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Daffy: From Acorns to LinkedIn

/ Adam Nash

This blog post was also published on Daffy.org

Steve Jobs famously talked about connecting the dots of your life in his now well-known commencement speech in 2005. There’s something incredibly insightful and at the same time humbling about that framing as a founder when you look at the differences between the product you set out to build, and where the journey takes you once you launch.

Daffy was based on a number of fairly simple, but powerful, inspirations:

When Alejandro & I raised our $4.8M seed round in 2020 to help build what is now known as Daffy, the Donor-Advised Fund for You™, it was very much based on the idea that we would build the Acorns for Charity. That’s what we pitched.

A little over one year ago, on September 30, 2021, we launched the service. Launching a new product is always both a triumphant and humbling process. It’s so powerful to see people using and enjoying something new that you and your team brought into the world. At the same time, the initial launch is almost always the beginning of the learning process, because real customers have a way of showing you the truth about where they see value in your creation.

So, not surprisingly, it quickly became obvious that we had missed something fundamental in our initial concept of the product.

Giving is not like saving on one very important dimension. Unlike saving, giving is fundamentally better with other people. We discover new causes and charities through other people. We are inspired to give by other people. Most importantly, we support the causes and charities we care deeply about with other people.

The more we learn from our members, the more we’ve come to realize that Daffy is meant to be more than just the best donor-advised fund on the market.

We set out to build the Acorns of Charity, but the future of Daffy may look much more like LinkedIn.

Giving is Better Together

The best software product clues tend to come from the organic actions of customers, and this has definitely been true with Daffy. In this case, our first clue came from people sharing their inspiration around giving with others. 

Every DAF allows their members to include a note to the charity with their donation, and when we designed Daffy, we included this feature. However, with every Daffy donation, the member is given the option to add a public note about why they give. For an optional feature, we weren’t expecting heavy adoption, but in our first year, over 36% of our donations had a public note.

These notes are not like typical internet posts. In many cases, they reflect emotional and deeply personal motivations for supporting causes and organizations.

It might be hard to believe, but in the early days of LinkedIn, there was a lot of public debate about what identity online would look like. Would people have a single profile that represented them on the web, or would we have multiple, reflecting the different slices of our lives? Mark Zuckerberg argued for the former, while Reid Hoffman argued for the latter.

What we believe we have discovered at Daffy is that there is another identity that is meaningful to people, and yet does not seem to have a home online: our charitable identity.

Our Charitable Identity

Even at LinkedIn, it was clear that there were going to be more than just social and professional profiles. Our identities and relationships are often compartmentalized based on context: think about what you ask someone you just meet at a party vs. a conference vs. a school event. At a little league game, I’m not even sure that I have a name — I’m just Julia’s Dad! These identities flourish and wane over the course of our lives, sometimes merging, sometimes fading.

Over the past few decades, it has become clear that there is a resurgence in how people think about themselves philanthropically. The causes you believe in, the organizations you support, the people you work with to make a difference — all of these matter increasingly to people. Perhaps it is a reflection of the times we live in, or perhaps it is an aspect of maturing generations. Whatever the cause, however, it is clear that people are eager to share this part of themselves with friends and colleagues, and also seek this information about others. We are proud of the roles and responsibilities we take on with charitable organizations and the people who work for these organizations.

Discovery. Inspiration. Support.

These seem to be some of the major emotional drivers behind the activity we see from our early Daffy members, and yet this seems to get lost on existing platforms. It’s so hard to compete with dating, news, shopping, and careers.

Fulfilling Our Series A Vision

2022 has not been a kind year for technology companies in general and has definitely been a tough fundraising environment for venture-backed startups. However, when Alejandro & I realized what we needed to do, we also knew we needed to raise our Series A sooner rather than later.

We know that building out this platform will take years, and we are grateful to Ribbit Capital and XYZ Ventures for supporting this vision, and we are especially grateful to the dozens of leaders and luminaries who have individually invested in our efforts.

Today, on Giving Tuesday, we are starting to roll out our first features that will help bring this vision to life. A place where people can not only share the causes and charities they personally support, but also spotlight a charity they are working to support right now. A way to learn who our friends and colleagues give to, and the opportunity to be inspired by their generosity and support their efforts. 

All of these features are layered over our ground-breaking, modern donor-advised fund platform, built from the ground up to help people be more generous by setting their own personal giving goals and then helping them achieve them.

