Does Brand Matter for Startups?

For top CPG categories 1923-1983: 20/25 brands held #1 position in their category the *entire* time 1983-Present: Only 4/25 kept the #1 position

Implication? Brand has never been more valuable for upstarts. Never been less valuable for incumbents.

Contrary to popular opinion, I think focusing on brand early in the life of your company is valuable.

Defining what your brand stands for and, these days, *who it stands with* is an easy way to cut through the noise and attract users who will spread the word.

It's a critical part of a product launch.

When people find a young brand they identify with, they shout it from the rooftops. Think of everything from SoulCycle to Bitcoin. Their champions are relentless. fwiw, this also helps a lot with recruiting. I’ve talked about this trend before as t-shirt theory

(Sidebar: This isn't about superficial marketing campaigns. If your product, people and values don't reflect your brand, then you're brand isn't what you think it is. Now back to the thread.)

On flip side, big companies using brand as a long-term differentiator feels less valuable than ever. Brand turnover keeps accelerating. It's easier for upstarts to poach niches in a market. Cool fades faster. Culture moves quicker. Easy to find yourself out of position.

From ketchup to razors to underwear, the big "enduring" brands seem to be able to rely less and less on their brand equity.

So what does increasing velocity of brands mean for founders? Unique branding is great for pushing your way into a market, but it's a short term tactic not a long-term strategy. You need something else - network effects, scale, better distribution - to win the marathon.

(Originally published as tweetstorm on January 22nd, 2019)

Dynamics of Network Effects

While we know that not all network effects are created equal, they don’t evolve equally either. Every product has different types of network effects that mature and develop differently over time. If anything, most network effects businesses are changing faster than ever before. So how can entrepreneurs and founders navigate this era of seemingly diminishing network effects? The trick is to know what your network effects look like today, but also project how they’ll evolve over time.

Read Full Article at a16z (with Li Jin)

esports vs ecommerce

Theory: esports is to traditional sports as ecommerce is to brick & mortar retail.

3 similarities. 1 difference.

Similarity 1: In ecommerce and esports, some people overvalue(d) the in-person experience.

Remember when they said we’d never buy clothes online because we need to try them on first? Remember when they said that shopping was a communal experience? Eventually they said we’d buy small things online, but we’d never buy something expensive like a car online?

For reference, online clothing is a $300B market today. Online cars is at $50B in US alone. I think they underestimated how consumer behavior can change.

They’re making the same mistake with esports. They say the “in-person sports experience” can’t be replicated online. They say it’s about the crowd and community. "You need to see a game in person to get hooked."

I think they underestimate how consumer behavior can change.

The experience is never the exact same, but ecommerce used the advantages it has (endless selection, one-click ordering, never leave home) and developed ways to overcome it’s disadvantages (free returns on everything).

Gaming and esports will do the same thing.

You can play fortnite anytime you want with people around the world. It’s inherently social. It naturally generates video content (without a huge stadium in the middle of a city). Those are big advantages. They’ll figure out ways to overcome the challenges.

Similarity 2: In ecommerce and esports, the stars have more control and the conglomerates/franchises have less.

This creates a unique advantage.

Stars don’t need brands to endorse or franchises to play for. Their celebrity is the brand. The other pieces, like distribution, can be outsourced.

In old days a celeb would endorse a makeup line. Now Kylie Jenner owns her own (& outsources production) In old days LeBron dealt with Dan Gilbert cause he owned the franchise. Ninja basically owns his own franchise (& outsources monetization). Bet LeBron is jealous.

Removing the brand/franchise gatekeepers gave ecommerce an unfair advantage. It sped up experimentation and innovation. It created endless variation. I think it will do the same in esports/gaming.

Similarity 3: The legacy distributors can’t keep up with digitally native ones.

Brick and mortar retailers like Macy’s saw ecommerce as a compliment to their “core” B&M business, even as it began to shrink. They kept asking themselves how to merge the two.

Amazon and Shopify just built digitally native ecommerce.

ESPN's viewership is in decline, but it's just adding esports content in the same format as the World Series.

Twitch & Caffeine don't have legacy constraints. They’ve built digitally native platforms around new consumption patterns. (fwiw overtime has too).

But there's one big difference: Esports is kind of a (profitable) marketing channel for game publishers.

To my knowledge, ecommerce never had anyone that could influence the ecosystem like that.

It’s a wild card that can change incentives. Unclear to me how this impacts things in the long run.

