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Dear readers,

I’m happy to announce I’ve completed my first year in my new role at a16z, and it’s been a blast! I will write more about it coming up, but in the meantime, it’s very timely that my colleague Scott Kupor has written a new book, Secrets of Sand Hill Road, with the fun subtitle “Venture capital and how to get it.” I’ve had the pleasure of reading ahead of its release, and as expected, it’s excellent, and provides a detailed guide and fantastic in depth info on everything you’d want to know about venture capital. As an author, Scott could not have more street cred — he joined and built a16z from the very early years, and is our go-to on all the nitty gritty of the industry for the whole team.

You can (and should!) pre-order the book here »

There’s a bunch of great topics, including:

  • Why the skill you need most when raising venture capital is the ability to tell a compelling story.
  • What to do when VCs get too entangled in the day-to-day operations of the business.
  • Why you need to build relationships with potential acquirers long before you decide to sell.
  • Why most VCs typically invest in only one startup in a given business category. 

The math of startups and venture capital
Of all the topics of the book, one of my favorites has to be the math of startups and venture capital, because it gives us a perspective on the life and death of startups as a whole. Because venture capital is an index of the broader startup ecosystem, it can tell us a lot — everything from how often the Ubers, Dropboxes, Facebooks, and Googles emerge as startups, to how quickly doomed startups typically fail.

All of these tell you why many venture capitalists ultimately end up being interested in companies that want (and can!) get big — and it’s not the right way to finance the vast majority of new companies, many of whom are more focused on smaller markets or slower growth business models. I want to share a couple slides that Benedict Evans from a16z presented a few years back to make this point:

The above tells an amazing story: Over the past few decades, a small number of startups — 6% — end up driving 60% of the returns.

And I suspect if we were to dig into the 6%, we see that just a small number, probably a dozen or so per year, that drive a substantial amount. In other words, the startups that end up big end up really big. These startups aren’t just unicorns, they are another order of magnitude more successful than that.

It also tells you why, as an entrepreneur, that investors are so focused on network effects, high margins, technology differentiation, a 10X product experience, etc. — these are the foundational drivers that help create this super huge outcomes.

Above: Here’s another surprise from the data, which is that the best investors don’t seem to be better at avoiding startups that fail. It’s not about the downside. Instead, the data says that a “good” 2-3x fund and a fantastic >5x fund lose money about the same % of the time.

However, for a fantastic fund, its winners are much, much bigger than everyone else’s. For these top funds, the biggest startups end up generating 90% of the returns. It’s all about upside! For startups that ask why investors seem so obsessed with market size and say that few ideas are big enough, here’s the data that explains why.

The J-Curve
Finally, there is the concept of the J-curve in venture capital investing in which you look at a basket of startups over a long period — say, 10 years — and see how the returns look. And it often resembles a J, where the early years look pretty bad! And then eventually the big winners get bigger and bigger, picking up momentum to ultimately drive returns for the fund.

It looks like this:

This graph demonstrates the phrase that “lemons ripen early” — as Secrets of Sand Hill Road discusses. A portfolio of startups will often have early losses as the teams without product/market fit run out of money early. The successful ones that will become the winners take time to emerge. These days, it can take 3-5+ years from the company’s inception to see its true growth trajectory. As a result, there’s a J-curve that shows early losses followed by the successful startups making up the different in the later years.

If you are as fascinated as I am about all of this, I know you’ll enjoy Scott’s book. I want to leave you with an excerpt below. In the section, he discusses the J-curve in detail and why it behaves why it does. Hope you enjoy it!

Thanks for reading, and more from me soon.

Andrew

Secrets of Sand Hill Road: Venture Capital and How to Get It
by Scott Kupor

“Carried Interest”

The heart of compensation for GPs (at least for those who are successful investors) is carried interest. It’s rumored that the term “carried interest” derives from medieval traders who carried cargo on their ships that belonged to others. As financial compensation for the journey, the traders were entitled to 20 percent of the profits on the cargo. That sounds very civilized, if not rich. I’ve also heard—although my Google search is failing me now—that the carry portion of carried interest referred to the fact that the traders were allowed to keep as profit whatever portion of the cargo they could literally “carry” off the ship of their own volition. I prefer that story.

Regardless of its historical origins, carried interest in the VC context refers to the portion of the profits that the GP generates on her investments and that she is entitled to keep. As with the management fee, the actual amount of carried interest varies among venture funds but often ranges between 20 and 30 percent of the profits.

As it turns out, how we define “profits” and how and when the GP decides to distribute those profits to herself and her LPs is a matter for negotiation in the LPA.

Let’s use a simple example to illustrate.

Go back to that $100 million venture fund we talked about before, and assume that we are in year three of the fund’s existence. The GP invested $10 million in a portfolio company earlier in the fund’s life, and now the company is sold for $60 million. So, on paper at least, the GP has generated a tidy profit of $50 million for that investment. She’s also invested the rest of the $90 million in other companies, but none of those has yet been sold or gone public. Ah, she can taste the carry check already!

But how does the money get divvied up between the LPs and the GP? Let’s assume that the GP has a 20 percent carried interest; in simple terms that means that when the fund earns a profit, 20 percent of that goes to the GP.

So, in our example, the GP is sitting on a $60 million check, of which $50 million represents profit, and wants to give 80 percent of the profit (or $40 million) to the fund’s LPs and keep 20 percent (or $10 million) for herself. The other $10 million in this example will go back to the LPs as a return of their original capital. We’ll come back to this later in this chapter and add some additional complexity to this.

But wait a second. Is there really a profit on which the GP is entitled to take her 20 percent? The answer is maybe. We need to take a little detour to introduce two other important concepts before we can conclusively answer the question.

As with fine wine, VC funds should get better with age. In fact, that’s why people in the industry refer to funds by their “vintage year” (or birth year), just as winemakers date mark their wines based on the year of the grape harvest.

As we discussed earlier, in the early years of a fund, VCs are calling capital from LPs and investing that capital in companies. This is a decidedly negative cash flow motion—money is going out with (likely) no near-term prospect of money coming in. That’s an expected effect, but eventually a VC must harvest some of those investments in the form of those companies going public or being sold.
The effect of calling capital from LPs in the early years coupled with the long gestation cycles for companies to grow and ultimately exit—in many cases it takes ten or more years for companies to be sold or go public—creates what is known as the “J curve.”


As you see in the above picture, the LP has negative cash flow (from the capital it’s giving to the venture firm for investment) in the early years of a fund and (hopefully) positive cash flow in the later years of the fund, a combination both of the capital having already been called and invested and the portfolio companies being sold or going public.

Venture capital is truly a long-term game. But, as explained in our discussion of the Yale endowment in chapter 4, cash does eventually need to come out the other end. Successful GPs will manage their portfolios to drive to this outcome, which can affect how they interact with entrepreneurs on this topic.

One phrase you often hear in the hallowed halls of VC firms is “lemons ripen early.” That is, the non-performing companies tend to manifest themselves close in time to the initial investment. Interestingly, this exacerbates the J-curve problem in that not only are VCs investing cash in the early years of a fund, but the non-performing assets are certainly not helping the GP return money to the LPs.

Reprinted with permission of Portfolio Books

The post Why startups are hard — the math of venture capital returns tells the story appeared first on andrewchen.

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Dear readers,

Podcasting has been a slow burn, and has turned into a movement. 90 million Americans now listen to podcasts, and if your behavior is anything like mine, it’s turned into a multi-hour per week habit. I reach for my podcasts whenever I’m commuting, whenever I’m doing a long walk between offices, or if I’m doing random stuff around the house. No wonder the consumer investment team ended up digging into this trend by doing a market map report — the analysis led by Li Jin and including work from myself, Connie Chan, and others. You can follow and message Li on Twitter if you have thoughts about the piece.

See below for a long-form analysis everything we’ve observed in the podcasting industry. It was originally published on a16z.com. There’s a lot to read here, but I wanted to highlight a couple of my takeaways and what I’m looking for now:

  • Podcasting is big, mainstream, but severely undermonetized — and some of the biggest opportunities in the podcasting space lay in pivoting the business model from ads into some kind of direct payment. I’m looking for startups that can change the game there.
  • The bigger idea is actually “audio”, not specifically podcasting. And in fact, the combined revenue of Headspace and Calm are more than half of the entire podcasting market. Whoa! I’d be interested in other products that tap into the trends around AirPods, Alexa, voice assistants, etc., but may not directly sound like podcasting
  • After this analysis, I’m looking for really differentiated verticals of audio. Meditation is one, but what about something that’s at a much higher price point? For example, something that’s very business-focused and can be put on a corporate credit card? It could create a strong advantage around paid marketing if a product has high subscription retention or ARPU, allowing them to make higher bids in the various ad networks.

The report covers things in more detail at the end, but that’s the tldr; from an investment standpoint.