All throughout November, our #BeMoreGenerous campaign gathered 30 notable leaders including Reid Hoffman (co-founder of LinkedIn), Charles Best (Founder of DonorsChoose), and Amy Chang (Board of Directors at the Walt Disney Co.) to use our new “Charity Spotlight” feature to share the charities they support this holiday season — and inspire others to give.

As of today, that feature is now available to every Daffy member.

Together, we believe that we can increase giving by over $1.2 Trillion dollars over the next decade in the United States alone, with an even larger opportunity globally.

If you are one of the 60-70 million households in the United States who give to charity every year, go to daffy.org now and set up an account. It’s completely free for members just starting out with a balance of under $100.

Connect with your trusted friends and colleagues. Share the causes and organizations you believe in. Inspire others to give, and more importantly, connect more people to organizations that desperately need more support. Include your family, and foster real discussions about the causes and organizations you support.

Daffy launched just a little over a year ago, and we are grateful to the thousands of people who have already signed up for the service. But our aspirations are audacious.

Our vision is a world where everyone puts something aside regularly for those less fortunate than themselves. A community of millions, not thousands.

Come join us.

Figma: A Random Walk in Palo Alto

/ Adam Nash / 2 Comments
Figma’s first conference, Config 2020.

On June 25, 2013, Dylan Field, one of my favorite interns from LinkedIn dropped by Wealthfront headquarters in Palo Alto to catch up and get some advice about his new startup, Figma.

At the time, I was up to ears with work as the new CEO, trying to sell the crazy idea that someday millions of people would let computers, rather than humans, manage their money.

But I always take time for people, particularly students just coming out of college and embarking on a career in Silicon Valley. So I met with Dylan for an hour, and we walked around the City Center in Palo Alto talking about his new company. The next day, I sent him a note asking if there was any more room in his seed round, offering to help him with product, growth, and recruiting.

Yesterday, that company (Figma) was acquired by Adobe for $20 Billion.

From Intern to Founder

In 2010, Dylan was an intern at LinkedIn, on the data science team overseen by my friend DJ Patil. However, search & data science were closely intertwined at LinkedIn, and since search was an area that I was responsible for, I spent a lot of time with team brainstorming new ideas and working through product problems. For some reason, I distinctly remember that Dylan was the first intern to ever make me feel old, based on one offhand comment about how he was too young to see the Star Wars prequels when they came out. 🤦‍♂️

Regardless, Dylan was brilliant and delight to talk to about almost any topic, and we kept in touch loosely through social media when he went back to school. He ended up interning at Flipboard, a company that happened to be founded by an engineer from Apple who co-taught CS 196P at Stanford with me, their first class on iPhone development. Dylan stayed close to the data science team at LinkedIn, and so we ended up with more than a few reasons to stay connected. I had left LinkedIn to take an EIR role at Greylock, so was just starting to become an active angel investor.

All of this led to that one walk around Palo Alto.

The Figma Pitch

There was no deck involved, and the meeting was not about fund raising. As it turned out, Dylan had already largely raised his seed round. In fact, a TechCrunch article came out about it that day. Going into the meeting, I had absolutely no idea what Dylan was working on, and knowing Dylan, it literally could have been anything and it wouldn’t have surprised me.

Instead, Dylan & I talked about the transition from Desktop to Web 2.0, and whether now was the right time to bring graphic design to the cloud. John Lilly & I had discussed a hypothesis about this while I was at Greylock, and it was one where I had come to have conviction. The basic premise was that the combination of Web 2.0, Social, and Mobile had finally created the possibility of building truly useful and user-friendly collaborative software in the cloud that was an order of magnitude better than desktop software and would finally drive the migration of professionals to web applications. More importantly, we believed that the history of desktop software contained clues to which types of software would be converted first: productivity applications (late 70s/early 80s), then enterprise applications, graphic design & desktop publishing, and finally personal finance. In fact, this theory is part of the reason I spent 2012 exploring the idea of bringing financial software to the cloud, eventually leading me to the sector now called “fintech” and my role at Wealthfront.

As we talked about this theory, Dylan then shared with me one of those simple insights that seems so obvious in hindsight, but was anything but obvious at the time. He told me that with WebGL in the browser, he thought now was the time to move graphic design to the cloud. As someone who had spent significant time in grad school on computer graphics, my initial reaction was very negative. In my mind, graphic design was incredibly compute intensive, to the point where professionals used highly optimized $10K workstations, multiple GPUs, and optimized data storage to get the local performance they desired.