If theory is right, who ends up building the esports stack? Who's the Shopify, Amazon, the 3P shippers, the packaging companies, etc. of gaming/esports?

(Originally published as a tweetstorm on October 5th, 2018)

Judo-amazonomics?

Been thinking about Amazon recently. One of its big advantages is psychological. Lots of people are simply afraid to compete with them. It fuels a fear flywheel that clears out the competition. I think the brave and crafty will use it as an opportunity. Judo-amazonomics?

When Amazon enters a space (or even glances at it), people run for the sidelines. Founders pivot, investors stall, established players spin up “innovation” teams to deal with the looming threat.

Often the landscape clears of everyone except the old incumbents who have no choice but to fight. It makes it easier for Amazon to enter, which in turn makes them more fierce in the future.

Look at what happens to stock prices when Amazon’s eyes flutter in a particular direction. Double digit drops are the norm, even if it’s just “rumors” that Amazon’s coming.

I have no idea what their plans are in health insurance but healthcare companies shuddered when Amazon announced they’d do “something” a few months back. Same thing happened when they flirted with ticketing in 2017. Or digital prints in 2016. The list goes on.

This fear flywheel is strong. But the best founders are pragmatic optimists looking for hidden opportunity. There’s gold in them hills.

In some ways Amazon’s fear flywheel clears out the crowd and makes it easier for an early stage company. This can be huge advantage from other markets where startups not only slog it out with incumbents but other upstarts trying to elbow their way in.

Borrowing Alfred Marshall’s analogy, young trees always manage to find the cracks of light in an old forest. It helps that they don’t have other saplings to worry about.

It’d be profoundly stupid to underestimate Amazon. It built the machine that makes the machine. But it can’t do everything at once. And some things are more important to it than others.

For example, when Amazon announced they were offering print photography Shutterfly fell 12%. Amazon's going to crush them right?

Turns out Amazon was using a white label provider and the experience was meh. Since that day, Shutterfly's maintained top line revenue and its stock price has nearly doubled.

Photo prints (rightly) aren't really a priority for Amazon, but I would guess their foray reduced the number of upstarts trying to take share from Shutterfly.

Two pieces of advice to anyone thinking of starting a business here:

(1) find a niche that isn’t core to Prime

(2) prepare yourself for a day when Amazon might come.

On (1) ask yourself whether what you’re building would be a significant feature for Prime. Health insurance feels like it could be a core part of a Prime membership. Photo prints, not so much. Ticketing is probably somewhere in the middle. Find the holes that Prime creates.

On (2) build something that that makes your product defensible if/when Amazon comes for your market.

Maybe it’s a network effect they can’t overcome, (like the streetwear marketplaces). Maybe it’s a unique buying experience they can’t replicate (like jewelry or eyeglasses). Maybe it’s a strong brand (take your pick). Maybe it’s something else (hint: scale is a bad answer).

Regardless of the type of defensibility you build, it better be crazy strong because if you’re wildly successful (and I hope you are) then they’ll at least test your boundaries.

I look forward to the case studies of the future, where we all look back at how a few crafty and brave founders used Amazon's fear flywheel to their advantage. I’m sure it’ll seem both rational and obvious in retrospect.

(Originally published as a tweetstorm on August 6th, 2018)

T-shirt theory

Hypothesis: early test for founders on whether you’re building something interesting is if people are trying to affiliate with your project. Call it the t-shirt theory

If people are excited to wear a t-shirt with your logo, you’re building something that resonates. Keep going.

Double points if they want to wear it and they’re not directly involved. Zero points if they’re a BD person that feels obligated to wear it. Negative points if that person also wears a sweater to cover it up.

Most interesting projects tap into a deep sense of mission and community. In the early days they’re more like movements than companies. It’s the only way to get talented people to work on something in its infancy or to get early adopters when the tech is buggy.

Apple stickers used to be everywhere when it represented being part of a community committed to bringing beautiful design and usability to technology.

I remember asking a friend to snag me a twitter water bottle in the early days when it represented giving ordinary people a voice.

I still have a GiveDirectly sticker on my notebook because I think what they’re doing is awesome.

Vitalik’s rainbow unicorn llama t-shirt became a cult sensation in part because of what ethereum represents to that community.

I think most people - developers, early adopters, investors, advisors - subconsciously run this test in their head. It’s an early sign for founders that you're tapping into something foundational in your community.

This works equally well with people putting stickers on their laptop or putting your handle in their twitter/github profiles. It’s about association, not swag.

This isn't the end point. Lots of other things you'll need to do to build something successful. But it can be an early sign you've got potential.