The other quick plug I want to give — get a copy of the PDF version of the deck by joining the a16z newsletter:

Subscribe to the a16z newsletter here.

The a16z team uses the newsletter to circulate resources, including podcasts, op-eds, presentations, and more. You can subscribe to get more updates.

Without further adieu, here’s the a16z consumer team’s definitive analysis of the podcast ecosystem in 2019. Enjoy!

Thanks,
Andrew

Investing in the Podcast Ecosystem in 2019 by Li Jin

In the world of podcasting, the flywheel is spinning: new technologies including AirPods, connected cars, and smart speakers have made it much easier for consumers to listen to audio content, which in turn creates more revenue and financial opportunity for creators, which further encourages high-quality audio content to flow into the space. There are now over 700K free podcasts available and thousands more launching each week.

As new tech platforms hit scale, we on the consumer team have been closely watching the future of media and the technology driving it — in all forms. We’re interested in investing in the next wave of consumer products and startups coming into the ecosystem, and that includes the audio ecosystem.

Our investment philosophy is to not be too prescriptive, so we do the kind of “market map” overview below to help us have a “prepared mind” when we see new startups in the space. The below deck and commentary (with some sections redacted, of course) was presented to the extended consumer team, including general partners Connie Chan and Andrew Chen, who are investing in this space. If you’re working on anything interesting in this area, we’d love to hear from you!

From niche internet community to one-third of Americans

Over the course of the last 10 years, podcasts have steadily grown from a niche community of audiobloggers distributing files over the internet, to one-third of Americans now listening monthly and a quarter listening weekly.


Americans listening weekly to podcasts grew from 7% in 2013 to 22% in 2019. 65% of monthly podcast listeners have been listening for less than 3 years.

People are already spending a lot of time on podcasts, and it’s growing: listeners are consuming 6+ hours per week and consuming more content every year.

Among weekly podcast listeners, there’s high consumption: 7 episodes per week and nearly 1 hour per day.

The demographic of podcast listeners is not your average American. Roughly half of podcast listeners make $75,000 or more in annual income; a majority have a post-secondary degree; and almost one-third have a graduate degree [source]. There’s also a gender gap with podcast listeners skewing mostly male, mirroring the gap among podcast creators as well. However, the gender gap has narrowed from a 25% gap in 2008 to 9% today.

Podcast listeners are not your typical American: they’re affluent, highly educated, and skew male.

In the years following the release of Apple’s podcast app in 2012, smartphones pulled ahead of computers for podcast consumption and have grown to become the dominant way that consumers listen to podcasts. The green line includes smart speakers, which have grown 70% year over year in terms of listening.

Since Apple launched its Podcasts app in 2012, smartphones have quickly grown to become the most common device for podcast consumption.

What may surprise people living in heavy commuter markets is that listening primarily happens at home, which represents almost half of all podcast consumption.

We would also anticipate that more recent technologies like Bluetooth-enabled cars and smart speakers — now owned by 53M Americans or 21% of the population — could change the mix of where podcast listening happens.

The lion’s share of podcast listening happens at home, followed by taking place in a vehicle.

A brief history of podcasting

Simply put, podcasts are digital audio files that users can download — or in some applications, stream — and listen to. While podcasts differ widely in terms of content, format, production value, style, and length, they’re all distributed through RSS, or Really Simple Syndication, a standardized web feed format that is used to publish content. For podcasts, the RSS feed contains all the metadata, artwork, and content of a show.

To listen to a podcast, a user adds the RSS feed to their podcast client (such as Apple Podcasts, Spotify, etc.), and the client then accesses this feed, checks for updates, and downloads any new files. Podcasts can be accessed from computers, mobile apps, or other media players. On the podcast creator side, creators host the RSS feed as well as the show’s content and media on a hosting provider, and submit the shows to various directories, such as Apple’s podcast directory.

Podcast content is typically available for free, though creators can choose to set up private RSS feeds that require payment to access.

Current headlines about podcasts today hail them as the next major content medium, describing them as “suddenly hot”, as the next battlefield for content, and as an “antidote” for our current news environment:

How did this “suddenly” happen? As with all tech trends, it had a longer and slower start before going more mainstream. Let’s time travel back 15 years ago, when there were no smartphones and the internet was accessed only through desktop computers.

In February 2004, journalist Ben Hammersley wrote about the emergent behavior of automatically downloading audio content in a February article in The Guardian:

“MP3 players, like Apple’s iPod, in many pockets, audio production software cheap or free, and weblogging an established part of the internet; all the ingredients are there for a new boom in amateur radio. But what to call it? Audioblogging? Podcasting? GuerillaMedia?”

In doing so, Hammersley accidentally invented the term we still use today, “podcasting” — a portmanteau of “iPod” and “broadcast” — for this kind of content. The word was added to the Oxford English Library later that year.

In 2005, podcasts were added to the iTunes store, with Steve Jobs saying, “Podcasting is the next generation of radio, and users can now subscribe to over 3,000 free Podcasts and have each new episode automatically delivered over the Internet to their computer and iPod.”

In 2007, the first iPhone was introduced, but it wouldn’t be until 2012 that Apple created the Podcasts app. The release of this app is widely considered an inflection point for the industry, as it put podcasts a single tap away for hundreds of millions of users around the world. Ironically, a few months later, Google discontinued its own podcast app called Google Listen.

In 2014, the first season of Serial aired, considered to be the first breakout podcast, with its narrative audio journalism drawing in 5M downloads in the first month.

In the past 5 years, there’s been an explosion of listening behavior and innovative content. New devices made it easier to listen: Alexa launched in 2015, Google Home and AirPods in 2016. And an explosion of new content — ranging from daily news to narrative to talks shows — met the growing listener appetite. In tandem, ad spend has been growing steadily each year, from $69 to $220M in 2017 [source].

The app landscape Many apps for listening to podcasts, but little differentiation or loyalty

Apple Podcasts played a pivotal role in the development of the industry and remains the dominant app for listening. However, its market share has fallen in the last few years, from over 80% to 63%. The corollary to this stat is that historically, podcasting has been predominantly an iOS user behavior, given that Google didn’t have its own native application, something that changed last summer with the launch of Google Podcasts.

Apple’s share of the podcasting market has slipped from over 80% to 63%, while Spotify has quickly grown to almost 10% of the market.

Spotify — which has made a big push into podcasts in just the past couple years — now accounts for almost 10% of listening.

Beyond these two large companies, there’s a long tail of listening apps from smaller companies. Most of these apps all have roughly the same content, given widely open directories of podcast RSS feeds. And there’s hundreds more listening apps out there. The barriers to entry for creating a new podcast app are quite low, since content is all distributed via RSS feeds and anyone can access them. There are also tools for creators to create their own podcast app from their own RSS feed.

A note on comparing listening apps: metrics between apps are not entirely an apples-to-apple comparison, as some apps (like Apple Podcasts, Overcast, and Stitcher) auto-download shows that users subscribe to, whereas others (e.g. Spotify, Castbox) don’t continuously download new episodes. This affects comparisons between apps and may overstate the traction of listening apps that auto-download shows. The industry has not standardized around what defines a download or listen.

A taxonomy of consumer podcast apps

From our research, users seldom feel passionately — either positively or negatively — about the podcast app they’re using. This suggests that the audio content itself is the core element users are engaging with, and since the content is the same on all apps, users don’t feel particular affinity to any one listening app.

Three major categories of consumer podcast listening apps: the incumbent, large existing audience and new podcast focus, and long tail listening apps.

I categorized consumer podcast listening apps into three major categories:

  • The incumbent: Apple Podcasts
  • Companies with large, existing audiences who are newly focusing on podcasts
  • Long-tail listening apps

The major feature of Apple Podcasts is that — despite its shortcomings in user-facing features and monetization — it’s pre-installed on all iPhones, making it a tap away for 900M people worldwide. We estimate that Apple Podcasts has 27M monthly active users in the U.S., based on App Annie, so a sizeable absolute number but relatively small compared to the total install base. Though Apple accounts for the majority of podcast listening, the company currently doesn’t monetize podcasting at all — all ads that you hear on podcasts are a result of advertisers and podcasters connecting off-platform.

For some users, the app is a basic, functional listening app, as compared to other media apps and products, with rudimentary categorization and discovery features. For some creators, the features it currently lacks include native monetization capabilities, in-depth analytics, demographic information for listeners, or any attribution for where listeners come from. Since Apple Podcasts launched in 2012, the app itself has changed very little. The New York Times wrote in 2016 that “the iTunes podcasting hub that Mr. Jobs introduced remains strikingly unchanged,” and beyond adding more analytics features in 2017, the same still holds true today.