Dylan was not deterred. He explained that the heavy compute was the exact reason why moving to the cloud made sense. By providing high powered machines in the cloud, anyone could get access to an almost arbitrary amount of power without spending $10K, and latency & bandwidth had progressed to the point where shipping the UI bits to the client was a solved problem.

He was right.

It was a simple moment, but I had to admit that multiplayer gaming had already solved problems of low latency, collaborative UI, and that it might be possible to extend that to the web now. Graphic design wasn’t just going to move to the web – eventually it was going to be better, faster, and cheaper online. On top of that, collaboration would be the killer feature that desktop couldn’t match.

The initial product idea, a photo editor in the cloud, turned out to not be the right way to ride this wave. But in the end, Dylan & team were intelligent and flexible enough to clearly iterate to a product that not only is riding that wave, but is also defining it.

Silicon Valley is about People

When I graduated from business school, my first job was as an Associate at a venture capital firm in Menlo Park. 2001 was a rough time to start in venture capital, but I was excited because I loved the idea of investing capital with founders when everyone else had pulled back. Our office, however, was too large, built out for a boom that had been cut short in 2000. As a result, they gave me a choice of offices.

I picked the one no one wanted, adjacent to the reception area. People thought it was too noisy, but I always left the door open. The reason was quite simple: when founders came in, I wanted to overhear how they treated our receptionist. You can learn a lot about a person based on how they treat people with less power when no one else is around.

Success in Silicon Valley is a dizzying combination of skill and luck, execution, and timing. But first and foremost, it is about people. One of the reasons that the most successful software cultures struggle to avoid hierarchy, is that the rapid change in platform capabilities means that the half-life of experience is brutal. The best solution for a problem five years ago may not be the the best solution today, and it very likely won’t be the best solution five years from now. As a result, young engineers approaching problems for the first time can sometimes see opportunities that the most experienced can’t. Other times, a “new” problem can actually just be a rehash of a problem that was common decades ago. The key is always to work the problem, and always work to avoid the destructive HiPPO anti-pattern. (HiPPO = the highest paid person’s opinion)

These days, online discussion is filled with debates about impressing your boss, impressing your CEO, impressing the company. To me, this misses the real opportunity. For most people, their best opportunities are likely ahead of them, and the connection to that opportunity will mostly come from a co-worker, a “weak connection,” and likely someone who isn’t above you in power and hierarchy.

Dylan was an intern, and not even an intern on my team. There was no obvious reason for me to spend time with him, other than that he is an amazing human being. Very intelligent, and also very kind. A long term, first principles thinker, but also someone who gets his hands dirty building. Ambitious, not to be a billionaire, but ambitious to make a difference and have an impact.

As an angel investor, I tend to look for a strong, authentic connection between a founder and the product they are building. For me to invest, I have to believe the founder is not only tackling a problem big enough to generate venture returns, but also is someone who is intelligent, trustworthy, and ambitious.

Dylan might have been an intern, but even as a teenager, he was all three.

A True Silicon Valley Story

Our careers are built based on the overlay of networks that we build. Every school, every job, every company is an opportunity to connect with people. It will only be obvious with hindsight which connections will generate the most value in your career, but try to remember that everyone may have something you can learn from.

There were quite a few executives at LinkedIn, and more than a few interns. There was no way to predict this type of outcome. Nine years ago, I became an investor in Figma, and two years ago Dylan became an investor in my new startup, Daffy. Roles change fairly quickly, but relationships with good people last decades.

Congratulations to Dylan, Evan, and the whole Figma team. This acquisition is just one more step in the fulfillment of a broad vision to elevate design in every organization. 🎉

It’s a true Silicon Valley story, and one we should all be rooting for.

A Goal for Giving

/ Adam Nash

Like many people, for most of my career, I never set an explicit goal for giving to charity. While I was raised to believe that everyone should put something aside for those less fortunate than themselves, in practice, I mostly gave only when I was asked. Sometimes it was a friend running a marathon for a worthy cause they had a deep connection to. Other times it was a fundraiser for one of the schools that my children attended. But overall, it was reactive, not proactive.

This all changed for me in 2011.

I first learned about donor-advised funds when LinkedIn went public in 2011. All of a sudden, private wealth managers became ubiquitous on campus. Part their sales process, as it turns out, was to promote the tax-deductible benefits of giving to charity through donor-advised funds.

The concept of a donor-advised fund appealed to me, but it raised an important question: how much should you contribute to a donor-advised fund? I had no idea.

