Revolution or Evolution – Did Apple give us a post-mobile future this week?

tl;dr Context for WWDC - the big tech players want to own your user experience and the evolution of the browser. Heading into WWDC this week I’m eager to hear Apple’s vision for the future of mobile.  We’ve come a long way since the advent of the smartphone which moved us beyond the web page, browser, mouse and keyboard. The iPhone opened up an entirely new technology and business model but it has reached a saturation point. Benedict Evans and Mary Meeker highlight this slowing growth. The industry needs to evolve. Smartphones are on a replacement curve, not an adoption curve. This has enormous implications for the big tech players and the startups we invest in. Discovery and engagement on mobile is harder than ever. Distribution and retention is tough. People don’t engage with new apps. The average user downloads zero apps per month. SurveyMonkey uses their panel data to Continue reading "Revolution or Evolution – Did Apple give us a post-mobile future this week?"

Gboard — Google’s brilliant strategy to leapfrog Apple, Facebook and iOS messengers

Google’s new iOS keyboard seeks to own the key mobile use case — messaging.

gboard Last week, Google launched the Gboard to stellar reviews. It’s a 3rd party iOS keyboard that allows for searching and sharing in context on the phone. It’s a brilliant strategy for ensuring that Google is central for information discovery. It has the potential to be more strategic than the default search deals Google has previously struck with iOS Spotlight and Safari. To top it off, after nearly a week of playing with it, I love it. It’s a strong keyboard and has a slew of delightful features like emoji autocorrect [search pizza], predictive searches [text want to get a drink tonight], and of course the core search and share card metaphors. Up until now, first class keyboards that have done well on Android have had a hard time replacing the primary keyboard on iOS. It’s not an easy Continue reading "Gboard — Google’s brilliant strategy to leapfrog Apple, Facebook and iOS messengers"

Seed Startups – Business Model Experiments

tl;dr Seed startups are business model experiments and should apply the scientific method.

In 2011, my co-founder and I set out to build PrimaTable. Our vision was to bring yield management to local businesses. Our belief was that mobile technology had the potential to unlock local inventory, providing value to both consumers and small businesses. Revenue management techniques, previously seen in travel and ads, would now be possible. While PrimaTable didn’t become a stand alone business, it was a successful seed. We rapidly tested our assumptions for the business and market. We iterated through a series of products and models. There were a handful of testable hypotheses wrapped up into our vision. Our seed round was used to test these hypotheses, mitigating risk, as fast as possible. As a startup, we sought rapid growth and were predicated on the belief that smartphones represented a market dislocation that newly enabled Continue reading "Seed Startups – Business Model Experiments"

Seed Startups – Business Model Experiments

tl;dr Seed startups are business model experiments and should apply the scientific method.

In 2011, my co-founder and I set out to build PrimaTable. Our vision was to bring yield management to local businesses. Our belief was that mobile technology had the potential to unlock local inventory, providing value to both consumers and small businesses. Revenue management techniques, previously seen in travel and ads, would now be possible. While PrimaTable didn’t become a stand alone business, it was a successful seed. We rapidly tested our assumptions for the business and market. We iterated through a series of products and models.

There were a handful of testable hypotheses wrapped up into our vision. Our seed round was used to test these hypotheses, mitigating risk, as fast as possible. As a startup, we sought rapid growth and were predicated on the belief that smartphones represented a market dislocation that newly enabled Continue reading "Seed Startups – Business Model Experiments"

The Booking.com Marketplace Playbook

tl;dr Marketplaces extract value when they generate demand. The Booking.com low rake plus bidded auction model is the playbook modern marketplaces should follow.

Background

People know Booking.com as a behemoth in the travel industry but it wasn’t always the case. Priceline’s purchase of Booking.com in 2005 looks brilliant with Booking.com driving > 2/3 of PCLN’s revenue and accounting for a large portion of their $60B market cap.

