. Turns out you could’ve just walked into an off-price store all this time!

[4] This is also why I am personally intrigued by the online consignment players. TheRealReal for example has enormous operational complexity because of the one off nature of its inventory – and forced to streamline processing costs (photography, content, authenticity verification, tagging) to the point of being profitable even on $100 items. Our investment in Luxury Garage Sale takes this complexity even further: moving thousands of truly unique SKUs across the country to its different retail stores, and even further re-leveraging the consigned items by putting them in try on at home and return boxes, called Luxbox

[5] Grubhub’s network effects, though strong from a technical perspective, are arguably weaker as consumer behavior shifts towards expecting a holistic delivery experience. This is because the company at present does not fully control that experience. Amazon, by virtue of its logistical prowess, can begin to recast the network in its favor, especially if it is willing to undercut on price and subsidize the costs of speed. Whether that is cost effective for them is irrelevant – Amazon is not concerned with short term profits.

 

The Economics Underlying Chatbot Mania

Over the last several weeks, we’ve reached peak AI/Bot mania. Most of the conversation has centered around Chatbots and the potential emergence of a new platform/distribution layer. If you’ve been mostly ignoring the press, some good reads are:

Tl;dr – the major takeaways are as follows: given that consumers don’t really download apps anymore, brands & retailers have a new access point to end consumers, sitting on top of existing messaging platforms and leveraging chatbots to ensure mass scale. The truth is that the chatbot platform conversation is really just an extension of the one we had about a year ago during the emergence of Magic/Operator and SMS as the new platform, which we discussed in Are We Already Rebundling Mobile. An important extension given that such bots have been democratized and can now be spun up not just by tech companies, but by traditional retailers (on their own or within Messenger) or even by individuals such as you and me.

screen-shot-2016-03-24-at-09-50-46

All @TayTweets joking aside, the more intriguing aspect this time around is that Artifical Intelligence and Machine Learning have improved by leaps and bounds. A few articles that reflect this point are: Why AlphaGo Is Really Such a Big Deal, The Current State of Machine Intelligence, Can Machine Learning Predict a Hit or Miss on Estimated Earnings, and The Humans Hiding Behind the Chatbots

But again, the vast vast majority of analysis has focused on bots living within the worlds we frequent (messaging & SMS) and the platform implications. SO – I wanted to spend a few paragraphs to quantify and explore the effects of these advancements from a unit economic or business perspective. The big ones are twofold in my mind: (1) Properly executed AI can transform certain human capital marketplaces from operating as take-rate businesses and transition them into high gross margin software businesses. (2) Chatbots in their current function as customer service agents can make a material impact on contribution margin & overall EBITDA if they can successfully remove the customer service expense line.

20% Take Rate —-> 90% Gross Margins?!?!?

First, some context. About four months ago, writing in “The Middleman Strikes Back” I suggested:

“It’s clear why a hybrid AI/machine learning model is the holy grail for several verticals – replicating [a high] level of personalized service while minimizing overhead labor costs and maintaining extraordinary software level gross margins.”

But in fact, I was wrong. Dennis Mortenson, founder of X.ai in “The Humans Behind the Chatbots” believes that the hybrid in “hybrid AI /ML” should be minimized even further…to zero:

“The two scheduling e-mail bot companies have divergent plans for expansion. Clara, which is slowly letting people off its waitlist and said it currently serves hundreds of companies, charges $199 per month per user. X.ai, on the other hand, plans to move from limited beta to a public release later this year and wants to charge about $9 per month. Dennis Mortensen, its founder, wrote in an e-mail that “only a machine-powered agent can take on the 10 billion formal meetings that U.S. knowledge workers schedule every year.” Mortensen said the service will start asking e-mail senders to clarify when the computer can’t interpret an message—“Did you mean Monday, April 4?”—instead of having an employee read it and infer. “We want to give the job away for free, or for $9, which you can only do if it’s software,” he said.”

Executing on Dennis’ vision, by removing human labor in the middle, you have effectively transformed a take-rate marketplace into a high margin software business, while managing to provide a similar product. Here are examples of some of the service/agent businesses* that could see their economics transform towards 80-90% gross margins when fully leveraging AI:

The Unit Economics Underpinning the AI

Additionally, the company’s variable costs (ie the cost to provide each incremental production or engagement) will transition from significant (paying humans) to immaterial (software cloud hosting fees) enabling a much lower cost of servicing demand, should these companies choose to lower prices. Doing so could expand the audience for such products tremendously.