In the second category, there’s a number of media and technology companies that have large existing audiences making a big push into podcasts, including Spotify, Pandora, and iHeartRadio. The strategies for these companies are mostly centered around leveraging their existing audiences to cross-promote podcasts; using listener data to personalize listening experiences or to help surface relevant podcasts; and leveraging their reach and existing monetization mechanisms to help creators earn more revenue. Google, which launched a standalone Podcasts app last year, has talked about making podcasts a first-class citizen in terms of surfacing podcast content in search results, as well as the growth opportunity that Google users worldwide represent in terms of potential podcast listeners.

Finally, there’s the long tail of podcast apps. These are comprised of startups and a fair number of non-VC funded companies. These apps are predominantly competing on the basis of better user-facing features such as improved discovery, search, and social capabilities, as well as creator monetization including their own ad networks or direct user monetization features. Increasingly, startups in this last category are also looking for other ways to distinguish themselves outside of listening experience — including experiments with exclusive, sometimes paid, content.

A discussion about shifting user behavior around consuming podcasts would be incomplete without calling out Spotify. In just the past few years, Spotify has burst onto the podcast landscape, moving from being music-centered to “audio-first”, and becoming the second largest platform for listening after Apple Podcasts.

Spotify’s market share in podcasting has grown to 9% in a few short years based on data from Libsyn, a podcast hosting provider, and the company has laid out plans to become a destination for all types of audio content.

Interestingly, Spotify may be growing the market of podcast listeners: the data below from Megaphone (formerly Panoply Media) shows that downloads of podcasts from Spotify happen in geographies that historically had fewer podcast downloads.

Downloads data suggests that Spotify is growing the audience of podcasting.

Spotify also accounts for two of the largest podcast acquisitions in industry history —..

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Am I just getting old?
When I encounter a new product idea for the first time, I find myself asking: Is this idea dumb? Or I just getting old?

Early on, there’s often not much to judge it on besides the idea. Sometimes the idea sounds either dumb or trivial. But over the years, I’ve started to not try to judge too much, especially when it’s early

Ideas seem pretty random because in the past few years, some of the biggest wins were: An app that lets you get into strangers’ cars. An app that lets you stay at random peoples’ houses. Disappearing photos. A site that doesn’t let you play video games, but you can watch other people play. Seriously?

And if you go back a few years earlier, I remember having entire convos about why anyone in the world would want a profile or a website on the internet. Or why phones should be used for calling, and adding email was dumb. It sounds silly, but that was the perspective then

The Dumb Idea Paradox – the official definition
The dumb idea paradox is what happens when an idea sounds dumb, and yet you have a (usually very small) group of people highly engaged in doing it. And maybe that group of people seem to getting bigger and bigger. Will it continue? Will millions ultimately do this thing?

When products that have this property — it’s counterintuitive behavior PLUS it traction — imho they are the most attractive startups in existence. After all, this is an indicator it’s likely in a new market, and often times, the TAM of these markets ends up being huge!

In other words, this handy graphic:

(Note I made that as a screenshot in GSheets. You’re welcome)

Natives versus immigrants want different kinds of products
Furthermore, these ideas often formed at the seam of the “natives” versus the “immigrants.” If you are Instagram-native, what you consider a great idea for a new retail space or ecomm brand is likely very different than someone who isn’t exposed to the same thousands of pics

The upcoming generation are using tech in a different way. They are Fortnite-native. Minecraft-native. They are streaming-native. They use “insta” differently. Food delivery will be considered a human right. The expectations will be very different.

For network effects-driven products, it matters that your friends are also into the same thing. If my peers aren’t playing Fortnite every day, then I won’t see the same value and engagement. Contrast that to a fully activated network of kids that are on it every day

Thus, I’m sure that the first time I hear about a wild idea that appeals to this group, it will be easy to dismiss out of hand. And perhaps I’d be more attracted in something that takes on the same trends, but is more familiar

Strong and weak technologies
My partner Chris Dixon has written about the idea of strong and weak technologies, which often arrive in pairs at the start of a new technological age. The weak version often sounds more practical, but the strong ones often win. Here are some examples:

The weak version of a technology is often the more plausible, “immigrant” version of an idea. The stronger version will sound better to folks who are natives.

As an investor in consumer companies, I’m always startled when I see surprisingly strong growth metrics on top of an idea that I don’t get. It’s always a signal that I need to dig deeper, at least until I feel like I’m starting to get it. But it’s hard.

So I repeat the question: The next time you hear an idea that sounds dumb, ask yourself — is it really dumb? Or are you just getting old?

The post The Dumb Idea Paradox: Why great ideas often start out by sounding dumb. appeared first on andrewchen.

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Dear readers,

Many of you may have read the recent New York Times article “Uber and Airbnb Alumni Fuel Tech’s Next Wave” which is about how alumni of successful startups often split off and start new companies, and how ecosystems of investors/advisors form around these new companies to support them. In the NYT article, I mention that a16z has invested in 2 ex-Uber teams, and today, I’m excited to announce the first one — Pietra — a new startup focused on a marketplace for the jewelry.

In the announcement, I talk both about Pietra, and Ro/Pan and the team and also about the characteristics of ex-Uber alumni that make me excited to invest in them: 1) the ceo mentality of ops teams and “programs and platforms.” 2) unique expertise with marketplaces and network effects, and 3) deep scaling and technology infra.

I included the entire Pietra announcement below, which was originally published on the a16z blog here.

Thanks!
Andrew

Marketplaces, Pietra, and the Network Effects of Next Startup Talent

One of my focus areas as an investor is marketplaces, because I’ve seen firsthand how they can transform an industry — especially when they also have network effects that can lead to huge scale and impact. And while marketplaces have been evolving into new areas for a while — including services — I especially love how marketplaces show up in interesting and sometimes unexpected places, places where technology has not gone before.

One such area is jewelry (yes, jewelry!). Even though gemstones and jewelry have been at the center of art, commerce, and culture since the dawn of human civilization — going from stone jewelry created 40,000 years ago in Africa to the trade routes between East and West to Fifth Avenue in New York to the Instagram feed on your phone — the technology for discovering, designing, and purchasing jewelry online hasn’t evolved much at all. Yet jewelry is one of the categories that could benefit most from modern trends such as social media, mobile, and mass personalization. This is especially true for the incredible variety of artisans and boutique jewelry vendors out there who currently can’t access bigger markets, or the deep technology expertise and stacks of bigger players.

That’s why I’m excited to announce Andreessen Horowitz’ seed investment in Pietra, a new startup focused on a marketplace for the jewelry and especially the diamonds industry. If you wanted to buy a diamond engagement ring, the process goes something like this: “Do you know where I can buy a diamond?” “I might know a guy.” That “guy” (more often a family business, an aggregator, or other player) then sells you a diamond with very little transparency into supply, pricing, or other things. That kind of exchange is ripe for technology to come in between and mediate things — not only efficiently connecting suppliers to buyers, but also expanding supply and demand for both sellers and buyers beyond local limits.

Jewelry represents $200B+ of annual spend, but remains a highly fragmented and opaque market… it’s yet another way marketplace businesses can provide more transparency, variety, and even education for consumers. So Pietra aims to fully modernize the jewelry buying experience across every touchpoint by offering beautiful, mobile-first product discovery; chat and collaboration tools to better engage, negotiate, and purchase jewelry; and vetted suppliers, along with curated product lines from boutique jewelers, influencers, and celebrities.

The team comes with decades of deep expertise in fashion, luxury commerce, and marketplaces. Co-founders Ronak Trivedi and Pan Pan are two of my former colleagues from Uber, where they led key efforts on UberPOOL and grew it from a new product only available in San Francisco to a global product supporting hundreds of millions of trips per year and billions in gross bookings. That kind of scale matters in a market like this. In fact, many of the core marketplace lessons and mindsets from Uber — combined with the team’s experience in the jewelry industry, deep customer insights, and passion for design — led to their starting Pietra.

I’m also personally very excited about the new wave of “network mafias” coming from people trained at Bay Area startups who go on to do new and different things, often borrowing from lessons learned in their previous startups. Classic examples include Paypal, and more recent examples include Square and others. For Uber alumni in particular — which I can personally speak to since I worked there for three years — there are three mindsets that are compelling to me and that I love seeing in startup founders are: (1) an entrepreneurial mindset that’s baked in at all levels; (2) specialized expertise that can transfer across industries; and (3) technical challenges coupled with networks of talent.

Because rideshare grew city by city at Uber, it led to an entrepreneurial team structure where each city had a General Manager (GM) who served as the de facto CEO of the city, acting like a mini-startup in the context of the larger organization. Surge pricing and driver incentives were first manually implemented by local teams with SQL queries and spreadsheets, and only later widely implemented in code by the software teams at headquarters. When I first joined Uber, each product team was also set up to be full stack, without dependencies into other teams, allowing them to build fast and iterate quickly to solve challenges. This kind of mindset — everyone’s the CEO of their own mini-startup unit — is key to fast cycles of innovation.

