I hope you find it useful!
Part 1 here:
Part 2 here:
(note: there was a brief break when some content was not recorded)
The truly great consumer technology companies of the past 25 years have all had one thing in common: they created habits. This is what separates world-changing businesses from the rest. Apple, Facebook, Amazon, Google, Microsoft, and Twitter are used daily by a high proportion of their users and their products are so compelling that many of us struggle to imagine life before they existed.
But creating habits is easier said than done. Though I’ve written extensively about behavior engineering and the importance of habits to the future of the web, few resources give entrepreneurs the tools they need to design and measure user habits. It’s not that these techniques don’t exist — in fact, they’re quite familiar to people in all the companies named above. However, to the new entrepreneur, they largely remain a mystery.
I’ve learned these methods from some of the best in the business and put together an amalgamation of them that I call “Habit Testing.” It can be used by consumer web companies to build products that users not only love, but are hooked to.
Habit Testing fits hand-in-glove with the build, measure, learn methodology espoused by the lean startup movement and offers a new way to make data actionable. Habit Testing helps clarify three things: 1) who your devotees are; 2) what part of your product is habit forming, if any; and 3) why those aspects of your product are habit forming.
It’s time to abolish the reference check. The unpleasant process of calling up a job applicant’s former boss to gab about the candidate’s pluses and “deltas” is just silly. Maybe if we all just agree to stop doing it the practice will go away, like pay phones and fanny packs. Instead, I’ve learned a better way to hire that leverages a universal human attribute—namely, the fact that we’re all lazy.
What’s my beef with reference checks? They don’t accomplish the job we intend them to do. In a startup, you can’t afford to hire B-players. But reference checks, which are intended to do the screening, fail to eliminate these candidates who are just so-so. This happens because the person giving the reference has no incentive to say anything but good things about the candidate. Telling the whole truth, warts and all, could expose the former boss to a defamation lawsuit. But legal action aside, no one likes to speak poorly about an ex-colleague. It’s bad karma and just feels icky.
Instead of asking a reference to call you and spend an awkward half-hour chitchatting about pretty much nothing, try a technique I’ve come to call it the “average-need-not-apply” method. Though I’m not sure who invented it, the approach was taught to me by Irv Grousbeck at Stanford.
Note: This post originally appeared in TechCrunch
Here’s the gist:
In advertising, marketers reinforce a behavior by linking to the promise of reward. “Use our product,” they claim, “and you’ll get laid”; it’s the gist of many product pitches from soap to hamburgers.
But online, feedback loops aren’t cutting it. Users are increasingly inundated with distractions, and companies find they need to hook users quickly if they want to stay in business. Today, companies are using more than feedback loops. They are deploying desire engines.
Desire engines go beyond reinforcing behavior; they create habits, spurring users to act on their own, without the need for expensive external stimuli like advertising. Desire engines are at the heart of many of today’s most habit-forming technologies. Social media, online games, and even good ol’ email utilize desire engines to compel us to use them.
Recently, my mom came for a visit. She read my blog and discovered her son has a crazy habit of running barefoot. After some convincing, she begrudgingly accepted my rationale, especially after I showed her that a nice Jewish professor at Harvard said it’s ok.
But on one morning, as I was about to walk out the door, my mom stopped me with a tight grab to the arm reminiscent of my childhood. “It’s bad enough you run outside with bare feet but you look ridiculous running with these cheap shmatte gloves.” She always had an eye for spotting the quality of apparel and she correctly identified my Wal-Mart bargain bin gloves, which I bought for $2 per dozen.
“Why are you wearing these things?” she exclaimed. “You must be cold! Let me get you a nice pair of warmer gloves. You’re cold, right? Is that the reason?”
“No,” I said. “It’s not.”
She tried again. “It must be a fashion thing then. The kids are not wearing shoes on their feet but they’re wearing gloves on their hands.” This time she was sure she’d deduced the reason. “So at least let me buy you some nice quality gloves from Bergdorf. You want to be in with the times, I get it. Is that the reason you wear gloves when you run?”
“No,” I said again. “It’s not.”
Reading Leena Rao’s recent article on Techcrunch about the personalization revolution, you get the sense that the tech world is waiting for a bus that isn’t coming. Rao quotes well-known industry experts and luminaries describing what needs to happen for e-commerce to finally realize the promise of personalized shopping, a future where online retailers predict what you’ll want to buy before you know yourself.
Ironically, Rao and her pundits are missing the zooming race car that’s speeding by them as they wait for the personalization bus to arrive. That racecar is Pinterest and the new breed of startups marking the beginning of what I call the “Curated Web.”