While I was initially a big skeptic of X.ai, the combination of a product that increasingly works with minimal human intervention and a product priced to undercut the market tremendously at $9/mo is a proof that this transition from human marketplace to pure software is already underway.

Further, there’s even an even bigger opportunity in play. If Matt Turck’s suggested “data network effects” take hold many of these service marketplaces – few of which are operating in actual winner take all markets – could be replaced by a software layer, leveraging data network effects so strong that those markets actually become winner take all.

$$$ Massive Value Creation in Public Markets

Again, this is mostly a theoretical exercise, but let’s imagine for a moment the value creation consequences of fully automated chatbots successfully managing 100% of a company’s customer service interactions.

Here are a handful of examples of some companies you might be familiar with showing their current enterprise value, approximately how much they spend on human capital customer service and the effective sensitivity in their valuation if they could maintain their current level of customer service via no-cost** chatbots:

The Unit Economics Underpinning the AI2

It’s not clear to me this is the optimal way to assess the economic value of chatbots – I kind of doubt anyone knows yet – but what is clear is that the effect to profitability would be tremendous. Massive. And that’s just by automating customer support alone.

Importantly, and intentionally, this exercise ignores the real, global cost of losing so many service level jobs from the economy. I’m not qualified to assess that cost nor its effect. There are many opinions in the market for what an AI economy might look like; Roy Bahat at Bloomberg Beta recently offered an intriguing one to The Twenty Minute VC – a futuristic marketplace actually placing a premium on any human manufactured products or human assisted services because of its rarity. There are others as well. Much discussion around AI is conjecture, but its economic effects are a very serious business.

* Certain of these companies do not publicize take-rate or offer non take-rate subscription models. In these cases, gross margins have been assessed from public interviews, or estimated based on reported hourly worker wages and expected throughput.

** This assumption is implausible as there would still be some associated costs related to the software itself and managing/customizing the software on a daily basis.

Special thanks to Dan Abelon for his feedback on this piece.

The Market Has Spoken: Go Horizontal, Not Vertical

When I entered the venture world in 2012 and started learning the ropes, one of the lessons that was repeated heavily was the importance of vertical specificity. Namely that consumers were becoming more demanding, expected lower friction and better workflows, and vertical focus was the only way to service these behavioral shifts.

From Andreessen-Horowitz partner Jeff Jordan’s seminal post at the time, “People Marketplaces”:

While many of the horizontal platforms are doing interesting things, we tend to think that the vertical approach is resonating more with consumers.  Most of the companies that are showing early signs of breaking out tend to target one vertical.  Our hypothesis is that the horizontal plays may suffer from a potential “paradox of choice”: Consumers could be getting overwhelmed by the seemingly infinite array of potential service options presented by horizontal platforms, but consumers can easily understand the highly specialized value proposition of a company offering services in one vertical.  When you use the Lyft app, for example, it’s immediately obvious that you can get a ride from where you are to where you want to be.

My partner Chris Dixon points out that vertical approaches have additional advantages.  From a product perspective, the vertical apps can tailor their workflow to the unique characteristics of that vertical—the best way to find someone to clean your house is different than the best way to find a ride.  And from a marketing perspective, a narrow focus on one vertical lets the company do things to potentially accelerate each side of the two-sided marketplace.

But sometime in 2014 or 2015, that started to change. Jeff Jordan, writing nearly 30 months later, about his investment in OfferUp, an unequivocally horizontal platform noted:

Yet one of the categories that has been resistant to disruption has been the “for sale” verticals — everything from bikes, boats, cars & trucks, computers, furniture, garage sale, motorcycles, musical instruments, RVs, camping equipment, baby clothes, cribs, sporting equipment, and so on. We believe OfferUp has the potential to truly be a category killer — in the existing category of buying and selling goods between people locally — by providing a trustworthy and easy mobile-first experience.