To make rideshare work as a global product, folks at Uber had to solve challenges in areas as diverse as Jakarta to Portland to ridesharing and food delivery. Whether it was solving the cold-start problem in a new market, or figuring out the best pricing and incentives, or growing network effects in a highly competitive market, those insights can be translated to new industries. Starting any new company requires founders to turn a series of insights into actions and products.

To be clear, it’s not just marketplace expertise that’s important here — it’s also about solving deep technical challenges at scale in areas such as machine learning, data, infrastructure, mapping, automation, and much more. But the social aspect of the Uber alumni network is also appealing, with a rich ecosystem of folks advising and angel investing in companies, paying it forward and creating a new generation of startups.

I’ve said it before: technology changes, but people stay the same. Whether it’s applying new behaviors and technologies to evergreen things — like jewelry! — or the evergreen turnover of a new wave of entrepreneurs founding the next generations of startups (in developer APIs, video streaming, SaaS, etc.), I’m excited to see what everyone does next. And I’m looking forward to investing in more companies like Pietra.

The post Announcing Pietra and a16z — my first ex-Uber investment! appeared first on andrewchen.

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Dear readers,

I recently hosted an AMA on Quora where folks asked a bunch of really fantastic questions. Thanks to Adam D’Angelo and Alecia/Adrienne for getting this set up.

Wanted to share a couple of the most upvoted answers below:

  • What do you look for in an investment?
  • How long should a founder be without salary?
  • What distribution channels should a new consumer internet startup consider in 2019?
  • What investment have you made that is the most out there?
  • Which commonly-discussed growth metrics in consumer tech businesses are the most meaningless and/or misleading?
  • What is your advice for startup CEOs?

Enjoy!

Andrew

1. What do you look for in an investment?

This one is hard to answer generically — it’s easy to say, great team! Or big market! Or technology differentiation! Or something generic like that. However, being in venture capital is about being in the “exceptions” business.

There were hundreds of mobile photo apps prior to Instagram and Snapchat, and they would have been money-losing investments. Same for social networks before Facebook, or there were more than a dozen investor-backed search engines before Google.

My job is to find the exception to the rule, and pick an individual company that will stand out, and I don’t have to be bullish about an entire category of companies. In practice, this happens also because individually, I’m focused on doing 2–3 investments per year, and don’t have the capacity to, say, invest in every single company working on XYZ.

All of that said, beyond the obvious things (team, market, product, etc.) there are a few things that make me lean into understanding a company, in particular.

First, it’s interesting when a startup using a new platform or a new technology in a clever way. For example, Instagram Stories and Snap Stories are a huge new short-form video format, and an app that might interact with these stories in an interesting way might be compelling. Or because esports is so huge, if someone builds on the idea that perhaps games content could be streamable-first, then that’s intriguing too. Taking advantage of a new technology helps answer the “Why now?” question and explains why it’s a fresh opportunity that should be tried. If your new startup could have been built 15 years ago, perhaps the idea’s already been tried and just isn’t that good.

Second, technology changes constantly but people stay the same. And their motivations — in particular, to spend time with friends, to date, to be able to earn more, to find better work over their careers, to take care of their pets, etc., etc. — also stay constant over time. So when a new startup purports to create new consumer behavior, I’m sometimes skeptical. But if a product allows people to tap into a pre-existing motivation but in a new, fresh way, then I’m interested.

Third, I like to see a strong insight around how the product will grow. For example, it’s important if a new video streaming startup, for instance, has deep relationships with the YouTube/Instagram influencer community to get it off the ground. Or if a new workplace collaboration tool is built to tap into calendars and be inherently viral through cal invites. The reason for this is that we are in an interesting era of new technology products where in general building the technology is not all that hard. Startups typically don’t fail because of technology issues, given open source, AWS, lots of collaboration tools, a network of smart people, etc., etc. This used to be the case decades ago, but these days, startups fail because they don’t get traction in the market. As a result, I like to see something clever and insightful in how the product will get off the ground — especially if it’s driven by viral growth, or some form of organic, as opposed to paid marketing.

Usually at the stage where I am seeing companies, one of the big things I’m evaluating for is “it works!” I usually look at their growth metrics, cohort charts, acquisition mix, engagement data, etc., and try to make sure that it’s sticky now and will remain so over time. Once I validate this, then I move onto some of the bigger qualitative questions like the ones above — what’s the trick that makes it grow? Why now? What new technology does it exploit? What classic human motivation does it tap into?

And finally, I want to reiterate that it’s all about finding the exceptions. You can spend as much time as you want analyzing a space, but it’s just about picking the individual startup you like most.

[PS. Here’s also a deck I published a few months back that is the more visual, longer-form answer to this question]

2. How long should a founder be without salary?

I’m a believer in free markets, and also in thinking long-term.

When founders first get their company off the ground, they often take risk and go without salary. However, as soon as they raise a real amount of money — either from institutional seed funds, a large group of friends/family, or with a VC — I think the founders should pay themselves basically market rate (within reason)

The reason for this, especially if there are cofounders, is that starting a company is already hard enough. Your customers are leaving you, recruiting is hard, employees will occasionally quit. It’s hard to think long term, about all of this when you’re worried about your paycheck.

If on top of all of this stress, the founders are paying themselves way below market, to the point where they are burning their savings, that’s just not a good thing. It creates a lot of stress, and unwanted behavior from the perspective of an investor.

Obviously if there’s a case where the founders were highly compensated before and it would impact the runway, OK, then great, there’s an opportunity to trade off a longer runway by capping the cash compensation. If the team wants to do that, great.

But in general, I believe in market rates for everyone, including the founders and the employees, within reason.

[PS. I tweeted this out and my friend Suhail Doshi responded with a pretty cool rule of thumb:

My rule of thumb is…
– seed funding: what you’d pay your lowest paid employee
– when you’re growing a bit: your lowest paid engineer
– scaling: mid level engineer
– successful: market for ceo pay
– not growing: cut back to your previous comp until you are / helps survive

This is pretty great. Thanks Suhail!]

3. What distribution channels should a new consumer internet startup consider in 2019?

First, let me start with the negative. It’s been said (and written) that we are kind of in a funky consumer internet winter, compared to 2007 when we had the Facebook platform and the iOS/Android platforms and so on. As a result, the conclusion is that there’s a general industry malaise and everything sucks and we should all go home, etc., etc.

It’s my conclusion that this is a vastly overhyped POV about consumer.

Last year, when Fortnite went from zero to 200M+ users, how could you not be excited about consumer tech? Or where we see Kylie Jenner built a multi-hundred million dollar revenue stream selling stuff on Instagram? Or you have a content creator like Ryan, the kid that makes unboxing videos, generating $20M+ per year?

There’s a lot of exciting opportunities out there. In my first few months at a16z, I met hundreds of companies in my first 3 months. Hundreds! There’s a lot of innovation and entrepreneurs out there trying to do great things.

Yes, it’s true that you can’t just build well-designed social photo apps and still expect to succeed. You have to do something different, and evolve with the time. But IMHO there are still fantastic opportunities.

OK, now going past the preamble and answering the question directly:

The best distribution channels for your startup are the ones that only make sense for your product to use — meaning it’s proprietary, and people can’t just tap into the same channel right away. The problem with Facebook ads as a channel, for instance, is that if you’re a mattress startup buying ads, you’re not just competing against all the other mattress companies but you’re also competing with the cool new protein shake company. Contrast that to Dropbox, which has primarily grown using shared folders inside the workplace — they own that channel, and the only others who could compete on that are folks who have some kind of shared folder functionality. The performance of the channel is unlikely to degrade over time via competition because it’s proprietary.

If you agree, then the obvious question is, if I’m a startup looking for a proprietary channel, which one do I use? That’s hard to answer generically, so I won’t attempt to do so. However, the better observation is that if you are starting a brand new company, then you have the opportunity to both pick the idea — and have a hypothesis about product/market fit — as well as to pick its growth strategy at the same time. If you can think about both at its inception, then you can start thinking about a proprietary channel from day 1.

I think this is not the answer the person who wrote the question wanted to hear, so let me also try to give some more trend-driven ideas too.

I like video. There’s a lot of video being created and consumed, and I like the idea of a “video-native” product that is designed to create a lot of video as part of user engagement. Or create a lot of opportunities for streaming.

I like social data in the workplace. If you are building a workplace collaboration tool, whether it’s horizontal like Slack or more vertical like Figma, most of the files and systems you touch understand who all the users are inside the company. In particular, the calendar is a very rich data asset full of people and their relationships, and I feel that’s underleveraged by startups seeking to grow. I love the pattern of putting, say, ZOOM links, inside of calendar requests, and think more startups might end up finding opportunities to do the same.