And fwiw, most t-shirts/stickers/association I see these days are for gaming and crypto projects.

(Originally published as a tweetstorm on July 27th, 2018)

For when someone says “I’ve seen this before, it didn’t work”

If you’re a founder you’ve probably heard someone say “oh, I’ve seen this idea before - it didn’t work” or “isn’t this just like that other thing that person/company X tried?”

As a founder, I heard this dozens of times. It’s likely to come from investors, but you hear it from other founders, potential employees, advisors, customers, even family members. Like it or not, pattern matching is strong.

I get contacted from a new company every 3 months working on a idea that's similar to Frank (our old startup). And our idea was similar the original Lending Club and Prosper idea - but with a unique twist, of course :)

Each generation of founders comes back to a few ideas that were tried by a previous cohort. Micropayments to users to sell their data is a one I’ve seen in various eras. Computer based designers is another. In the end, Chewy sounds a lot like Pets.com.

So here’s the thing if you’re a founder hearing “someone tried this before”: this isn’t a reason to be discouraged.

Successful companies often look like previously unsuccessful ones, but with a few differences that are only obvious in retrospect.

Choose whichever cliche you like best - past is prologue? back to the future? - but it’s undeniable that the future often starts off looking pretty similar to the past. In fact, because consumers favour things they know, this can be a feature, not a bug.

While hearing ‘someone tried this before’ doesn’t mean your startup is doomed, it does mean you need to do your homework. And that is much easier said than done.

In this discovery phase, you to need to answer three questions:

(1) has this been tried unsuccessfully before?

(2) why did that company fail?

(3) am I really different?

These sound trivial, but if you're answering them honestly they’re actually very hard. In fact, each one is harder than the last.

‘Has this been done before’ is hard because most startups fail quietly. It’s not like there is some central repository of failed startup ideas.

The ones we tend to hear about in the press are either the huge successes (Airbnb) or the notorious failures (Theranos). 99% of startups end up in the middle.

And once a few years have passed, people have shifted in and out of the ecosystem so community memory erodes. “Who was doing that? Shoot I forget what exactly they did. Ahh nevermind”

Best thing you can do is find nodes - investors, advisors, recruiters - that see a lot of things and might remember. Extra points for finding people who have been around a long time or from different cohorts.

It’s really a grind game though. Ask everyone you meet: “have you seen anything like this before?” The trick is to ask it *honestly*. It’s discovery not promotion. It’s “Have you seen this?” Not “have you seen THIS!”

“Why did they fail” is even harder to get answers to. Ask 3 co-founders why their start-up failed and you’ll probably get 3 different answers.

It’s like a Rorschach test for the founder mind. One might say they went after the wrong market. Another might say the product had a fundamental flaw. Another might focus on execution mistakes.

They’re all probably right in some form or another. You need to continue to push and prod to get to the second and third layer

To borrow a legal term: ask them to connect the dots between the proximate and the cause in fact of their company not working. Keep asking why. Keep going down the ladder of inference. The more specific the answer, the more likely you’re at something real.

Keep in mind you’re talking to someone about something they may have spent years on and is -- for better or worse -- a part of their identity. Be empathetic as you dig. It’s part investigative journalist, part therapist and part pastor.

“Is my startup really that different?” is the hardest question to answer because it’s the most personal to you. Whether you believe it or not you’re probably already emotionally invested in the answer. You’ll really really want it to be “of course we're is different”.

In a lot of cases the answer is yes. A small product change can open up a set of users that never existed before. A unique go-to-market can make all the difference. Even a new competitor can help users and investors understand your category.

But you can also get tricked. You can be different in a way that doesn’t actually change the outcome.

At Frank we made the experience of social lending way better, but we never solved the customer acquisition problem that took down our predecessors. Better product didn’t change that, so our potential was limited.

You need to be super self-aware at this point. You’ll want to weave a narrative that makes all the pieces fall into place. It’s the natural thing to do, and if you’ve started fundraising you might already have a nicely packaged story.

Superhuman self-awareness can be one way to manage this ... or you can try to set up a process that forces you to find real facts that could only be true if the answer to "am I really different" is YES!

Find the evidence that means your unique twist will help you succeed where others have failed. Give yourself a time limit to find that evidence. If you can't find them, then make them your initial OKRs. Work to prove that in the initial phase of your company.

So when someone asks “didn’t someone try this before” you know exactly what to say.