Fortunately, at the time, my accountant recommended a fairly simple approach: take whatever amount you plan to give to charity every year, multiply it by ten, and contribute that to a donor-advised fund. The best part? By investing the money upfront in a donor-advised fund, I could potentially fund years eleven or twelve with the proceeds.

For the first time, I was forced to answer what should have been a very simple question: how much did I want to give to charity every year?

At the time, I chose $20,000, which was 10% of my base salary at LinkedIn.

More importantly, I now had a giving goal. And it changed everything about the way I give.

The Two Hard Problems With Giving

It turns out that there are two hard problems inherent in giving money to charity:

  1. How much can you afford to give?
  2. Who should you give the money to?

Until I had a donor-advised fund, I never realized how much the first problem influenced my generosity. But every time I was asked for a donation, there was friction as I tried to figure out what I could afford. However, once I had a giving goal, the first problem largely went away. As a result, I found it easier to give when I found an organization or cause that I believed in.

More importantly, the goal made me more generous. While the donor-advised fund did not change the amount that I thought I should give to charity, it did change the amount that I actually gave to charity. Looking back at my records before 2011, it is clear that having a goal increased my actual giving by more than 100%.

This shouldn’t be surprising. Behavioral economists have known for a long time that pre-commitment can dramatically increase the amount that people save for retirement. Why couldn’t it also work for giving?

This is the reason Alejandro & I started Daffy.

Set Your Giving Goal Today

Our research shows that when asked, most people intend to give a larger amount to charity than they actually end up giving in practice. At Daffy, we call this difference the Generosity Gap. It may sound like a small thing, but we believe that if everyone set a giving goal, it could increase the money given to charity by more than one trillion dollars over the next ten years.

Every year, we set goals for ourselves. Financial goals. Fitness goals. Diet goals.

Until 2011, I didn’t know what a donor-advised fund was, and I didn’t have a giving goal. But in 2022, you can sign up for Daffy in minutes, set a giving goal for the year, and have an app at your fingertips anytime you find the desire to give.

This year, consider setting a goal for your giving and be the generous person that you want to be.

Join us.

Just Getting Started…

/ Adam Nash / 3 Comments

“The journey of a thousand miles begins with a single step” — Lao Tzu

As the year draws to a close, I wanted to share some good news: Alejandro Crosa & I have started a new company, and we’ve raised an initial round of funding led by Ribbit Capital.

This was one of my goals for 2020, and I couldn’t be more delighted to be setting off on this adventure with Alejandro.

Alejandro is one of those rare talents that makes Silicon Valley special. When we first met, he was a contract engineer from Argentina, referred by Google to LinkedIn as we prepared for the Open Social launch back in 2007. But Alejandro had an unstoppable desire to learn, moving from platform to search to mobile. Together, we collaborated on a number of innovative prototypes, including a search engine for Twitter based on LinkedIn data (I still miss this one…)

His passion for new technologies, design, and great products is inspiring. 

Even after we both left LinkedIn, we kept in touch, and talked often about starting a company together. This is that company.

Alejandro & I believe that there is still a lot more to do in consumer fintech, and that through software we can help bring purpose to the way people approach their financial lives. 

Micky & Nick have built one of the pre-eminent firms in fintech; they risked their own money and believed in the category long before most venture firms were willing to invest. We couldn’t be more excited to partner with Ribbit on this new adventure.

I also want to thank Ross Fubini at XYZ Venture Capital for his support, as well as a humbling list of friends & angels for backing this new idea. So thank you to Gina Bianchini, Amy Chang, Walter Cruttenden, Dylan Field, Todd Goldberg, Minnie Ingersoll, Aaron Levie, John Lilly, Gokul Rajaram, Mike Schroepfer, Leonard Speiser, James Tamplin, Rahul Vohra, Liza Wang, and the rest of our investors for supporting us. 

Most importantly, we are hiring! If you are a talented engineer or designer excited about consumer fintech, and want to take a shot at building a platform that just might change the world for the better, come join us! 🦍

We’re just getting started. 🎉

 

Ikigai: How to Find Professional Success

/ Adam Nash / 5 Comments

On December 25, 2017, I tweeted out a page from the World Economic Forum about Ikigai and was shocked at how broadly it spread. This post elaborates on the concept.

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Over the last twenty years, I’ve been asked by hundreds of students for advice on how to think about their careers post-graduation. Inevitably, I’ve always responded with a simple framework to help structure their thinking around picking a profession:

  1. What are you exceptional at?
  2. What do you love to do?
  3. What does the world value?

As it turns out, there is a Japanese concept for this framework. Ikigai.