Booking.com path to success is a fascinating story (see How Booking.com Conquered the World). It was started in 1996 with a revolutionary new agency model as an OTA. The agency model is much lower friction vs the previous standard merchant model driving Expedia and Travelocity’s success. Booking.com lowered the reserve rake from 25-30% to 12% and innovated on a more favorable cash flow for suppliers. This low friction model allowed Booking.com to acquire nearly Continue reading "The Booking.com Marketplace Playbook"

Dream On-Demand Marketplace

Here is an example presentation for an on demand marketplace.

Prior to the presentation introduce the founders. You want to build ethos with the audience. Highlight relevant experience to build credibility.

The goal of the pitch is draw an investor in further. You want to establish a large problem that your team is uniquely suited to fix.

  1. Intro

    This is the highest level what does your company do.

  2. Problem

    What is the problem and why does it exist?

  3. Solution

    What is your value proposition - how do you solve this problem faster, cheaper, better. Show is better than tell. Demo!

  4. Market

    How big is this problem? Is this market well suited to a new marketplace? Convey an overwhelming sense of your knowledge of the intricacies of your market.

  5. Unit Economics

    The business model. A marketplace lives and dies on this slide.

  6. Traction

    Show progress and momentum. Up and to the right!

  7. Go To Market

    You’ve established this is a big market and a real problem but how scalable is your solution?

  8. Competition

    Competition can validate a market. Demonstrate your unique value proposition.

  9. Team

    Highlight founders’ background and experience. Why are you uniquely suited to succeed here?

  10. Ask

    Summarize existing financing and investors, how much you are looking for and what will you accomplish with this capital.

  11. Appendix.

    The best pitches anticipate questions that an investor leaning in might have. The two I always care about are:

    1. Greater detail on the product and tech
    2. Customer cohort data

Code and Data

Here is a R script for simulating a simple marketplace and generating these graphs.

Dream On-Demand Marketplace

Here is an example presentation for an on demand marketplace.

Prior to the presentation introduce the founders. You want to build ethos with the audience. Highlight relevant experience to build credibility.

The goal of the pitch is draw an investor in further. You want to establish a large problem that your team is uniquely suited to fix.

  1. Intro

    This is the highest level what does your company do.

  2. Problem

    What is the problem and why does it exist?

  3. Solution

    What is your value proposition - how do you solve this problem faster, cheaper, better. Show is better than tell. Demo!

  4. Market

    How big is this problem? Is this market well suited to a new marketplace? Convey an overwhelming sense of your knowledge of the intricacies of your market.

  5. Unit Economics

    The business model. A marketplace lives and dies on this slide.

  6. Traction

    Show progress and momentum. Up and to the Continue reading "Dream On-Demand Marketplace"

Startup Risk and Valuation

tl;dr Startup risk allows for the potential for reward. Valuation only increases on mitigation of risk.

“Out of clutter, find simplicity. From discord, find harmony. In the middle of difficulty lies opportunity.”

Albert Einstein

Startup are valued based on the overall market opportunity discounted by the risk associated with achieving a successful outcome. Therefore, valuation increases as the market increases or as risk is mitigated.

Successful companies level up. The team, product, business and process improve. The common successful venture backed path can look like a series of risks that are mitigated.

Stages:

  1. Seed - product market fit
  2. Series A - build team and business
  3. Series B - scale the business
  4. Series C - profitability
  5. IPO - liquidity

These phases are made up of a variety of risks that vary across companies and markets.

Let’s take a look at risks that exist, examples where the risk determined an outcome and the questions VCs ask.

Risks:

  • Execution / team risk - Google Video vs. YouTube - the incumbent with the benefit of vastly superior resources fell to better execution. Is this team uniquely able to execute on the opportunity?
  • Technology risk - OnLive. ultimately failed due to the inability to create a desktop visualization technology with low enough latency. Can the right product be built?
  • Business model risk - WebVan in 1999, Exec recently. At scale, will the unit economics support the proposed business?
  • Financing risk - Everpix and Canvas. How much capital is required to get to a positive outcome? Will this be a category that can easily find follow on capital?
  • Market timing risk - Friendster vs. Facebook. Too early and too late is just as bad as being wrong. Why now?
  • Market adoption risk - Plancast. Will the market resonate with the product? Will the company suffer from a lack of product market fit, startup competition, or strong incumbents?
  • Market size risk - Mochi Media. Is the market large enough to sustain growth and have a material impact on the fund?
  • Scalability risk - Sonar. Growth is the only thing that matters. For enterprise is there a repeatable sales process, for consumer are there distribution channels with sufficient volume to create a big business?
  • Legal risk - Aereo and Outbox. Are there IP, copyright, or other legal risks that have a material impact on the business?

