Category Archives: Startup

Jack Dorsey Interview

Intressting Jack Dorsey Interview.

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Jeff Bezos on How To Start Up A Business

jeff-bezos

Jeffrey P. Bezos is an e-commerce internet entrepreneur, investor, and technology innovator – He has started ventures such as Amazon.com, Blue Origin, and other businesses within Amazon such as AWS cloud computing, music sales, clothing retail, etc.
As of 2017, Bezos is the 5th wealthiest person on the planet with a net worth ~70 Billion USD.

In this video, Bezos speaks on innovation in software and management, the definition of profitability and success in business, how to make money through online or offline opportunities, and the incredible increase of broadband usage leading to greater ability to provide better service than ever before

Video ::Jeff Bezos on How To Start Up A Business

 

Nice Video : Jack Dorsey at Startup School 2013

Square co-founder and Twitter chairman Jack Dorsey made an appearance at Y Combinator’s Startup School event where he spoke about acceptance and motivation in how you build a team and company. You can’t do something without a common share or purpose — you will wobble and not do anything that is timeless.

Reading from Robert Henri’s “The Art Spirit“, Dorsey made comparisons about what’s in the story with how it relates to startups. He said that entrepreneurs should build what they want and with purpose.

 

Transcript here : https://glose.com/book/startup-school-2013/jack-dorsey

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No surprise, a lot of unicorns are actually donkeys.

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( Source : https://medium.com/@abhasvc/unicorns-vs-donkeys-your-handy-guide-to-distinguishing-who-s-who-f1b30942b2b6 )

I’ve been having this conversation a lot lately:

Friend: “Did you see [startup] just raised at a $1B valuation?”
Me: “Unbelievable.”
Friend: “They’re apparently killing it on [metric that is meaningless without the bigger picture].”
Me: “Yeah, but their [metric that also matters] is struggling.”

I am by no means the unicorn prophet, but here’s how I think about which companies have earned their unicorn status vs. which ones are playing a dangerous game of massive capital needs, sky high valuations, impossible expectations, and deferred judgement days. Hopefully, by the end of this post, you’ll have an intuitive feel for which startups actually have a shot at being unicorns and which ones are probably just donkeys.

The Fundamental Law of Growth

LTV = Lifetime Value of a Customer; CAC = Cost of Acquiring a Customer

Like Newton’s laws of gravity or momentum, most tech startups (see exceptions below*) who sell directly to their customers — both enterprises and consumers — must eventually obey the Fundamental Law of Growth: LTV/CAC > 3. There’s a lot of nuance as to why — a discussion that is better suited for a semester-long class than a blog post — but suffice to say that the LTV/CAC ratio speaks to a startup’s revenue trajectory, capital needs, and in turn, how much “irrational exuberance” is demanded of its investors. The lower the LTV/CAC ratio, the less efficient a company is at deploying capital and the more money it needs to fuel growth; conversely, the higher the LTV/CAC ratio, the more efficient the company is and thus the more value it creates for the same amount of capital. Though this can be derived, many before me have empirically observed that 3x is roughly the threshold needed to build big, sustainable businesses.

Assessing a company’s valuation is a discipline on its own and growth is only one factor in that calculation. However, for simplicity’s sake, one can assume that tech companies who don’t obey the Fundamental Law of Growth will eventually lose access to capital, drastically slow their growth, and watch their valuations plummet — those fabled unicorns will eventually emerge as donkeys. So with that, let’s dig into some examples…

*Companies whose value is not predicated on revenue (e.g., disruptive technologies, monopolies, social networks, intellectual property) as well as companies where revenue is achieved indirectly (e.g., ad-tech networks, certain marketplaces, certain viral growth startups) or discontinuously (e.g., government contractors) typically do not follow this rule


For each example, I’ll make assumptions about the various components of the LTV/CAC ratio (see below); some assumptions are based on publicly available data and others are just gut feels. If it’s the latter, I’ve generally erred on being generous to the startups.

ARPU = Average Revenue Per User

Case Example #1: HelloFresh, Subscriptions Meals

  • Customer Lifetime — in my household, we usually try each meal subscription company for a few weeks then switch it up, but let’s assume the average across all customers is 3 months or 0.25 years
  • ARPU — average revenue is probably 2 people, 3 meals per week, 3 weeks per month, so $60/week x 3 = $180/month or $2160/year
  • Margin % — we know from Mahesh’s excellent IPO filing teardown that their margin is 52% (sign of a strong operating team; that’s higher than I expected for this type of business!)
  • CAC — given the numerous other meal subscription companies, brick and mortar competitors, etc., it feels like the CAC is probably in the hundreds, say $400
LTV/CAC = 0.25 years x $2160/year x 52% / $400 = 0.70x