The Reason You Get Up in the Morning

Dan Buettner gave a TED Talk called, “How to Live to Be 100+.” He focuses quite a bit of his lecture on the island of Okinawa and their extraordinary number of centenarians. He identifies several diet and lifestyle habits that seem to correlate with a long and healthy life. Ikigai is one of those concepts. He recently gave an interview in the Telegraph:

They all have an ikigai. “In the Okinawan language,” said Dan, “there is not even a word for retirement. Instead, there is one word that imbues your entire life, and that word is ‘ikigai’. And, roughly translated, it means ‘the reason for which you get up in the morning.’”

He talked of a 102-year-old karate master who still practised, a 100-year-old fisherman who loved to bring the catch to his family, and a 102-year-old who, asked what her ikigai was, said that holding her great-great-great-granddaughter, a century her junior, felt like “leaping into heaven.”
In Buettner’s framework, Ikigai is not just something you think about when you are picking majors. It’s a form of balance that you seek through your entire life.

What Are You Optimizing For?

When I was in college, my mother constantly reflected on the bad advice she felt students were given as they attempted to pick a career. “Everyone tells students to follow their passion. It’s not that simple. There is a big difference between a hobby and a career.”

My father tended to be more direct. “The world doesn’t owe you a living,” he would often say, “Find something that people value.”

Our popular culture has become saturated with the idea that if you just find your passion, something you love doing, then your career will magically present itself. If only success were so simple. Finding something you love to do is critical, and if you are fortunate, you’ll find several. As it turns out, that’s just one piece of the puzzle.

The fact is, you may love something that the world doesn’t value highly. The world may value things that you aren’t very good at. And of course, you may be good at something that you don’t want to do.

The benefit of Ikigai is that it helps separate out the dimensions you can optimize your professional efforts around, in attempt to help you find a combination that will result in professional success and fulfillment.

Four simple questions.

  1. What do you love? Find something that you really enjoy doing. It’s simple to say that the journey is the reward, but when you love to do something, work can be something you look forward to.
  2. What are you good at? We all have different talents and aptitudes. With practice and determination, you can develop mastery in a wide variety of areas. However, if you have a natural (or hard-earned) talent in an area, that’s worth identifying.\
  3. What can you be paid for? Just because you can do something, doesn’t mean that the other humans around you will value it. Looking for something that the market will reward financially is a critical piece of this puzzle if for no other reason than to set expectations realistically.
  4. What does the world need? Being the unabashed capitalist, I originally assumed that anything the world needed would also be something the world would pay for. Stepping away from the theoretical argument, there is significant value in transparency from separating out this requirement.

Imperfect Combinations of Three

One of the most insightful aspects of Ikigai is the imperfect combinations of three of the four dimensions that are represented in the chart by different colors.

If you find work that you are good at, that you can be paid for, and that the world needs, you may find yourself feeling comfortable but unfulfilled. In this case, you aren’t working on something you love, but likely being compensated for your work and seeing its valuable impact on others.

If you find work that you love, you are good at, and that you are being paid for, you may find yourself feeling satisfied but useless. In this case, you aren’t working on something the world needs, but likely being compensated for your work and enjoying what you do.

If you find work that you love, you are good at, and that the world needs, you may find yourself feeling delighted but uncompensated. In this case, you aren’t working on something that world pays for, but you enjoy what you do and do it well. Fulfillment without wealth.

If you find work that you love, you can be paid for, and that the world needs, you may find yourself feeling excited but uncertain. In this case, you aren’t good at what you do, but you are being paid for something useful, and you love it. Purpose without proficiency.

It is not difficult to think of situations and phases in your life where you might not need to optimize for every dimension. For example, after a financially successful career, it is fairly easy to imagine why a person might optimize around work that ignores the need to be paid. For a retiree, the space between passion and mission might look ideal.

Finding Balance

Ikigai might sound like the right way to talk to students or young professionals in your life about their professional focus. But I would argue that no matter where you are in your career, you should take the time to be intentional about your professional choices and ask yourself these four questions.

Ikigai. It might be the key to a long & healthy life.

Solve the Product Maze Backwards

/ Adam Nash / 3 Comments

As the father of young children, I can tell you that there is a special place in my heart for restaurants that provide puzzles and crayons for small children to pass the time.