Fund Raising on Risk Mitigation:

I’ve often had friends ask when to raise their first round of financing. The answer depends on the level of risk associated with the project. In many cases, former engineers and product managers with strong track records of building and shipping successful products do not need to build a MVP to generate investment interest. For Continue reading "Startup Risk and Valuation"

OpenTable – Opportunity

When I co-founded PrimaTable, a restaurant marketplace startup, I had prior experience within Google’s Adwords and YouTube’s media marketplace. Taking the plunge, I tried to systematically learn about marketplaces from as many public company as possible. Unfortunately, many marketplace companies don’t report on the essential operational metrics (unit economics, CAC, LTV, liquidity, geographic density …) and require crude assumptions to decompose their performance. OpenTable was my closest comparable and reports nearly a complete set of supply side unit economics going back to 2006. Let’s take a look at their business.

History

Founded in 1998, OpenTable is a two-sided local marketplace connecting diners with restaurants. OpenTable started as a restaurant electronic reservation book (ERB). To grow their marketplace, OpenTable focused on single side utility, adding value to restaurants focused on customer service with a CRM and table management system. OpenTable focused on liquidity in a local geography prior to broader expansion. After the aggregation of a comprehensive list of restaurants in a metropolitan area, OpenTable.com provides value to consumers by facilitating the discovery of reservation availability.

Acquired by Priceline in July of 2014 for $2.6B, OpenTable takes reservations currently has over 32K restaurants internationally and has seated over 665 million dinners.

In this post, I’ll dig into OpenTable’s business with a focus on opportunities Priceline can capture. Priceline has stated a focus on three strategic areas (SAs) post-acquisition:

  1. International expansion
  2. Demand generation
  3. Marketplace innovation, especially in mobile

OpenTable’s business model is very similar to Priceline’s, in demand generation, supply aggregation and operational needs. Like hotels and airlines in the travel industry, restaurants have a high fixed cost and low variable cost (35%). To maximize profit, restaurants want to be at 100% occupancy and have significant margin to spend to acquire customers. Unlike Priceline, OpenTable has a much more frequent but lower margin and volume transaction.

Stage

OpenTable has grown to nearly $200M in revenue. The fastest growing portion of their revenue is reservation performance marketing product. SA #2 post-acquisition will be to focus on the marketing products further increasing the growth within performance marketing.

Revenue by Type.

Network effects

The beauty of marketplace businesses is - at liquidity there are strong network effects. Year over year growth in diners has consistently outpaced that of restaurants (outside of the Top Table acquisition in 2010). This is due to the increased value that each incremental user of OpenTable has due to the comprehensive coverage of supply. As OpenTable focuses on SA #3 marketplace innovation, expect revenue growth to begin to outpace even diner growth. OpenTable can offer additional value to both consumers and restaurants by creating a more efficient market.

Year over Year Growth.

Unit Economics

Restaurant Acquisition

Continue reading "OpenTable – Opportunity"

Oh, The Places You’ll Go!

“You have brains in your head. You have feet in your shoes. You can steer yourself any direction you choose. You’re on your own. And you know what you know. And YOU are the one who’ll decide where to go…”

Dr. Seuss, Oh, The Places You’ll Go!

My son was born a month ago. It has been one of the most amazing experiences, nothing short of miraculous. One night while soothing him back to sleep, I reflected on how different a world he will face when he starts his family. The amount of innovation that has happened over the course of my lifetime is staggering. The cumulative nature of discovery, each invention building upon a growing base of knowledge, dictates that this innovation only continues to accelerate. From our seat in Silicon Valley, acceleration is readily apparent.