I also like “in-real-life virality.” If you walk around and see a bunch of lime green scooters, and people are using them, then you will want to try it too. Magically, no customer acquisition cost! Or if you see people walking around playing Pokemon Go, then you might want to try it also, since they are out and about, and enjoying it so much. I think this is an underrated channel.

4. What investment have you made that is the most out there?

One day I was in the Mission district of San Francisco, and saw a huge line of people. I wondered what they were waiting for, and naturally, the curiosity got the best of me and I got in line too. As I looked around in line, I read the sign for the place. There was a huge aardvark icon, and lettering that said BOBA GUYS.

I had heard of Boba Guys before, and remember that every time I saw one of their stores, I would skip it because the line was too long. Business was that good.

While waiting, I tried to google to figure out who their founders were. No luck. Eventually I found a Kickstarter page with some info, for a store they had opened near Union Square, and found their names. Just my luck, they were already following me on Twitter. I DM’d them, ordered my boba — hong kong style with pearls — and waited.

A week later, they replied. We met for lunch near Hayes Valley, and I didn’t know what to expect. Maybe I could invest money into this thing? Did I even want to? It’s just milk and tea, right? But so was Coca Cola, or Starbucks, or Blue Bottle.

To my surprise, both Andrew and Bin were fantastic. They had great consumer packaged goods experience, had worked at Timbuk2, and came with a 20-slide deck prepared. The deck had retail comps versus other high-end stores, financial projections, and more. It blew my mind. These were very obviously the most talented bubble tea store operators on the planet.

As a quick segue, I had been going to pitches for high-end restaurants with a few friends prior to that, but had never invested. Going to a restaurant pitch was extremely fun, as you went with a group of friends, met the chef, and they made the entire food menu and all the drinks too. You hung out and could invest after. But I never liked the model because it felt like it could never scale. It’d be a fun hobby, but it’d be hard to make money. But it helped prepare my mind for investing in retail, and a beverage play like Boba Guys.

Back to bubble tea, I realized after the pitch that although it wasn’t a tech company, I should figure out a way to invest. Andrew, Bin, and I had a great conversation — the first of many, and then I rallied some of my friends to put a syndicate together to invest.

The bonus to all of this is that I now have a Boba Guys Black Card. This is a special investor card that lets me get my daily bubble tea fix for free. It’s amazing, and the investment was worth it just for the bragging rights with that.

5. Which commonly-discussed growth metrics in consumer tech businesses are the most meaningless and/or misleading?

These are the obvious offenders:

  • Cumulative charts for anything. These can only go up and to the right
  • Registered users. Totally useless, although sometimes I like to ask about this as a ratio to active users to get a sense for how efficiently the user acquisition is happening
  • Any retention metrics that aren’t standardized into cohort curves. Sometimes people will give a single snapshot number, like a “3 months later, X% still use the app!” and that’s not that helpful
  • Install numbers, without signups or activated signups or something more meaningful
  • For marketplace companies, “revenue” that’s actually “gross bookings” or GMV. Or GMV that counts in weird things, like security deposits or one-time setup charges
  • ARR meaning, “annual revenue run rate” as opposed to “annual recurring revenue.” Please, let’s just stick to ARR for recurring, not run rate. Thanks.
  • Taking the peak revenue of any single day and annualizing it as the headline number
  • Unlabeled X and Y axes in charts
  • Cohort curves that are some complex subset of users that make the retention look better
  • Showing “CAC” that’s actually blended CAC, and when you just look at the Paid CAC, it’s way above LTV
  • Actually LTV. Because who really cares about the lifetime of a user — startups should just manage to margin earned by a customer you acquire over the first 6–12 months, not the lifetime. That’s how you will make your ad spend decisions
  • Any misleading ratios where the denominator and numerator are totally non-obvious. Stick to actives, please.
  • Active user definitions that are complicated (must have visited 3 sessions in the last week, and done one action out of a list of 5). It makes all the downstream calculations on retention, engagement, etc., misleading since you’re throwing away all the data for the less active users
  • If you have a desktop app, and web, and mobile, break down the metrics for all three. Don’t combine, please

There are many, many more… but that’s a quick start.

6. What is your advice for startup CEOs?

I have a lot of advice, but maybe I will share the top 10 that come into my head:

  1. You’re not doing this alone. You have friends, family, your investors, and employees rooting you on. Talk to them
  2. Everything seems like it sucks — metrics go up and down. Customers leave. An employee quits. Product/market fit could be a lot better. But this is how it feels even if it’s a rocket ship. Important to put into perspective
  3. Your job changes dramatically over time. Your first job is to build the machine — the product that attracts the customers, and generates the revenue. But eventually it turns into a job where you’re building the machine that builds the machine. It’s all about hiring, leading, managing, etc., etc. Prepare for this to feel weird when it transitions — especially spending 25%+ of your time hiring
  4. Everyone’s gotten very data-driven these days, which is great, but you should set your strategy, and then your metrics should follow. It’s to verify that your strategy is working — having a lot of dashboards is no substitute for strong product insight and strategy.
  5. Some people say to stay off Twitter and forget the distraction. I say the opposite – find interesting, knowledgeable people from social media, and DM them to meet in person. Stay outbound. Use it for recruiting, networking, fundraising and more.
  6. Raising money is a really, really important thing. It can feel like a great milestone, but it’s just the beginning.
  7. Ben Horowitz’s book The Hard Things About Hard Things is the best book about being a CEO and managing your own psychology as you set out to do this crazy hard thing. It’s fantastic. Read and re-read it.
  8. Also read and re-read High Output Management by Andy Grove.
  9. Build long-term relationships with your employees, investors, and people in the ecosystem. Hopefully your startup thrives, but maybe it won’t — and you’ll still want to build a long-term network because there will be more to do in the future
  10. Don’t worry about generic startup advice — including lists like this one :) Make sure you find advice that’s tailored to your startup’s stage, industry, and specific situation. Talk to experts who are willing to dig in. Lists like this are fun to read but there’s a big gap in applying them

OK that’s my first 10 :)

The post What do you look for an investment? How long should a founder be without salary? And other Q&A appeared first on andrewchen.

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I recently did a podcast with Ryan Hoover, co-founder of Product Hunt and my sister Ada Chen Rekhi, previously SVP Marketing at Survey Monkey – here’s what we talk about:

  • The network effects that makes Silicon Valley what it is. The uniqueness of the Silicon Valley tech ecosystem, how network effects conspire to create a “rich get richer” situation for cities, and why new communication tools enabling distributed teams to work together across continents could mean that there will be no “next Silicon Valley.”
  • Big companies versus small ones. Ada shares her insights on the contrasting skill sets needed when working at a big company versus a small startup, after having herself gone from a small startup to a huge organization like LinkedIn back to a two-person startup with her husband.
  • Personal life OKRs. How to port the concept of OKRs — objectives and key results, a personnel management framework originated by legendary Intel CEO Andy Grove — to your personal life from your business (and why you would want to). We talk about you can use them to help manage your exercise, social life and relationship with your SO.

Of course, we also chat about some of our favorite products, including an app that lets you pop in to a luxury hotel for a few hours to shower or have a nap, a super cool way to greet visitors to your office, and a new app for emailing yourself.

Here it is below as an embed, but if you don’t see it inline, you can listen to the podcast via this link too. If you like the podcast, you can subscribe here. Thanks to Ryan for putting this together, including the transcript!

Some quotes from the episode

“When you’re executing at a small startup, or a small team, or just by yourself, it really comes down to ideating, picking and prioritizing, and then rolling up your sleeves and just getting things done as quickly as possible. It’s a night and day difference from a big company.” — Ada

“If you graph cities, there’s a power law: the biggest cities are really big and there’s this long tail of all these little tiny cities, and the reason for that is that there’s a network effect within cities. These ecosystems emerge because the designers are here, because the engineers are here, because the capital is here, because the marketing people are here, and on and on and on.” — Andrew

“When it comes to working at a large company, it’s much more cerebral and much more about the heart. You’re thinking about how to collaborate and communicate across a cross-functional team to get the initiative done: can you communicate what it’s about; can you motivate people to get it done; can you manage all the working pieces?” — Ada

“Either these network effects will continue to hold and the Bay Area will continue to be strong, or we make big structural shifts in how we organize teams and workforces and the network effects become less strong. But that doesn’t mean some other city becomes the next Silicon Valley, there won’t actually be a “next” Silicon Valley — it either continues or will just be distributed.” — Andrew

“The irony of it is that sometimes when you are working on projects with such large scale, because the skill set is so different, it actually feels like you’re not doing anything at all — you’re merely managing the appendages of the other groups and trying to make sure everyone is staying on track and executing.” — Ada

On joining a venture capital firm: “The idea that I would do the thing I want to do for fun as my full-time job feels like I’ve won an ice cream eating competition, and the prize is more ice cream.” — Andrew

Companies and Products Mentioned in This Episode

Transcript

Ryan: Hey everybody, this is Ryan Hoover with Product Hunt Radio and I’m here at Andreessen Horowitz down in Menlo Park with two people I’ve known for a little while now, two brothers and sisters, Andrew Chen and Ada Chen. This is the first brother and sister duo and hopefully the first of many. Thanks for having me over here. First off, Andrew, you joined Andreessen Horowitz, is it six months ago?