Under these assumptions, HelloFresh is an incredibly capital intensive company because of the (presumed) low customer lifetime/high churn. We know from the IPO filing that HelloFresh grew its revenue from $77M in 2014 to $290M in 2015 (276% growth), so you can understand why someone would say, “They’re killing it on revenue!”. We also know that the company didn’t report cohort retention data, but as per Mahesh, “they do mention that they achieve 2.8x LTV/CAC after two years.” Hold up, come again?Reporting LTV/CAC for only a subset of customers is disconcerting, and even then, it’s just under 3x; substituting 2 years into the LTV/CAC ratio suggests that the true CAC may be much higher ($800). Other food subscription and even some on-demand meal companies — Blue Apron, Plated, Instacart, Munchery, Sprig, etc. — may similarly have short customer lifetimes/high churn and thus low LTV/CAC ratios, thereby also violating the Fundamental Law of Growth.

Verdict: Donkey Watch

Case Example #2: Evernote, Productivity Software

  • Customer Lifetime — I use Evernote constantly, so I expect if anyone is going to have an extended lifetime, it’s them. But as a rule of thumb, lifetimes >3 years should only be considered in exceptional circumstances
  • ARPU — in most freemium products, paid customers make up only a tiny fraction (<5%). Nevertheless, let’s assume 25% are premium users at $50/year, so a blended ARPU of .25 x $50 = $12.50
  • Margin % — pure SaaS company with no customer service costs should probably achieve 70–90% margins, so let’s go with 90%
  • CAC — freemium models typically land in the $1–$100 CAC range, so let’s assume $20
LTV/CAC = 3 years x $12.50/year x 90% / $20 = 1.69x

Evernote has great customer lifetimes, margins, and low CACs; however, because their pricing is low, their overall LTV is limited and thus results in a low LTV/CAC ratio, again violating the Fundamental Law of Growth. Evernote could compensate by increasing pricing, but with other readily available substitutes (Google Docs, Microsoft OneNote), increased pricing likely increases churn too, so the pressure is on Evernote to then increase ARPU by increasing value (additional products, collaboration tools, AI insights, etc.).

Verdict: Donkey Watch

Case Example #3: Oscar, Health Insurance

  • Customer Lifetime — once you join an insurer, you typically stay with them until you switch jobs/get a job. <1.5 years is probably the average, but let’s use 2 conservatively
  • ARPU — $5000; saw this in an Oscar press release and it’s fairly typical of this market
  • Margin % — healthcare insurers have gross margins in the 5–10% range with a max of 15% as mandated by Obamacare, so let’s go with 15%
  • CAC — this is an expensive product for consumers to purchase and probably requires a light-touch inside sales team, so let’s assume CAC is $800
LTV/CAC = 2 years x $5000/year x 15% / $800 = 1.88x

Similar to HelloFresh, Oscar is posting massive revenue ($200M) and growth rates (135%), so you can again understand the hype around them; however, Oscar fails the Fundamental Law of Growth due to its low gross margins. If the Oscar team can achieve a CAC near $500 — perhaps because they’re the hip/fresh insurer on the block with best-in-class marketing — then maybe the company can still grow a horn, but that’s asking a lot given the inherent complexity and cost of the product. Recently, a number of other companies— Jet.com, Instacart, etc.— have built fast-growing businesses that operate on low margins, but they too are at risk of breaching the Fundamental Law of Growth.

Verdict: Donkey Watch

Case Example #4: ZocDoc, Online Physician Reservations

  • Customer Lifetime—I’ve heard that physicians typically churn after a year once they’ve established a sizable patient base, but let’s assume 2 years
  • ARPU — $3000 (publicly available)
  • Margin % — SaaS company with light-touch customer service should probably achieve 60–80% margins, so let’s assume 80%
  • CAC — Selling to physician practices must be challenging, so like any high-touch inside sales operation, ZocDoc’s CAC is probably in the $1–10K range; let’s assume $3K
LTV/CAC = 2 years x $3000/year x 80% / $3000 = 1.60x

ZocDoc has a good LTV overall, but their CAC is likely a show-stopper. Unfortunately, there’s no getting around that — selling to physicians is tough stuff, just ask Pfizer. Also, as competition increases, customer lifetimes and pricing erode too, further driving down the LTV/CAC ratio. I suspect this is why ZocDoc is shifting sales to hospital system customers (1000x higher LTV and only 20x higher CAC), but hard to know what fraction of their business this constitutes. Although I am not familiar enough with the unit economics of fantasy sports startups, I suspect that FanDuel and DraftKings may similarly be spending heavily on customer acquisition without the supporting customer lifetimes or ARPU needed to satisfy the Fundamental Law of Growth.