(Originally published as a tweetstorm on July, 13, 2018)

Trust, The Sharing Economy and Behavioral Economics

Originally posted on BehavioralEconomics.com in July 2016

Trust, The Sharing Economy and Behavioral Economics

4 Lessons from Behavioral Economics for the Sharing Economy

By D’Arcy Coolican & Lucas Coffman

Getting trust right is critical to commerce and economic growth. Evidence from behavioral economics can help guide the way. 

Trust and the Rise of the Sharing Economy

Trust. It’s a complex, tricky, hard to explain, harder to define concept, but it’s crucial for so many things.

As Adam Smith pointed out, a base level of trust in society is necessary for specialization and the economic growth that accompanies it. If we didn’t trust the butcher to give us quality meat without having to inspect the cow every time — or worse yet, if we needed to litigate after every grocery run — the whole system would come to a screeching halt.

This concept is even more critical in the sharing economy — which is often, quite appropriately, referred to as the trust economy.

The sharing economy requires an incredibly high degree of trust, often based off little more than a profile picture and rudimentary reputation system. One needs only a few examples to realize how much trust is actually involved.

  •  Think about the faith required to get into the backseat of a random person’s car late at night? Seemed like a leap, until Uber made it ubiquitous.

  • Or consider letting a complete stranger staying your guest bedroom? Even visionary investors thought it was a dangerous idea … until AirBnB proved that it wasn’t.

Maybe it’s a trust in the platform (i.e., I trust Uber to screen and monitor drivers) or just trust in people (i.e., that AirBnB host looks legit), but either way it requires a tremendous amount of trust.

These successes in the sharing economy startled more than a few cynics who assumed that this reliance on trust, reputation and goodwill would quickly become a giant scam or worse.

The Subsequent Fall of the Sharing Economy

But a concept that began with such promise is already going through some tough growing pains.

In many ways, the sharing economy seems to be coming apart at the seams. Whether it’s Uber drivers attacking their passengers, or Lending Club defrauding users, these recent problems — and big problems they are — have re-emboldened the original pessimists who doubted the idea of a trust economy in the first place.

Given that trust that is so crucial to the sharing economy — and that many Silicon Valley darlings seem to be getting it wrong — we thought it was time to go through the important lessons from behavioral economics on how trust (and trustworthiness) actually works, and the important consequences for the sharing economy companies.

Lessons from Behavioral Economics for the Sharing Economy

Lesson 1: Trust begets trustworthiness

One of our favorite concepts in behavioral economics is the idea that signaling that you trust someone, is a strong way to get that person to act in a more trustworthy manner towards you.

Armin Falk and Michael Kosfeld provided the first evidence of this hypothesis in their seminal paper: “The Hidden Costs of Control”. We give details on the experiment here, but the takeaway was that when Person A chooses to control or limit Person B’s options, Person B acts in a less trustworthy way towards Person A.

Put another way: If you show you trust the person, they’ll act more trustworthy towards you. Trust is self-fulfilling.

In many ways this explanation can help us understand the initial success of the trust economy.

  • The stranger that is welcomed into someone’s AirBnB might be a little more conscientious of a guest knowing that the owner has trusted them to act appropriately. After all, trust does beget trustworthiness.

This positive — and counter-intuitive — outcome helps show that people are more trusting than skeptics usually assume, especially when someone else goes out on that limb first.

This idea — and the resulting spike in trust-based activity — helped fuel much of the early optimism of a utopian trust economy where we could all operate on a system of goodwill toward mankind.

Lesson 2: Trust and reciprocity are limited in time

The TED talk types are often inclined to focus on these surprisingly positive elements of trust, but they often ignore the limitations that are just as important. While trust and reciprocity are very real phenomena, they also have very real limitations.

Most importantly, trust and reciprocity decline quickly with the passage of time.

As Uri Gneezy and John List show in their wonderful paper on gift exchange, the warm glow and good feeling of a generous and trustworthy act begins to disappear very quickly and after a few hours there is no difference in outcomes.

As one gets farther from the moment when trust was shown, the less likely one is to act in a trustworthy way.

How does this concept affect the sharing economy?

  • Maybe that AirBnB guest will be conscientious on the first night, but after 10 days in your apartment, they might spilling things on the couch and leaving a mess in the bathroom.

  • Or that 36 month loan on Lending Club or Vouch will look very different in month 32 than it does in month 2.

Many of the challenges the sharing economy has seen recently can be traced back to the evidence documenting this very real limitation on trust and collaboration: timing matters.

Lesson 3: Trust and reciprocity are limited in scope

Just as time can work to diminish trust and goodwill, so too can it diminish with decreased social proximity.