In the last 30 years, we’ve seen the mass adoption of personal computers, a global internet, and smartphones. Long the domain of only science fiction, technologies like 3d printing, virtual reality, connected devices, quantified self, consumer robotics, and self-driving cars are on the immediate horizon. A series of simultaneous parallel inventions served to create the modern information technology economy. Exponential growth of compute power (Moore’s law), storage capacity (Kryder’s law), and data transmission (Butters’ and Nielsen’s have driven unfathomable hardware advancement. The lasting effect of these inventions is still playing out.

Previous leaps in efficiency during the Industrial Revolution centered around augmenting physical processes and were limited by fuel and mechanical innovation. More so than anytime before, the technical innovation today serves to enable further innovation (whether explicitly with computer aided design, or implicitly changing how we learn). Information technology augments mental processes and allows the transformation of every facet of our world.

As a huge fan of science fiction I recognize I’m no Hari Seldon. Here are some thoughts about what the next 10 years may bring, looking at startups founded today.

Information Revolution

Information is being digitized, organized and made universally accessible. To quote the film Serenity, “You can’t stop the signal, Mal.” With the rise of connected devices and cheap sensors, data is increasing exponentially. Anything that can, will be quantified. Once quantified, it will be analyzed and understood. Put another way, every physical thing will become smart. Everything will be connected, measured and responsive.

The information revolution that is currently happening in this rapid digitization is what powers much of the modern innovation. As Google Research Director Peter Norvig says, the combination of rapidly increasing data and new methods to process this data means new and better models yielding increased information, relevance and personalization. Already, services are moving from comprehensiveness (10 Continue reading "Oh, The Places You’ll Go!"

I, for one, embrace our new robot overlords

tl;dr Technology creates efficiency and leverage. The rise in automation serves to empower the workforce just as machinery, electricity, and computing did previously.

At a wedding reception dinner recently, I engaged in a fascinating conversation with a good friend. The conversation was spurred by the report that Uber will replace drivers with self-driving cars. The debate was whether the self-driving cars will destroy taxi driver jobs. Here is the gist of my argument.

Recall that Luddites were first born in the Industrial Revolution’s as “textile artisans who protested against newly developed labour-saving machinery”. The Second Machine Age: Work, Progress, and Prosperity in a Time of Brilliant Technologies, written by Erik Brynjolfsson an MIT economist, paints an interesting perspective for modern Luddites. Technology universally improves economic standard of living. The net effect can be difficult to understand, as the first order will be an automation of manual jobs.

Brynjolfsson argues that the key to growth and prosperity is to “race with the machines”. He presents many examples where continued progress with digital technologies fundamentally improves society. Technology creates wealth in the way Paul Graham defines it - “stuff we want: food, clothes, houses, cars, gadgets, travel to interesting places, and so on.”

But like the Industrial Revolution, which took generations to improve the steam engine, it will take time for industry to embrace new digital technology. Remember Time magazine declared the personal computer its “Machine of the Year” in 1982. For anyone interested, Professor Brynjolfsson’s TED Talk, The key to growth? Race with the machines is a provocative response to Robert Gordon’s The Death of Innovation and the end of Growth.

In Kevin Kelly’s 2012 Wired article, Better than Human: Why Robots Will - And Must - Take Our Jobs, highlighted the same premise. Embracing the technological changes and leveraging new abilities will create unimagined jobs much in the same way the Industrial Revolution transformed society.

Similarly, Marc Andreessen recently had a flurry of “robots eat the jobs” tweetstorms. His argument, as Milton Friedman, human wants and needs are infinite - driving ever increasing demand, automation and technology leverage is fundamentally good - driving costs down for everyone, and finally humans will always be able to do things that technology cant.

Technology creates efficiency and leverage. Just as a loom enabled a textile worker to create higher quality goods, faster, modern technology platforms create leverage for individuals. Open source technology, public cloud infrastructure like AWS, established distribution channels like app stores, web search and ad networks enable a small team of engineers to create new companies for increasingly less capital. Automated technology will continue to serve as a force for greater efficiency and leverage whether it is Amazon’s Continue reading "I, for one, embrace our new robot overlords"

Deep Links – Mobile Acquisition Unlocked

tl;dr Deep links provide the ability for apps to better address discovery and engagement

I was lucky to share a panel with John Milinovich CEO of URX and Itamar Weisbrod CEO of Deeplinks.me at the grow.co’s Mobile Acquisition Unlocked conference yesterday. Here is a quick look at my view of the panel.