Andrew: Yeah, I think I’m on month five. I’m quickly reaching my half year mark, which has gone incredibly fast.

Ryan: Are you completely swamped with meetings and pitches or how has it changed since before Andreessen Horowitz?

Andrew: Yeah, so when I was at Uber I really loved meeting with startups and hearing about new ideas and staying in touch with the tech community, but I can only do it first thing in the morning and on weekends and it quickly filled up my schedule. So I would work at Uber and then I would do that [meet with founders] basically. The idea that I would do the thing that I wanted to do for fun, like as my full time job sort of feels like I’ve won an ice cream eating competition and the prize is more ice cream. I could do as much as I want, which is super awesome.

Ryan: Yeah. And so your, your background, just maybe for those that aren’t super familiar, you were at Uber right before this and then what’s your short version of your history?

Andrew: Yeah, yeah, totally. We were just talking about. So Ada and I, who’s my little sister, by the way, I want to clarify —

Ada: [laughter, eye-rolling and protestation]

Andrew: So we grew up in Seattle, and we both made our way to the Bay Area. Actually, the funny thing is my first job ever was actually in venture capital and was something I did right after college. Then after that I ended up working at a series of startups, I moved to the Bay Area 10 years ago to start my own company. I had actually met Marc and Ben [of Andreesen Horowitz] here and they actually led the seed round for a startup I was working on during the Facebook platform days when everyone was working on crazy viral apps.

Ryan: So that’s around when we met.

Andrew: Yeah, right. Yeah, that’s exactly, that’s right around when we met and they invested out of a Horowitz Andreessen Angel Fund, which was really funny because that would have been like H16N and so different. So, I met them and I worked on that for a while and ended up basically deciding that it’d be better to go to a larger organization, ended up at Uber running various growth teams there. So I spent three years there, like a really, really fun experience —

Ryan: Probably pretty wild too, right?

Andrew: — Yeah, the first 18 months was like really, really incredible startup like hockey stick growth, then the last 18 months were very eventful and everyone’s read about it in the news. So I don’t have to summarize that.

Ryan: Yeah, and Ada, you’ve had a pretty interesting journey at Microsoft, LinkedIn, Survey Monkey, and then a two-person startup with your husband.

Ada: Yeah. Yeah. Actually multiple two person startups as well as, I spent some time in the game space as well at Mochi Media. So, after I graduated from college, I was in Seattle at Microsoft for a year and Microsoft at the time I think was around 80,000-100,000 employees? Very, very structured. Worked in the ad center space and the online advertising space when search marketing was just becoming a thing and exactly 367 days or so later, moved out to the Bay Area in 2007 and so worked at a tiny little startup that had just raised Series A called Mochi Media, which was an online games ad network, and spent multiple years there after it was ultimately acquired by Shanda Games and then actually started my first company which was a contact management app called Connected. It was all about contact management without the work. We raised some funding for that, ultimately sold it to LinkedIn and I had my experience sort of joining LinkedIn as a just as a company that was really maturing at the time. They had just had their IPO. There are about 1700 employees and experienced hyper growth for the first time, focused on things like relaunching Connected as LinkedIn Contacts, growth, learning a lot about subscriptions and consumer SaaS and was recruited out of that to work at Survey Monkey, where I was SVP of Marketing and then recently left a couple of years back to start a new company that’s actually a husband and wife team with Sachin Rekhi and we started a company called Notejoy, which is a collaborative notes app for teams and so we’re really focused on, how do we actually create a fast and focused workspace for teams that gets them out of the noise of chat and email.

Ryan: Yeah, team collaboration and productivity is so important because if you can even improve collaboration and efficiency within a team by like even just 10 percent, it can have such a huge impact on both your productivity but also just like your joy.

Ada: That was actually part of the inspiration behind the name and it’s one of those things where even when you go to a small team like small tight-fitting teams or larger organizations, you see this friction today that still exists when it comes to communication and collaboration and just think about how many decrepit out-of-date Wikis you see and Google Docs that are sort of lost in the ether and then people joining and getting forwarded random emails from way back when because that’s the only place that knowledge lives, we were really thinking about how do we create something that tackles that and productivity has always been a huge space where I’ve been passionate about.

Ryan: This is a really broad question, but what’s it like working at such a big company like LinkedIn and Microsoft and others to now just you and your husband?

Ada: Yeah, I mean it’s hugely different and I think the biggest dimension where I would say working at a large company versus a small startup is different is that effective execution looks completely different. It’s a night and day difference. So when you’re executing at a small startup or a small team or even just by yourself, it really comes down to ideating, picking and prioritizing and then rolling up your sleeves and getting things done as quickly as possible from an execution pace. When it comes to working at a large company, it’s actually much more cerebral, right? And it’s much more in the heart. You’re actually thinking about how do you communicate and collaborate across the cross functional group of teams to get the initiative done. So can you communicate what it’s about? Can you motivate people to get it done? Can you manage all of the pieces?

Ada: And the irony of it is that sometimes when you’re working on projects with large scale, because the skillset is so different, it actually feels like you’re not doing anything at all yourself. You’re actually merely managing the appendages of all the other groups and trying to make sure that everyone’s staying on track and executing. And so as organizations scale, the execution work around how much collaboration it takes gets orders of magnitude greater in terms of how hard it is to get everyone aligned and marching in the same direction versus one person. And so, I really think that that’s one of the biggest differences, like you go to a startup to learn how to do things and maybe not very well and you go to a large company to see how things are done really well, but across a broad range of disciplines and functions and really see how the whole thing comes together as an engine sort of humming smoothly and operating.

Ryan: You mentioned communication is one skill or trait of people in larger companies. And Andrew, you used to blog, I mean you still do, but you used to blog a lot. That’s largely how I think you built a pretty massive following over the past decade or so. How did you even get into writing to begin with?

Andrew: So, first I love writing. That’s kind of the very first thing, and I was always one of these, teenagers where like, I kept a journal and I would like write in it and then delete it and then start a new one and literally I was the only audience. I just like enjoyed it myself. And so before starting my current professional blog, I think I had like three other blogs that I had started over the years. Just basically, just getting going and then deleting them and not really sticking with it over time.

Ryan: Why did you delete the previous blogs?

Andrew: Because you get bored with it, and you’re just kinda like, okay, I’m done, kind of thing. And then like I think on those it was literally, it’s like who’s reading it? It’s like Ada, like my parents, like —

Ada: — Fun fact about Andrew’s early blogs: he would actually forcibly subscribe us to the emails to make sure that we wouldn’t miss anything.

Ryan: That was before some of the ICANN email laws and certainly before GDPR.

Andrew: Yeah, right. Yeah, exactly. So I think, don’t tell a 20 year old who they can subscribe to a blog or not. So I really enjoyed that. And then when I moved to the Bay Area 10 years ago, what I basically decided to do was I was like, I’m gonna write down everything that I’m learning and I’m just gonna start, like going out and so the funny thing, I was learning so much in my first year that I was just writing a lot of, like pretty random snippets, some of it would be like a paragraph or two, and I would do it like, maybe twice a week or something like that. So like pretty often and that’s actually how I met Marc Andreessen originally. It turned out that he somehow randomly had stumbled on my blog via Hacker News and then through that, had ended up seeing some of my content and then he cold emailed me and that’s how I met him in 2007. So it was like a pretty random and amazing adventure but at the time, I was an entrepreneur in residence. I was a 24 year old entrepreneur in residence actually across the street from here, which is really funny. And one of the things that my colleagues would tell me is they would say like, why are you wasting your time blogging, you’re giving away all your best ideas? Like, what are you doing? Like, these are the secrets that you’re going to use to understand the thing. And at the time I was like, well, I’m never going to be a venture capitalist so like it doesn’t matter. And so as a result, I’m just going to give away all this stuff and then, and it’s obviously so ironic now that like, so much of the job is, is obviously, sharing your ideas and giving back to the community via Twitter and Medium and writing, writing essays and all that.

Ryan: Now that’s the norm.

Andrew: Yeah, right, exactly. Yeah. And in fact it was like, it would have been considered very contrarian I think to actually share a bunch. But anyway, so I’ve kept it up and I think, I’m, I’m well into the many, many hundreds of essays, over 10 years and I think at times I’ve taken like a hiatus, I think I took a two year hiatus in the middle. But like I think my goal now is really to publish like regularly, but to do it at the kind of like a high level of quality and to go deeper into ideas and to sort of break new concepts and new kinds of data to the community versus literally the, the early days it was like, it’d be like 500 words, like what did I learn today kind of thing.