On a recent trip out to The Counter in Mountain View, Jordan (who is 8)  was really struggling with a large maze puzzle on one of these activity sheets. It was a fairly large maze, and he was frustrated by his inability to see the dead ends ahead, forcing him to retrace his somewhat tortured crayon path.

I told him to try to solve the maze backwards.

As you can probably guess, he began at the end, and was able  to find a path back to the beginning in just a few seconds . He was delighted, and a bit surprised, to see how simple the puzzle looked like from a different perspective.

Surprisingly, I find that both entrepreneurs & product leaders miss this important lesson when evaluating ideas for either their company or their products.

Three Questions in Product Prioritization

In my experience, there are three common questions that often come up when product features are being debated:

  1. Should we build this?
  2. When should we build this?
  3. How should should we build this?

Unfortunately, even highly talented teams can become  get bogged down in debate and uncertainty when all of these questions become entangled. As engineers & designers are professionally trained to answer the question of “How,” the worst debates tend to happen around the questions of  “Should” and “When.”

Too often, when debating what feature to work on next, debates around timing quickly devolve into debates about whether the feature is needed at all.

Solving the maze backwards does a fantastic job of disentangling these two questions. Simply asking the question of “If we are successful, will we have this feature in 3 years?” tends to illuminate whether the debate is about “Should” or “When.”

If the answer is yes, you will have that feature, then the question is simple. You are just debating priority.

Avoid the Local Maximum

One of the well known issues with iterative processes for delivering product features is the “local maximum” problem.

The assumption is that where ever you start with your product, your team keeps working on improvements. Each improvement is measured to ensure it is “better” than the product before the change. However, you can reach a point where every change you make hurts the metrics that you measure. The fear is that there is a better version of your product (the absolute maximum), but it requires a change bigger than you can get to from the current design.

It’s called a local maximum problem because of the similarity to the concept in mathematics when you are traveling along the curve. From the local maximum, every move is down, even though the curve ends up higher eventually.

Solving the maze backwards can help.

By asking the simple question about whether or not your product in the far future has a given capability, it can unblock your thinking about what leaps and changes will be necessary. Whether the limitations are in technical architecture or product design, clarity on your long term vision can help your team visualize a future not trapped by their current constraints.

Too often, the real limitation is not related to either technical or design constraints, but rather a lack of clarity and imagination about what might be possible. Just like a maze, it is easy to get lost in the middle. Thinking backwards from the end goal can help the team escape a Zeno’s paradox of minor feature improvements.

Founders Can Solve the Maze Backwards, Too

It may seem hard to believe, but in early 2009 when I took over LinkedIn’s mobile efforts, there was still active debate within the company about whether to dedicate significant effort to mobile. Why? Well, back in 2009, the Blackberry was still hitting record sales, the  app store was a year old, and from a web metrics point of view, mobile views represented less than 1% of LinkedIn’s traffic. Like every hypergrowth startup, LinkedIn had a huge number of initiatives it wanted to pursue around growth, engagement & revenue, and it wasn’t obvious that mobile would move any of these needles for the company in the next few years.

Solving the maze backwards helped.

What was fairly obvious in 2009 was that the growth rate of mobile engagement was compounding at a phenomenal rate. LinkedIn, as a professional use case, might have been slightly behind social use cases for mobile adoption, but it was fairly clear that within 5 years (by 2014), mobile should represent a majority (over 50%) of all visits to LinkedIn.

Thinking backwards helped give us the confidence to invest in both talent and technology that had little short term payoff, but would become essential to engagement over the next five years as those predictions came true.

Fast forward to 2017. I was recently meeting with a founder who was debating whether they should hire a Vice President of Marketing. As he walked me through his thinking, the argument wandered, and became more focused on whether or not the company “needed” marketing.

I asked him if there was any way, if the company hit their numbers over the next three years, that the company would not need marketing, or an experienced marketing leader?

The CEO quickly responded that marketing would be essential to hit the numbers they were looking for in three years. All of a sudden, the conversation changed. The question wasn’t whether or not to invest in marketing, but more a question of when they need to.  Was this a 2017 or a 2018 problem? Is this something they would need to hit the milestones to raise their next round of funding, or something that they would invest in during the next cycle?

It was now a question of when.

Questions of “Should” vs. Questions of “When”

“The essence of strategy is choosing what not to do.” — Michael Porter

Being clear about what your product will and won’t do is a critical element of product strategy. However, because it is so important, even well-meaning teams can turn almost any feature into an existential debate.

Thinking backwards can help differentiate questions of “should” from questions of “when,” and that can be incredibly productive in moving the discussion to prioritization.