Let’s get real: “for sale” isn’t a vertical – unless eBay is a vertical. No – used kids clothes are a vertical. Furniture is a vertical (a big one). Electronics are a vertical. “For sale” is horizontal.

But it’s not just OfferUp. The once discussed opportunity for the unbundling of Reddit to build deeply vertical specific, transactional communities – well, that’s started to push horizontal and get rolled up too. Take Massdrop for example, the hyper fast growing digital transactional community, that initially focused on headphones, but now covers over a dozen topics – from its Series B announcement:

The company focuses on what it calls “community-driven commerce.” It allows people who are interested in things like high-quality audio, men’s fashion and quilting (yes, those are all actual Massdrop communities) to connect with other enthusiasts, discuss products, make purchases with group discounts and even help design new products.

Massdrop has already created communities in 11 categories. Co-founder and CEO Steve El-Hage (pictured above) said the oldest communities (namely, the ones for audiophiles and for fans of mechanical keyboards) are the most popular, if only because they’ve had a head start. Massdrop says it now has a registered user base of more than 1 million people.

El-Hage plans to launch four new communities before the end of the year, and then add a new community every month in 2016.

Josh Breinlinger, an early OfferUp investor, and Partner at Jackson Square Ventures actually noted this shift 9 months ago. Writing in Vertical or Horizontal, he tried to unpack the danger in funding every available vertical:

The high price vertical is dominated by marketplaces for cars and homes, e.g. Zillow, Redfin, Beepi.  These are infrequent purchases with a very high ticket price.  Consumers in these verticals care about price, selection, and service more than turnaround time and convenience…

Now, let’s look at a different vertical.  Let’s take locksmiths. Does an “Uber for Locksmiths” make sense? I’m sure it would be a wonderful buyer experience to be able to push a button and have a locksmith show up in 5 minutes to fix a lock for $75.  So, if somebody built this, would it be successful?  I believe the answer is a resounding “no.”  The economics of customer acquisition and usage patterns just don’t work because a consumer may only use a locksmith once every couple years and only pays a small amount of money…

The way to address this problem is to get horizontal usage.  Let’s imagine that same locksmith marketplace also offers plumbers, gardeners, housecleaners, and carpet cleaners.  Now a user can sign up to get a locksmith, but also use the service for every other home service.

What Josh is really saying, and what the public markets seem to be affirming is that TAM (Total Addressable Market) is becoming one of the major if not the absolute primary considerations in valuation and health of a business. Growth, in and of itself, isn’t the predictor of value it used to be because growth can be manipulated by heavy marketing spend AND will taper hard when companies try to pull unit economics in line IF the TAM or network effects are insufficient. Here’s a subset of the recent multiple contractions – Enterprise Value against TTM Net Revenue – across the tech/marketplace sector just over the past two quarters (Q2 of 2015 –> Q4 2015):

The Sad State of Verticalization-Img1

The Sad State of Verticalization-Img2

 

While its an imperfect analysis given that eBay and TripAdvisor – the two most stable companies in this sample – are materially more mature than the other comps, there remain some clear takeaways:

  1. For example, while Shutterstock is nearly as mature as TripAdvisor (founded in 2003 versus 2000) it is the biggest loser on a EV/Net Rev basis. It’s also has the smallest TAM of any company in the sample ($16 Billion).
  2. Etsy’s contraction is comparable which makes sense given that its TAM is arguably similar…I made the case back in Unpacking Etsy’s S1 that no one actually knows Etsy’s TAM but that their aggressive community policing and regulations have unquestionably constrained its potential.
  3. In spite of LendingClub’s hyper growth, one might have imagined that its multiple contraction would have at least been in line with its peer set, if not actually lower, given its dislocation. My belief is that $LC is still trading at a material premium to the market because its TAM as the premier marketplace for “lending” with potential expansion far beyond consumer and SMB loans is absolutely massive. Of course its 100% Y/Y growth helps, but its TAM is absolutely massive.

In summary: what I learned in 2012 still appears to hold true – consumers love vertical specific workflows. But investors love massive markets. And therein lies the dislocation. Heading into 2016’s bearish investor environment my belief is that startups targeting niche verticals (even those into the $billions) – without a clear story or understanding of how to expand horizontally, will be at a considerable disadvantage.

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