Verdict: Donkey Watch


Concluding Thoughts

I hope this framework gives you a better sense of how to evaluate today’s unicorn landscape. The companies above all have impressive, press grabbing growth metrics, but they also fail the Fundamental Law of Growth for different reasons — short customer lifetime, low pricing, low margin, and high CAC — so must be viewed with some skepticism.

The most obvious next question is: if the Fundamental Law of Growth is so simple, why did investors grant $B valuations to these companies and others in the first place? I believe the answer is a combination of downside protections, upside overoptimism, and what can only be described as FOMO.

Downside protections are being prominently discussed now in light of Square’s down round IPO (albeit still in unicorn territory); to put it simply, late stage investors have (smartly) insulated themselves from losses, so they’re willing to give more on valuations. With regards to upside overoptimism, I imagine that when these rounds were executed, both investors and entrepreneurs believed that things would look up — customer lifetimes would extend, ARPU would increase, margins would expand, and CACs would decline. Alas, it doesn’t always pan out that way, which is why we encourage our portfolio companies to stay conservative on valuations: big up rounds can be appealing in the short-term, but when companies stumble (which they often do), the subsequent down rounds can be outright devastating. Zenefits, for example, is likely to feel that pain shortly given their recently exposed stumbles.

Personally, I’m looking forward to a private market correction. I feel my colleagues and I have done a good job building a portfolio of companies with sound fundamentals and well-earned valuations; a return to sanity would be a welcomed change, as it would unlock quality talent that we can then direct to our companies and others who are playing the prudent, long game.

Lessons Every Startup Can Learn from Uber’s Growth

Uber was founded just six years ago, but it’s already one of the fastest growing companies in the world. As an illustration of just how massive the company’s growth has been, Uber has reportedlycreated over 160,000 jobs in the United States alone and plans to create over a million more in the next five years. In 2014, it raised over 60% of all funding going to on-demand startups.

But while Uber is often held up as a remarkable case study on the potential of growth hacking, the company has also faced some serious challenges stemming from the short cuts it’s taken. As a result, there are a number of different lessons for entrepreneurs to take from Uber’s growth–both successes and mistakes.

Uber 101

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Image by JD Lasica

Uber is a ride sharing company that was founded in 2009 by Travis Kalanick and Garrett Camp, a successful technology entrepreneur that had previously launched Stumbleupon. After selling his first startup to eBay, Camp decided to create a new startup to address San Francisco’s serious taxi problem.

Together, the pair developed the Uber app to help connect riders and local drivers. The service was initially launched in San Francisco and eventually expanded to New York in 2010, proving to be highly convenient great alternative to taxis and poorly-funded public transportation systems. Over time, Uber has since expanded into smaller communities and become popular throughout the world.

There are a number of factors driving Uber’s growing popularity:

  • The service is more convenient than traditional cab companies.
  • It offers an alternative for consumers who have become disenfranchised with traditional corporate service models offered by other transportation companies.
  • Uber offers a higher level of customer service than traditional cab companies by employing drivers with pleasant personalities.
  • The service allows customers to rate their drivers, which makes it easier for the company to hold drivers accountable and improve quality control.
  • Uber customers can monitor their driver on a screen to estimate when they’ll arrive – a far preferable alternative to waiting an indeterminate amount of time for a no-show taxi.

As a result, Uber has been able to rapidly expand into new markets around the world. The company is expected to generate an astonishing $10 billion in revenue a year, despite growing competition from alternative ride sharing companies such as Lyft. Given current trends, it’s expected that the company will continue growing over the next few years.

However, Uber also faces some challenges that it will need to overcome to meet its lofty growth goals:

Read more here : http://indianbizparty.com/learning/lessons-every-startup-can-learn-from-ubers-growth/

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WhatsApp Only Needs 50 Engineers for Its 900M Users

 

Earlier this month, in a post to his Facebook page, WhatsApp CEO Jan Koum announced that his company’s instant messaging service is now used by more than 900 million people. And then Facebook CEO Mark Zuckerberg promptly responded with two posts of his own. One said “congrats,” and the other included a cheeky photo Zuckerberg had taken of Koum as the WhatsApp CEO keyed his 900-million-user post into a smartphone. “Here’s an action shot of you writing this update,” Zuckerberg wrote.

WhatsApp is owned by Facebook, after Zuckerberg and company paid $19 billion for the startup a little more than a year ago. That means Facebook now runs three of the most popular apps on the internet. Its primary social networking service is used by more than 1.5 billion people worldwide, and Facebook Messenger, an instant messaging service spun off from Facebook proper, spans 700 million. But the 900 million-user milestone announced by Koun is very much a WhatsApp achievement, not a product of the formidable Facebook machine.