This is not intended to be dismissive of questions of prioritization. Phasing decisions are some of the most important decisions start ups make. Financing for startups is phased. Small teams can only work on a few projects at a time. Customers can only absorb so many new features at once. As a result, prioritization decisions are incredibly difficult to make.

Greedy algorithms are very good, but can be traps if you are working against competitors and an ecosystem that is willing to make bets that lie across the gap from your product’s current local maximum. Thinking backwards can help illuminate long term goals that are across the gap.

When you are building a product roadmap, and get stuck on debates about a short term feature that doesn’t move the numbers, I encourage founders to take a moment and try to solve the maze backwards.

It worked for Jordan, right?

Spend Time Thinking About The People Who Don’t Use Your Product

/ Adam Nash / 4 Comments

on-the-outside-looking-in

This is an extension to my original three post series on user acquisition.

Today, AirBnB announced that it had reached a settlement with the city of San Francisco on how to effectively register and monitor legal listings in the city. I am a huge fan of the company, and it seems like a positive outcome for both San Francisco and AirBnB.

For many, the issues around many of the sharing economy companies, including AirBnB, are examples of regulators trying to find a way to both control and incorporate rapid, disruptive innovation.  There is, of course, some truth to this point of view.

However, as a product leader, there is another important takeaway that seems to be too often forgotten. Most of us spend too little time thinking carefully about the people who don’t use our products. 

The people who don’t use your product often won’t show up in your core metrics. But if you don’t spend time understanding them, you will eventually feel the negative effects in your growth and your brand.

It’s Natural for Companies to Obsess About Their Users

When a startup launches a new product, it is natural to obsess with every user it touches. Every click, every tap, every piece of data is precious feedback about your features. The data is one of the most objective sources of information about what your users are doing with your product and when they are doing it. In the early days, before finding product/market fit, a huge amount of time tends to be spent on the people you touch but who don’t convert. In fact, that may be where most people at the company spend their time.

As consumer products find product/market fit and hit escape velocity, more and more engineers and designers spend a disproportionate amount of time on users. The people who work on growth & marketing will still often continue to look at the data on leads, trying to find ways of converting those non-users to users. However, as a percentage of the company, fewer and fewer engineers, designers & product managers will be looking at data from non-users.

This makes sense, of course, because as your product grows, almost all feature development is focused on your users. In 2008, when we established the Growth team at LinkedIn, we discovered that of the hundreds of features on linkedin.com, only three features reliably touched non-users. (For those of you who are curious, those features were the guest invitation (email), the public homepage (linkedin.com), and the public profile (in search.))

Customer obsession, of course, is generally a good thing. But as we learned at LinkedIn, if you want to grow a viral product, you have to spend a considerable amount of time thinking about the non-user, where they touch your brand and your service, and find ways to both reach them and convert them to users.

You Have More Non-Users Than Users

Few brands and products could ever claim that their conversion rate for everyone they touch is over 50%. It is even possible that Facebook, with nearly 2 billion users, still has more people in the world who have heard of the company than who use it.

In 2011, I remember talking to the great founders at CardMunch about a new email they were proposing to add to their service. CardMunch was a wonderful app that made it effortless to scan a business card and then have it automatically entered into your address book, with almost no errors. The proposal was to add an email so that the person whose business card you scanned (non-user) received an email from the CardMunch user with their business card in electronic form.

The team was ready to whip something together quickly and test the idea, and the concept was good in principle. But given some of the experience of Plaxo a decade before, it was prudent to ask the simple question: “How many people will see this new email?” Within a few minutes, we figured out that the number of people who would receive this email within the first three months would be 30 to 50 times the total user base of the application.

Some of you are probably thinking, “sounds like a great growth feature!” Others are likely venting about why we have so many emails cluttering our inboxes. Both reactions are fair.

The guidance I gave the team, however, was to consider the fact that, once they launch this feature, most people who have ever heard of CardMunch will have only heard of it through this email. The product and the brand. I asked them to spend a bit more time on the design on the email, in that context, to ensure that all of their hard work on a wonderful product wouldn’t be drowned in an avalanche of poor experience.

In the end, Sid Viswanathan & team did a great job brainstorming ways that they could show the value of a connected addressbook in the email, including LinkedIn features like people you know in common. Once framed properly, it was simple to think about what they wanted non-users to think about their brand and their product.

Non-Users Matter

Marketers, of course, have known this for decades. It is a brand marketing staple that it takes at least three touches of a brand before it will stick with a potential customer.