John had a great framework for describing the stages of deep linking.

  1. enablement - engineering your app to respond to the correct routes.
  2. publishing routes - allowing for an interconnected web of apps.
  3. use cases - utilizing deep links, first in existing marketing channels (email, push, re-engagement …)

Deep links (either one of Charles Hudson’s 3 ways deep linking could play out) are an enabling technology. I’m not overly concerned about the specific implementation. I hope that iOS 8 and Apple’s recent interactive notifications, app extensions and widgets herald a more open app to app interaction.

The use cases for deep linking are many and varied. Marketer 101: more targeted, specific messages with simpler transactions yield higher ROI campaigns. This is true in emails, push notifications, shared links, ads and beyond. Can you imagine if while searching for [deep linking] on Google you were taken to wikipedia.org and not directly to the content? Deep links are a step in the right direction.

Taking a product centric view to user acquisition, great UX, inherent viral channels, platform distribution, referral programs, and drip marketing often have a higher leverage effect on a user base than pure paid marketing. Deep links can improve nearly every aspect of an apps growth strategy.

My main takeaways from the overall MAU conf are 1) Facebook is still the best and largest scale mobile acquisition channel. While marketers are excited about Twitter, YouTube, native ads and a series of vendors, FB remains the de facto leader in both installs and re engagement. Which brings us to 2) 2014 is the year of re-engagement. Marketers repeatedly highlight vendors like TapCommerce, ActionX and Kahuna as new high ROI channels.

It is still clear mobile discovery and engagement are still fundamentally broken (as I’ve previously written about). Deep links provide the low level infrastructure to allow companies to begin to address discovery and engagement.

Willful Delusion – Startups and the Stockdale Paradox

tl;dr Willful delusion - rational optimism is necessary for startups.

Early when I was starting PrimaTable, a friend and mentor told me about the Stockdale Paradox. Described in Jim Collin’s Good to Great, the paradox is named after Vice Admiral Jim Stockdale, an American naval officer held captive for eight years in the Vietnam War.

Stockdale’s Paradox

When asked about about how he coped with captivity and regular torture, Admiral Stockdale responded:

“I never lost faith in the end of the story, I never doubted not only that I would get out, but also that I would prevail in the end and turn the experience into the defining event of my life, which, in retrospect, I would not trade.”

When asked who didn’t make it home from Vietnam, Stockdale replied:

“Oh, that’s easy, the optimists. Oh, they were the ones who said, ‘We’re going to be out by Christmas.’ And Christmas would come, and Christmas would go. Then they’d say, ‘We’re going to be out by Easter.’ And Easter would come, and Easter would go. And then Thanksgiving, and then it would be Christmas again. And they died of a broken heart.”

Collin’s coined the Stockdale paradox as Stockdale’s summary:

“You must never confuse faith that you will prevail in the end — which you can never afford to lose — with the discipline to confront the most brutal facts of your current reality, whatever they might be.”

Startups

Creating a new product is hard, creating a new company is even harder. There are countless reasons why any given company doesn’t exist. Startup growth is a process of managing and mitigating risk.

In order to make the leap from Peter Thiel’s Zero to One, a founder must believe the technology is different, the market is different, her team is different, the business model is different and so on. This belief has been called a Reality Distortion Field but without balancing the ability to confront the brutal facts a startup often faces can lead a founder astray. Weathering the difficult challenges of a startup, requires the ability to see and navigate issues or Tom Tunguz’s Ruthlessness and Grit.

Like Stockdale’s paradox, starting a company and surviving requires a willful delusion. Delusion supporting optimism in face of that risk. Willfulness allows the management of risk through rational assessment. While a founder needs to be a rational, convincing and brilliant operator, at the same time, she must ignore the mountain of evidence that this company shouldn’t exist.

The present and future of video

tl;dr Consumption will be digital and mobile. Industry has to adapt to business models that support this change.