Ryan: So I’m going to take a tie into that a little bit. You mentioned a term called, correct me if I’m wrong, but something along the lines of mullet startups, is that correct? Or do you remember that there’s a tweet in a conversation with you and some others around the distributed nature of companies?

Andrew: Oh yeah, okay, mullet, yes.

Ryan: Mullet startups is a catchy term because it’s a trend that we’ve identified. Product Hunt is a mullet startup I guess, we’re headquartered in San Francisco, but we have a distributed team.

Andrew: So The Economist’s cover for this week is Peak Valley, is, is it over in Silicon Valley?

Ryan: Right.

Andrew: So then I think there’s been, there’s been a lot of like really interesting dialogue around that. I think, and obviously a lot of it has to do with like housing and the Bay Area and there’s so much to unpack there, right? But I think that one of the reactions to it has been that we see many companies, with their leadership and their executives in the Bay Area, but when it comes to hiring engineers and designers and all sorts of other folks, then they’re much more likely to distribute the team, anywhere.

Ryan: Right.

Andrew: And so, yeah, to your point, this is sort of the mullet, because it’s sort of business in the front and party in the back kind of thing. AndI think it’s fascinating because it is actually just the reverse of one of the models that we’ve seen over the years where, for example, you’ll have a really strong technical team out of Paris or out of Israel or out of Singapore and they’ll get started, they’ll get funded and then they’ll realize, okay, hey, all of our customers are in the US, let’s move the CEO and the sales and marketing function to the Bay Area. And so you end up with the, the mullet, but just like kind of, but now you do it in reverse. Right. So I think that’s like a pretty interesting, reverse mullet, which is kind of an interesting trend these days.

Ryan: Yeah. So it’s just you two right now Ada at Notejoy, but if you were to, let’s say you needed to hire 10 people tomorrow, how would you approach it? Would you hire in the Bay Area or would you go remote?

Ada: Yeah, I mean that’s actually a fascinating question because it’s something that we’ve debated and thought about because things have changed so much. Not only from the costs, but then also, what is the ability for you to access and interact with people at scale, if they’re located in other places. We actually talked to this close friend of mine who’s a founder who, built his company and scaled it to revenue, pretty substantial revenue in the Bay Area. And he basically said to us, if I were to do it again, I believe that Silicon Valley is the worst place to self-fund a company or to start a company or even to have funding and try to build a team. And the biggest challenge that he was having was actually access to talent. I think it would really depend. I think on one hand I think we have really strong networks within the Bay Area and so it would be possible to kind of peel people off and that’s really how many startups start with their founding team. They pull people that they respect, that they work with, that have shared belief in to kind of create that initial nucleus of a team and that gets you to your first couple of headcount. So maybe we can get to 10 that way, but I do think that now when it’s coming to scale, like yeah, we would definitely be looking very closely at could we build a remote team and create a really distributed workforce for Notejoy.

Andrew: I think one of the distinctions is do you hire a lot of folks who are doing the kind of individual contributor work versus the managers because I do think that it ends up being really hard once you want to find the engineering director that’s managed 200 engineers to find that elsewhere, versus it being, kind of a main thing. So, so there’s a really interesting thing about cities, right? Which is like if you graph the population of cities and sort of like, stack rank them, you’ll see that there’s a power law in it. And like the biggest cities are really, really, really big and then there’s this like there’s this long tail of all these like little tiny cities. And the reason for that is that there’s really like a network effect within cities, right? Like, whether it’s show business in LA or it’s, finance in New York, like these ecosystems that emerge happen because, you end up with the designers who are here because the engineers are here because the marketing people are here because the capital is here because and on and on and on and all in one place. And so one of my colleagues here at Andreessen Horowitz, Darcy, had mentioned, he tweeted the idea that, one of two things will happen, right? Either these network effects continue to hold, meaning that then, actually the Bay Area will just continue to be what it is, right? Or, we actually make really interesting structural shifts in how we organize teams and workforces and all that stuff. In which case the network effects become less strong. But what that means is not that then all of a sudden, some other city like becomes a quote unquote the next Silicon Valley. It actually just means that everyone just lives where they want to live and eat and that’s that. And so, so if you believe that thesis, then you’d actually say there is no quote unquote next Silicon Valley. It either just continues or it’ll just be distributed. Right. I think that’s like a pretty interesting —

Ada: — I think you see that already emerging even within online communities. So when you think about where the discourse actually taking place, right, it’s taking place on Medium, it’s taking place on Twitter, it’s taking place on Product Hunt. We went through the experience of launching on Product Hunt and we were really amazed by how international the community was in contrast to the..

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[Dear readers, this essay is on the future of marketplaces. Is there still room for marketplace startups to innovate? We answer, emphatically, yes! Am excited to share a vision on the past and future of the service economy, in a collaboration by my a16z colleague Li Jin. From “Unbundling Craiglist” to “Uber for X” – we lay it all out in a single framework. Hope you enjoy our thinking! -A]


Above: 4 eras of marketplaces focused on the service economy – and what’s next

Goods versus Services – why a breakthrough is coming
Marketplace startups have done incredibly well over the first few decades of the internet, reinventing the way we shop for goods, but have been less successful services. In this essay, we argue that a breakthrough is on its way: While the first phase of the internet has been about creating marketplaces for goods, the next phase will be about reinventing the service economy. Startups will build on the lessons and tactics to crack the toughest service industries – including regulated markets that have withstood digital transformation for decades. In doing this, the lives of 125 million Americans who work in the services-providing industries will join the digital transformation of the economy.

In the past twenty years, we’ve transformed the way people buy goods online, and in the process created Amazon, eBay, JD.com, Alibaba, and other e-commerce giants, accounting for trillions of dollars in market capitalization. The next era will do the same to the $9.7 trillion US consumer service economy, through discontinuous innovations in AI and automation, new marketplace paradigms, and overcoming regulatory capture.

In contrast, the service economy lags behind: while services make up 69% of national consumer spending, the Bureau of Economic Analysis estimated that just 7% of services were primarily digital, meaning they utilized internet to conduct transactions.

We propose that a new age of service marketplaces will emerge, driven by unlocking more complex services, including services that are regulated. In this essay, we’ll talk about:

  • Why services are still primarily offline
  • The history of service marketplace paradigms
    • The Listings Era
    • The Unbundled Craigslist Era
    • The “Uber for X” Era
    • The Managed Marketplace Era
  • The future of service marketplaces
    • Regulated services
    • Five strategies for unlocking supply in regulated markets
  • Future opportunities

Let’s start by looking at where the service economy is right now and why it’s resisted a full scale transformation by software.

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Software eating the service economy, but it’s been slow
We’ve all had the experience of asking friends for recommendations for a great service provider, whether it be a great childcare provider, doctor, or hair stylist. Why is that? Why aren’t we discovering and consuming these services in the same digital way we’ve come to expect for goods?

Despite the rise of services in the overall economy, there are a few reasons why services have lagged behind goods in terms of coming online:

  • Services are complex and diverse, making it challenging to capture relevant information in an online marketplace
  • Success and quality in services is subjective
  • Fragmentation – small service providers lack the tools or time to come online
  • Real-world interaction is at the heart of services delivery, which makes it hard to disaggregate parts of a purchase that might be done online

Let’s unpack each reason below:

First, on the complexity and diversity of services, services are performed by providers who vary widely, unlike goods which are manufactured to a certain spec. Even the names of services can vary: what one home cleaning service calls a “deep clean” can be different from another provider’s definition. This lack of standardization makes it difficult for a service marketplace to capture and organize the relevant information.

Second, services are often complex interactions without a clear yardstick of success or quality. The customer experience of a service is often subjective, making traditional marketplace features like reviews, recommendations, and personalization more difficult to implement. Sometimes just getting the job completed (as in rideshare) is sufficient to earn a 5-star review, whereas other higher-stakes services, like childcare, have complex customer value functions, including safety, friendliness, communicativeness, rapport with child, and other subjective measures of success.

Third, small service providers often lack the tools or time to come online. In many service industries, providers are small business owners with low margins; contrast this with goods manufacturing where there are economies of scale in production, and thus consolidation into large consumer products companies. As a result of industry fragmentation, service providers often don’t have time or budget to devote to key business functions, such as responding to customer requests, promoting and marketing themselves, maintaining a website, and other core functions. While major e-commerce platforms have taken on the role of distribution, merchandising, and fulfilling orders for goods, there are few platforms that service providers can plug into to manage their businesses and reach customers.