One of the (many) intriguing parts of the WhatsApp story is that it has achieved such enormous scale with such a tiny team. When the company was acquired by Facebook, it had 35 engineers and reached more than 450 million users. Today, it employs only about 50 engineers, though the number of WhatsApp users has doubled, and this tiny engineering staff continues to run things almost entirely on its own. In a world where so many internet services are rapidly expanding to millions upon millions of users, WhatsApp shows the way forward—at least in part.

WhatsApp doesn’t talk much about its engineering work—or any other part of its operation, for that matter—but yesterday, at an event in San Jose, California, WhatsApp software engineer Jamshid Mahdavi took the stage to briefly discuss the company’s rather unusual methods. Part of the trick is that the company builds its service using a programming language called Erlang. Though not all that popular across the wider coding community, Erlang is particularly well suited to juggling communications from a huge number of users, and it lets engineers deploy new code on the fly. But Mahdavi says that the trick is as much about attitude as technology.

Mahdavi joined WhatsApp about two years ago, after the startup was up and running, and its approach to engineering was unlike any he had seen—in part because it used Erlang and a computer operating system called FreeBSD, but also because it strove to keep its operation so simple. “It was a completely different way of building a high-scale infrastructure,” he said on Monday. “It was an eye-opener to see the minimalistic approach to solving … just the problems that needed to be solved.”

Code in Parallel

In using Erlang, WhatsApp is part of a larger push towards programming languages that are designed for concurrency, where many processes run at the same time. As internet services reach more people—and juggle more tasks from all those people—such languages become more attractive. Naturally.

With its new anti-spam system—a system for identifying malicious and otherwise unwanted messages on its social network—Facebook uses a language called Haskell. Haskell began as a kind of academic experiment in the late ’80s, and it’s still not used all that often. But it’s ideal for Facebook’s spam fighting because it’s so good at juggling parallel tasks—and because it lets coders tackle urgent tasks so quickly. Meanwhile, Google and Mozilla, maker of the Firefox browser, are striving for a similar sweet spot with new languages called Go and Rust.

Like Haskell, Erlang is a product of the ’80s. Engineers at Ericsson, the Swedish multinational that builds hardware and software for telecom companies, developed the language for use with high-speed phone networks. “Instead of inventing a language and then figuring out what to do with it, they set out to invent a language which solved a very specific problem,” says Francesco Cesarini, an Erlang guru based in the UK. “The problem was that of massive scalability and reliability. Phone networks were the only systems at the time who had to display those properties.”

Erlang remains on the fringes of the modern coding world, but at WhatsApp and other internet companies, including WeChat and Whisper, it has found a home with new applications that operate not unlike a massive phone network. In essence, WhatsApp is a replacement for cellphone texting services. It too requires that “scalability and reliability.”

What’s more, Erlang lets coders work at high speed—another essential part of modern software development. It offers a way of deploying new code to an application even as the application continues to run. In an age of constant change, this is more useful than ever.

Keep It Simple, Smarty

The language does have its drawbacks. Relatively few coders know Erlang, and it doesn’t necessarily dovetail with a lot of the code already built by today’s internet companies. Facebook built its original Facebook Chat app in Erlang but eventually rebuilt so that it would better fit with the rest of its infrastructure. “You had this little island that was Erlang, and it was hard to build enough boats back to the island to make everything hook in,” says Facebook vice president of engineering Jay Parikh.

Of course, WhatsApp didn’t have to integrate with an existing infrastructure in this way. And Mahdavi believes the relative scarcity of Erlang coders isn’t a problem. “Our strategy around recruiting is to find the best and brightest engineers. We don’t bring them in specifically because the engineer knows Erlang,” Mahdavi said on Monday. “We expect the engineer to come in and spend their first week getting familiar with the language and learning to use the environment. If you hire smart people, they’ll be able to do that.”

The company has succeeded by hiring engineers who are adaptable—in more ways than one. Asked to explain the company’s secret, Mahdavi’s response seems far too simple. But that’s the point. “The number-one lesson is just be very focused on what you need to do,” he said. “Doing spend time getting distracted by other activities, other technologies, even things in the office, like meetings.”

At WhatsApp, employees almost never attend a meeting. Yes, there are only a few dozen of them. But that too is the point.

 

source : http://www.wired.com/2015/09/whatsapp-serves-900-million-users-50-engineers/

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A Fireside Chat with Bill Gurley of Benchmark: The Future of Ecommerce — September 15, 2015

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