Today, TV is changing radically down to what the word even means. This week in the US, the FCC is voting on net neutrality rules affecting the future of digital video. At the same time, the medium is changing in short form, changing windows, and the rise of mobility.

Wired

Consumption of media is changing. The average American adult spends 11 hours per day with electronic media. The top two forms are still TV and radio.

In What Does ‘Watching TV’ Even Mean?, Katherine Rosman writes:

We spend a full five hours and 16 minutes a day in front of a screen, and that’s without even turning on a television. Adults are watching their televisions slightly less—with a daily intake of four hours and 31 minutes this year, seven minutes less than in 2012.

The traditional subscribers of TV through cable, satellite and fiber fell by 250K in 2013 as reported by Bloomberg.

Looking at TV ad spending slowing growth, Peter Kafka asks Peak TV? (emphasis question mark)

Ad spending on TV in the US grew only 3% last year. The average price of a 30-second ad is down 12% since 2009. Channels have responded by running more ads (14:15 per hour on broadcast TV and 15:38 on cable).

There is a limit to how many ads a channel can stuff in.

While the average American household now now gets 189 cable TV channels, they watch only 17.

In response to this change in consumption, the business of video is changing. Existing cable networks have seen dramatic consolidation as evidences by this fantastic WSJ graphic.

Video Consolidation.

Digital Video

Digital video is the disruption that has been a long time coming. Here are a couple of ways to look at it.

High level, digital media in aggregate now has overtaken TV. Digital video is still a fraction of time spent and ad spend is proportionately less although digital is growing dramatically faster. For digital video, it is still early, Nielsen reports the daily average time spent as 5 hrs and 4 min on TV relative to 13 min on desktop video or 11 min on smart phone video.1

For ad dollars, digital video is a small fraction at $4B growing 40% yoy vs $66B on TV. This is complicated by worries about the effectiveness of the format with reports that up to half of video ads are not viewed.

In terms of time spent, digital media (total internet usage) broadly over took TV in 2013 with 43% of time spent vs 37% on TV.

The big four:

Netflix is the Continue reading "The present and future of video"

The present and future of video

tl;dr Consumption will be digital and mobile. Industry has to adapt to business models that support this change.

Today, TV is changing radically down to what the word even means. This week in the US, the FCC is voting on net neutrality rules affecting the future of digital video. At the same time, the medium is changing in short form, changing windows, and the rise of mobility.

Wired

Consumption of media is changing. The average American adult spends 11 hours per day with electronic media. The top two forms are still TV and radio.

In What Does ‘Watching TV’ Even Mean?, Katherine Rosman writes:

We spend a full five hours and 16 minutes a day in front of a screen, and that’s without even turning on a television. Adults are watching their televisions slightly less—with a daily intake of four hours and 31 minutes this year, seven minutes less

Continue reading "The present and future of video"

Beyond The App Store – Mobile Discovery and Interaction

tl;dr The next phase in mobile search and interaction is contextual deep discovery.

Mobile discovery and interaction is still in a nascent state. Facebook’s announcement of Applinks at their F8 Event and URX’s Omnilink last week sparked a ranging conversation about what both UX and technology might look like.

Mobile discovery is entering a new phase beyond just app discovery to more general engagement. As Benedict Evans has repeatedly argued, the interaction model hasn’t been established for mobile.

[O]n mobile the internet is in a pre-Pagerank phase, lacking the ‘one good’ discovery mechanism that the desktop web had, but it’s also in a pre-Netscape phase, lacking one interaction model in the way that the web dominated the desktop internet for the last 20 years. Of course that doesn’t mean there’ll be one, but right now everything is wide open.

This next evolution of mobile discovery and interaction requires deep hooks into the mobile OS. As a result, Android as a more open platform seems to be leading the way. By allowing for advanced customization of home and lock screens, advanced context passing in Android Intents, and more generally additional app store ecosystems.

Let’s consider the evolution of the ecosystem.

Phase Zero - App Stores

In July 2008, Apple launched the first version of the iOS app store with just 500 apps. This app store was little more than a keyword search on structured meta data (title, description) provided by app developers. Quickly, the categorized top app lists drove engagement. This drove a rise in CPI based, incentive ad networks to propel apps up the charts. Admob (acquired by Google for $750M) and Tapjoy were the early players.