Fourth, real-world interaction is central to services, which can pull other steps of the services funnel into the offline world as well. Many services are produced and consumed simultaneously in real-world interactions, whereas goods entail independent stages of production, distribution, and consumption. The various stages of the goods value chain can be easily unbundled, with e-commerce marketplaces comprising the discovery, transaction, and fulfillment steps. Conversely, since the production and consumption of services usually occur simultaneously offline, the discovery, distribution, and transaction pieces are also often integrated into the offline experience. For instance, since getting a haircut entails going to a salon and having interactions with the providers there, the stages of the value chain that precede and follow that interaction (discovery, booking, and payment) also often get incorporated into the in-person experience.

All of these factors make it very hard for services to come online as comprehensively and widely as commerce – but there’s hope. We’ve seen multiple eras of bringing the service economy online, and we’re on the verge of a breakthrough!

The 4 eras of Service Marketplaces, and what’s next 
There have been 4 major generations of service marketplaces, but coverage of services and providers remains spotty, and many don’t provide end-to-end, seamless consumer experiences. Let’s zoom out and talk through each historical marketplace paradigm, and what we’ve learned so far.

Above, you can see that there have roughly been four major eras of marketplace innovation when it comes to the service economy.

1. The Listings Era (1990s)
The first iteration of bringing services online involved unmanaged horizontal marketplaces, essentially listing platforms that helped demand search for supply and vice versa. These marketplaces were the digital version of the Yellow Pages, enabling visibility into which service providers existed, but placing the onus on the user to assess providers, contact them, arrange times to meet, and transact. The dynamic here is “caveat emptor”–users assume the responsibility of vetting their counterparties and establishing trust, and there’s little in the way of platform standards, protections, or guarantees.

Craigslist’s Services category is the archetypal unmanaged service marketplace. It includes a jumble of house remodeling, painting, carpet cleaners, wedding photographers, and other services. But limited tech functionality means that it feels disorganized and hard to navigate, and there’s no way to transact or contact the provider without moving off the platform.

We’ve all had the experience of a listings-oriented product, like Craigslist. You find something you want, but everything else – trust/reviews/payments/etc – that’s all up to you!

2. The Unbundled Craigslist Era (2000s)
Companies iterated on the horizontal marketplace model by focusing on a specific sub-vertical, enabling them to offer features tailored to a specific industry. We’ve all seen the diagram of various companies picking off Craigslist verticals – it looks something like this:

As a reaction to the “Wild West” nature of Craigslist, to improve the customer experience, each startup would create value-add via software. For instance, Care.com carves off the Childcare section of Craigslist, and provides tech value-add in the form of filters, structured information, and other features to improve the customer experience of finding a local caregiver. It’s a huge leap in terms of user experience over Craigslist’s Childcare section.

Angie’s List, a home services site founded in 2005, carves off Craigslist’s household services category. The platform has features including reviews, profiles, certified providers, and an online quote submission process. But the marketplace doesn’t encompass the entire end-to-end experience: users turn to Angie’s List for discovery, but still need to message or call providers and coordinate offline.

Unmanaged vertical marketplaces like Angie’s List go a step beyond Craigslist and take on some value-add services like certifying providers when they meet certain standards, but customers still need to select and contact the service provider, place their trust in the provider rather than the platform, and transact offline.

Like previous listing sites, these platforms in this era try to use the ‘wisdom of the crowds’ to promote trust. These platforms have a network effect in that more reviews means more users and more reviews. But user reviews have their limitations, as every user has a unique value function that they’re judging a service against. Without standardized moderation or curation, and without machine learning to automate this process, customers have the onus of sifting through countless reviews and selecting among thousands of providers.

3. The “Uber for X” Era (2009-)
In the early 2010s, a wave of on-demand marketplaces for simple services arose, including transportation, food delivery, and valet parking. These marketplaces were enabled by widespread mobile adoption, making it possible to book a service or accept a job with the tap of a button.

Companies like Handy, Lugg, Lyft, Rinse, Uber and many others made it efficient to connect to service providers in real-time. They created a full-stack experience around a particular service, optimizing for liquidity in one category. For these transactions, quality and success were more or less binary–either the service was fulfilled or it wasn’t–making them conducive to an on-demand model.

These platforms took on various functions to establish an end-to-end, seamless user experience: automatically matching supply and demand, setting prices, handling transactions, and establishing trust through guarantees and protections. They also often commoditized the underlying service provider (for instance, widespread variance on the driver side of rideshare marketplaces is distilled into Uber X, Uber Pool, Uber Black, Uber XL, etc.).

Unlike the previous generations of marketplaces, in which the provider ultimately owns the end customer relationship, these on-demand marketplaces became thought of as the service provider, e.g. “I ordered food from DoorDash” or “Let’s Uber there,” rather than the underlying person or business that actually rendered the service.

Over time, many startups in this category failed, and the ones that survived did so by focusing on and nailing a frequent use case, offering compelling value propositions to demand and supply (potentially removing the on-demand component, which wasn’t valuable for some services), and putting in place incentives and structures to promote liquidity, trust, safety, and reliability.

4. The Managed Marketplace Era (Mid-2010s)
In the last few years, we’ve seen a rise in the number of full-stack or managed marketplaces, or marketplaces that take on additional operational value-add in terms of intermediating the service delivery. While “Uber for X” models were well-suited to simple services, managed marketplaces evolved to better tackle services that were more complex, higher priced, and that required greater trust.

Managed marketplaces take on additional work of actually influencing or managing the service experience, and in doing so, create a step-function improvement in the customer experience. Rather than just enabling customers to discover and build trust with the end provider, these marketplaces take on the work of actually creating trust.

In the a16z portfolio, Honor is building a managed marketplace for in-home care, and interviews and screens every care professional before they are onboarded and provides new customers with a Care Advisor to design a personalized care plan. Opendoor is a managed marketplace that creates a radically different experience for buying and selling a home. When a customer wants to sell their home, Opendoor actually buys the home, performs maintenance, markets the home, and finds the next buyer. Contrast this with the traditional experience of selling a home, where there is the hassle of repairs, listing, showings, and potentially months of uncertainty.

Managed marketplaces like Honor and Opendoor take on steps of the value chain that platforms traditionally left to customers or providers, such as vetting supply. Customers place their trust in the platform, rather than the counterparty of the transaction. To compensate for heavier operational costs, it’s common for managed marketplaces to actually dictate pricing for services and charge a higher take rate than less-managed marketplace models.

Managed marketplaces are a tactic to solve a broader problem around accessing high-quality supply, especially for services that require greater trust and/or entail high transaction value. If we zoom out further, there’s many more categories of services that can benefit from managed models and other tactics to unlock supply.

What’s next: The future of Service Marketplaces (2018-?)
We think the next era of service marketplaces have potential to unlock a huge swath of the 125 million service jobs in the US. These marketplaces will tackle the opportunities that have eluded previous eras of service marketplaces, and will bring the most difficult services categories online–in particular, services that are regulated. Regulated services–in which suppliers are licensed by a government agency or certified by a professional or industry organization–include engineering, accounting, teaching, law, and other professions that impact many people’s lives directly to a large degree. In 2015, 26% of employed people had a certification or license.

Regulation of services was critical pre-internet, since it served to signify a certain level of skill or knowledge required to perform a job. But digital platforms mitigate the need for licensing by exposing relevant information about providers and by establishing trust through reviews, managed models, guarantees, platform requirements, and other mechanisms. For instance, most of us were taught since childhood never to get into cars with strangers; with Lyft and Uber, consumers are comfortable doing exactly that, millions of times per day, as a direct result of the trust those platforms have built.

Licensing of service professions create an important standard, but also severely constrains supply. The time and money associated with getting licensed or certified can lock out otherwise qualified suppliers (for instance, some states require a license to braid hair or to be a florist), and often translates into higher fees, long waitlists, and difficulty accessing the service. The criteria involved in getting licensed also do not always map to what consumers actually value, and can hinder the discovery and access of otherwise suitable supply.

Above: Bureau of Labor Statistics. (11/9/18)

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Five strategies to unlock regulated industries
We’re starting to see a number of startups tackling regulated services industries. As with each wave of previous service marketplaces, these new approaches bring more value-add to unlock the market, with variations in models that are well-suited to different categories.

The major approaches in unlocking supply in these regulated industries include:

  1. Making discovery of licensed providers easier
  2. Hiring and managing existing providers to maintain quality
  3. Expanding or augmenting the licensed supply pool
  4. Utilizing unlicensed supply
  5. Automation and AI

1) Making discovery of licensed providers easier
Some startups are tackling verticals that lack good discovery of licensed providers. Examples include Houzz, which enables users to search for and contact licensed home improvement professionals, and StyleSeat, which helps users find and book beauty appointments with licensed cosmetologists.

2) Hiring and managing existing providers to maintain..

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