As Arun Chandrasekar from Stanford, Cynthia Kinnan from Northwestern, and Horacio Larreguy from Harvard show in their paper on Social Networks as Contract Enforcementpeople are much more likely to act appropriately (even without a contract) when they share many close social connections with the person on the other side of the table. As these common social ties decrease, the degree of cooperation declines significantly.

So what does this mean for the sharing economy?

  • One might be more conscientious of refilling the gas for the car sharing service they use by their apartment that they know their friends also use, but maybe not the car they use when they’re visiting a different city.

  • Or (more controversially) an AirBnB user might be more likely to rent a room to someone that looks and sounds like they do.

Again, this evidence doesn’t mean the sharing economy doesn’t work, but we need to be aware of what the behavioral evidence says we should expect to ensure the systems that are built are fair and durable.

Lesson 4: Don’t lose trust, because it’s really hard to get back

One of the most under-appreciated concepts in the world of sharing economy start-ups is the idea that once trust is lost, it can be extremely hard to get back. “Move fast and break things” might work for a social media company like Facebook, but it can destroy an industry that relies on sharing, trust and cooperation.

For an example of this we need to look no farther than the heartbreaking history of the Tuskegee Study.

The Tuskegee Study was an experiment that started in the 1930’s that aimed to study certain diseases in poor black sharecroppers. The horrifying part was that after a cure for the disease was discovered, doctors withheld treatment in order to continue studying the effects on their patients. Revealed to the public in 1972, it goes down as one of the darkest moments in US history.

In a new paper, Marcela Alsan from Stanford and Marianne Wanamaker from the University of Tennessee, showed that this helped create a post-1972 distrust between black males and the medical community that has persisted. Over the last 50 years this distrust has led to black males underutilizing doctors and dying almost 1.4 years younger.

As the post-2009 finance community can attest, re-gaining the public’s trust after it has been lost can be an extraordinarily difficult task.

So for every sharing economy start-up that fails to foster or reward the trust of their users, the entire industry suffers. One does wonder how the sharing economy as a whole suffers for every one of these Uber driver issues or bad Lending Club loans.

The behavioral research would suggest that the price will be high.

What does it all mean?

The sharing economy was born with an incredible amount of promise. It was going to leverage trust to help create a more cooperative and efficient world. But if it’s going to actually fulfill this promise, its leaders need to begin to acknowledge and design around the limits on trust and cooperation that behavioral economists have already been helping us understand.

It doesn’t mean we should declare the entire industry dead and move on to the “next big thing”. It just means we need to be more thoughtful about where it will work and what design mechanisms can give it the best chance for success.

  • Not every exchange is ripe for the sharing economy. For example, a platform that relies on a reciprocal action years after the initial action might be too disconnected to actually work. This is probably just a no-go.

  • Some platforms might not be as big as Uber. For some, the limitation on scope means the actual circle of trust is necessarily small. I might be willing to lend my lawnmower to 100 people around me but my car to only 25 people around me. This might be smaller that venture capitalists ideally want, but at the end of the day I’m sure they’d prefer a platform that works to one that doesn’t.

  • Commitment mechanisms are critical where time is a factor. For example Frank is a P2P lending platform that allows people to borrow money from friends and family in a safe way. In Frank the reciprocal action usually happens months after the initial action, but because the platform asks borrowers to set up the repayment schedule immediately it captures that sense of trust and reciprocity at its peak. (Full disclosure: the authors of this article helped design and create Frank.)

  • Repetition is important where trust can dissipate. Every interaction can help build and re-enforce trust. Taking an Uber everyday can help me trust the system. Or getting an email from Frank with every successful payment can help restore the feeling of trust and reciprocity.

  • Technology can make the world feel smaller. Online communities — whether a Reddit board, an AirBnb reviewer, or a Facebook group — can make people who were previously distant feel “proximate” and increase that trust factor.

  • Start-up failure rates are unacceptable for the social economy. The majority of start-ups end up failing, it’s just how that system works. And it’s fine if the platforms fail, but for every user that feels a breakdown of trust, the rest of the industry suffers. Everyone needs to be cognizant of that.

I believe in the sharing economy. I believe it has the power to create economic opportunities for a part of country that is often left behind. I believe it can make the world more efficient and reduce the power of middle-men.

But until that industry begins to understand the well documented behavioral and psychology constraints of it, it will fail to meet the lofty expectations that it sparked.

Read full post at Behavioraleconomics.com