Phase One - application discovery

Chomp - search algorithm improvement

The first phase of the evolution of this interaction and discovery model on top of the core mobile OS started with better search on App Stores by companies like Chomp (acquired by Apple), and Quixey (raised $75M from USVP, GGV, Alibaba). Chomp launched in January 2009, when the iOS app store had grown to > 15,000 apps and already top 20 lists were not sufficient for app discovery. By the time Apple acquired Chomp to improve its search algorithms in February 2012, the number of apps had grown to >500,000.

Phase Two - contextual application discovery

Launchers and Lock / Home Screens - app organization and at a glance discovery

With both Android and iOS currently having >1M apps in their app stores, app discovery and engagement is broken. Cover (acquired by Twitter), Aviate (acquired by Yahoo) and 100s more launchers and smart screens organize and contextual prompt app usage. These apps are subject Continue reading "Beyond The App Store – Mobile Discovery and Interaction"

Recent VC spending peak reflects new pre-IPO rounds

tl;dr Venture financing hit a recent quarterly peak Q1 2014. This peak is due to a handful of late stage deals in a new pre-IPO environment.

With the release of the NVCA / PriceWaterhouse Cooper MoneyTree report last week, a lot has been written about the state of venture financing.

The focus of the response has been on the top line reported. “Venture capitalists invested $9.5 billion in 951 deals in the first quarter of 2014.” The comparisons drawn have been to past bubbles.

A level deeper, the MoneyTree press release goes on to recognize that this growth didn’t come necessarily across the board. Software is leading the way from a sector perspective. More interestingly, according to the MoneyTree report data, the gains were from expansion and later stage deals. But by their nature, and the nature of the MoneyTree survey, early stage deals are underreported.

To dig into this trends, we can look directly at public crunchbase data.

The Numbers

Amount Raised by Stage and Quarter.

Decomposing the total amount raised demonstrates an increasing trend across stage. The huge increase in the quarterly amount raised is driven by companies having raised a series-C or greater. The last quarter series-C+ dramatically increased beyond their trend.

Companies Funded by Stage and Quarter.

The number of companies that raised by quarter has very different trends by stage. Angel and seed deals grew dramatically from 2010 through 2013 but actually decreased in the first quarter of 2014. Anecdotally, I suspect this is due to a lag in the reporting of smaller deals and not a decline in funding. Series A deals lagged angel deals by greater than the 9-12 months needed to raise the next round, causing the publicized Series A crunch through 2013. Series B companies have begun an up tick but again lag earlier rounds. Tom Tunguz demonstrates this in his post The Hardest Round.

Changes in capital efficiency and ease in company creation take a while to propagate through the venture economy.

Takeaway

This increase in venture investment is being driven by investment in a handful of companies. This is a relatively new trend of late stage pre-IPO investment from hedge funds and private equity firms. In Q1 2014, Cloudera raised $740M from Intel, T. Rowe Price and Google Ventures. Dropbox raised $350M from BlackRock, Morgan Stanley, T. Rowe Price. Lyft raised $250M from Coatue, Alibaba, and Andreessen Horowitz. And the list continues…

This new normal of pre-IPO trend also seems to continue as Airbnb raised Continue reading "Recent VC spending peak reflects new pre-IPO rounds"

Flywheel – 8 ways to build marketplace liquidity

tl;dr Marketplace = liquidity. Focus and fake as much as possible to get started.

Steve Schlaf has an excellent overview of the on-demand mobile services. Many, if not all, of these services represent modern evolutions of service marketplaces. This isn’t surprising, marketplaces from eBay to Kickstarter to Uber are a triumph of the power of the internet and now mobile computing. Goods and services that previously didn’t have sufficient demand in local markets can now market to the globe. Service marketplaces ticking Bill Gurley’s 10 Factors for a digital marketplace, large markets with high fragmentation, poor experiences, economic burden and network effects, can be rethought.