The promise of personalized e-commerce began over 10 years ago with technology pioneered at Amazon. It was then that the mental dye was cast for what eCommerce personalization would look like, an algorithmic solution for matching customer to products. Web watchers came to expect that someday all online retailers would have such algorithms on their sites and the dream of personalized commerce would finally be realized.
For over a decade, startups took their best shot at making this apparition a reality. Companies like Hunch tackled the data collection piece of the equation, asking users endless survey questions to determine their tastes and preferences. Google’s Boutiques.com tried to crack the challenges of structuring the data associated with personalized shopping recommendations. Ultimately, these attempts failed.
Note: This article was first published in Forbes
Last week, I sat down for drinks with a few friends. “Have you heard of this Pinterest website?” said Jonathan, “My wife is totally addicted.” “Yes! Molly is hooked too,” said Ben, “She even has her grandmother into it, who, by the way, still can’t figure out Facebook.” “What’s Pinterest?” said Colin, the unmarried engineer.
My friends, the very definition of tech-savvy, couldn’t understand Pinterest’s astounding success. For one, the idea of capturing photos on a virtual wall is nothing new. The Facebook newsfeed is 5 years old and searching for pretty pictures on Google Images is ancient.
And yet, the Pinterest juggernaut is growing faster than Facebook when it was this size. Investors recently plowed in$27 million only five months after the company raised its previous round of financing. But even those who believe Pinterest is onto something big may not really understand why.
Here’s the gist:
Is this it? Really? Facebook wins, cashes in its chips, and we all go home?
Of course, there is more to come and it’s a future filled with sheer awesomeness. Within the next few years, technology will improve your life in ways you can scarcely imagine. But if you’re looking for where we’re headed, it’s useful to know where we’ve been and most importantly, we should know the catalyst driving us from one phase to the next.
Though tech types tend to focus myopically on the laws of hardware innovation, including those written by Moore, Metcalfe and Kryder, these principles focus on infrastructure, which is only the first phase of a rising technology wave. After infrastructure, technology waves enter a platform and finally an application phase. It is during the platform phases in particular that entrepreneurs build world-changing companies without much initial capital, a la Gates and Zuckerburg. How do companies change user behavior so profoundly and produce massive growth, seemingly overnight?
Lately, I’ve noticed a startling paradox in Silicon Valley. I see shitty companies hiring more engineers than they know what to do with, while other, much better companies struggle to fill open roles. Now my definition of “shitty” is completely subjective, but I bet you too can name some ridiculous start-ups that no sane engineer should work for. Meanwhile, companies catering to huge markets, logical business models, amazing user growth, and cash in the bank from top investors, are having a hard time hiring tech talent. What gives?
I call this phenomenon the developer divide. It occurs after a company has cracked a user need and is gaining traction, the VCs have started piling on the cash and the servers are melting from all the users. But there’s one big problem. The company is having trouble hiring engineers to keep up with the torrid pace of growth.
Take Pinterest, the latest toast of Silicon Valley. The company is growing faster than Facebook when it was of equivalent size. Andreessen Horowitz, some of the smartest money on Sand Hill Road in my opinion, just invested in a $27 million dollar round only 5 months after the company closed its series A. The company has umpteen different ways to monetize and few serious competitors. Of course, the company is no sure thing and has plenty of risks ahead, but any investor could make a case for why this company is a good bet. But despite the opportunity, a LinkedIn search reveals the company still employs only 15 people.
When we look at successful entrepreneurs, it may appear that they spend their lives relentlessly driving towards a singular goal. We assume the path to success was a straight shot, lined with mile markers throughout. In fact, it wasn’t. Entrepreneurs make it up as they go. The nature and uncertainty of entrepreneurship favors those who can quickly find the most efficient path, regardless of where the crowd may be headed.
Finding the optimal path, that is, doing only the stuff that matters most and quitting the rest, is paramount to an entrepreneur’s success. In this final post in my three-part series on the lessons and parallels of running a business and running as an athlete, I’ll be taking a look at why quitting is as important as commitment.
Every week, I meet with entrepreneurs who are lit up with passion for their business. Typically, when I am asked to advise someone, I will ask what the top issue is that I could help him or her with. True to form, they begin to describe their social media plan, followed by a description of the slides in the investor presentation they will inevitably make. They would be hard-pressed to omit the amazing code they are in the process of building and the great feedback received from a PR agency they met with, and on and on. Invariably, and quite clearly, there is a lot on their mind.