Schlaf’s map is partially representative of Andrew Parker’s earlier unbundling of Craiglist. The surprise isn’t that Craigslist is disaggregating, it’s that it is taking so long (note Andrew’s piece was written at the beginning of 2010). A marketplace that reaches liquidity is difficult to unseat even with as poor an experience and as diverse an offering as Craiglist.

The proliferation and funding of these service marketplaces reflects the value they have at liquidity. The lack of speed of this disaggregation reflects the incredible difficulty in reaching that liquidity. These two sided marketplaces have the classic chicken-and-egg cold-start problem. Below are some tips to drive the flywheel of marketplace liquidity.

As a quick background, I’ve spent most of my career focused on various marketplaces: search ads - Google, media - YouTube, local - PrimaTable, and most recently travel - Hotel Tonight.

Two Sided Marketplace

A two sided marketplace requires both buyers and sellers. Buyers are only interested in relatively valuable supply and vice versa.

To be successful, two sided marketplaces must build essentially two businesses. Uber must sell drivers on the value of their market relative to their other options through price, liquidity, aggregated demand and services like payments and insurance. At the same time, they also create a great customer experience and user acquisition through P&R, mobile user acquisition, and virality.

At scale, everything needs to be automated to facilitate liquidity. Until you get there manually faking the market can get the flywheel going.

Just as startups = growth, marketplace = liquidity. Let’s consider both sides of the market.

Supply and Demand

Faking the seller (supply) side of the market is often the easiest. For a seller, a new marketplace represents integrating a new channel for the possibility to make more money. In service marketplaces, this new channel is often exclusive and thus the risk associated requires a commensurate economic incentive in the form of relative value. Suppliers primarily care about liquidity - defined by wikipedia as “a market’s ability to facilitate an asset being sold quickly”.

Demand can be harder to build Continue reading "Flywheel – 8 ways to build marketplace liquidity"

State of the M&A Market

tl;dr Recent acquisitions represent a huge increase in valuations over historical multiples.

The recent spat of enormous acquisitions (Mandiant @ 1B, AirWatch @ 1.45B, Nest @ 3.2B, WhatsApp @ 19B, Oculus) in the first three months of 2014 had me question whether this is M&A market is materially different than previous years with the likes of Tumblr @ 1B, Instagram @ 1B, Ariba @ 4.5B, SuccessFactors @ 3.5B and more. How far outside of normal are we?

I want to start this post with an important caveat. While Crunchbase is the most representative public data source for start up information, I’ve found the fund raising information is more comprehensive than the acquisition data. For this analysis, I’m assuming (possibly incorrectly) that there aren’t any biases introduced by missing data. Essentially, you need to believe the gaps in either announcement or coverage are uniform across various dimensions (time, category …). We’ll see at least one example where this assumption might not hold true.

The Numbers

Crunchbase Covered Acquisitions.

The number of acquisitions covered by Crunchbase has steadily increased and appears to have reach ubiquity based on a slowing growth rate.

Avg vs Median Acquisition Prices.

In the beginning of 2014, a few huge transactions are pulling the average up dramatically. We are clearly outside the realm of normal on the tail of these acquisition prices. At the same time, the median outcomes haven’t moved nearly as much representing that the majority of companies being acquired are more stable.

Cash on Cash Multiples.

Another interesting dimension of these recent acquisitions is the efficiency of investment, the total price of the transaction divided by the total capital raised. We can see that the current 2014 acquisitions are nearly 4 times the previous years reported multiples.

How do you maximize likelihood of an acquisition?

Category Acquisition Rates.

Taking a look at rates of acquisition (companies acquired as a percent of all companies not including IPOs), we see that as expected this varies dramatically across categories. Web, Ads, Gaming and Enterprise lead likely due to lower priced acqui-hires. Interestingly, Hardware has dramatically lower rates. While this may be a virtue of the hardware industry dynamics, I suspect this is actually a violation of our assumption that the data coverage is universal.

Category Acquisition Rates Over Time.

Enterprise acquisition rates have been higher than consumer historically. In 2009, this trend seems to reverse and consumer outperforms. This could be a reflection of the acqui-hire dynamics or this could be that enterprise acquisitions take longer.

Note that this downward trend is to be expected. Companies take time to reach an acquisition. Below we will see it takes between 4 and 5

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