Somewhere along the way, software companies lost touch with the basic idea that every piece of content that contains their brand is a potential touch. It is not just the users of the core product that matter for long term growth.

Market research and customer development are often essential for discovering and understanding new potential users for your product. The case can be made that viral systems can, in fact, spread to these new pockets automatically. However, truly viral products are few and far between, and in most cases these new markets will not be in the data sets that your product & engineering teams are focused on.

Brand will also impact your company well beyond new user acquisition. With AirBnB, we now know the many ways in which their service and brand touch non-users. Neighbors, for example, have natural questions and concerns when a house or a unit near by is available on the platform.

Software companies, especially successful ones, tend to have passionate and talented designers and product leaders who are eager to find clever solutions to real user problems. Given the right data and focus, there is no question that these teams can also design and build features that address non-user concerns.

Tesla spends time thinking both about the feeling a driver has in the car, as well as the experience of a non-Tesla owner who is watching that car drive by.

Spend more time thinking about all of the people who touch your product & your brand, not just your users.

 

The Millennial Definition of Success

/ Adam Nash / 3 Comments

Wealthfront Team, June 2014

Wealthfront Team, June 2014

It’s hard to believe in 2014, but when I first considered joining LinkedIn in 2007, most of my colleagues had trouble seeing the value in a platform built on top of what looked like an online résumé. At the time, when I was asked why I joined the company, I would tell them that it had always been true that success in business was based on what you know and who you know.  LinkedIn was just the modern incarnation of that powerful fact.

One of the most pleasant surprises in my current role at Wealthfront has been discovering how relevant career success is to millennial investors. As it turns out, every generation has grappled with the issue of how to find financial success, and millennials are no different.

What may surprise most people (including my compatriots in Gen X) is that more than any other generation, I believe that Millennials may have a lot to teach us. You see, it turns out that Millennials have figured out how to make that old adage actionable.

Who You Work With & What You Work On

Increasingly, as I talk to Millennials, some of whom who have found early success in their careers, and others who are just starting out, I hear the same things. This generation overwhelmingly associates success with control over who they work with, and what they work on.

There is an old refrain in management that people join companies, but they leave managers. There is a kernel of truth in that statement. However, in the modern workplace, relationships with colleagues, managers and leadership all have a role to play. Increasingly, valuable employees ask:

  • Am I learning from the people I work with?
  • Are we succeeding together as a team?
  • Do I share the same values as my colleagues?
  • Will I fight for them? Will they fight for me?

Driven by Passion, Seeking a Mission

There have been numerous surveys and studies indicating that Millennials are overwhelmingly focused on “their passions.” I think, in some regards, this has trivialized a more fundamental and important trend.

Is it really surprising that more and more people have realized that what you are working on matters?

The old duality of your work life and your personal life have been hopelessly intermingled. Instead of arguing about whether you live to work or work to live, in the 21st century people increasingly turning away from a purely mercenary view of their labor. They want to believe in the mission, believe their efforts are going towards something bigger than just financial reward. This is why you hear increasing anecdotes of young people choosing lower paying jobs, in some cases jobs that pay tens of thousands of dollars less, to focus on an organization that they draw more purpose from.

Success = Control

Not everyone has this luxury, and in some ways that is the point. What does success really mean, if it doesn’t mean that you get increasing control over who your work with, and what you work on?

Wealthfront now has over 12,000 clients, and most of them are under 35. What I find striking is that, overwhelmingly, with every success in their financial lives, these young people seem to immediately focus on using their success to gain control over their careers. They don’t seek to optimize for title, or  financial reward. Instead, they increasingly use their success to effectively fund the ability to work on a product they believe in, an organization they want to be part of, and a leader they want to follow.

As the CEO of a hypergrowth company, this leaves me with two pieces of actionable advice:

  • Financial reward is not enough. If you want to attract and retain the best and the brightest, financial reward is somewhat of a commodity, and an undervalued one at that. Instead, expect potential candidates to look at your company and ask, “Is this a problem I want to work on?” and “Are these people I want to work with?”
  • This is a networked economy. As Reid Hoffman has described, increasingly the value people build in their careers extends outside of your company. There is a material, and possibly essential difference, in a consumer business where your employees feel like they are punching a clock, versus a team that truly believes in what they are working on and the team they are working with. The influence of your employees, especially as your company grows, is under-measured, and as a result, under-appreciated. But in a huge networked economy, it may be the key to differentiated success.

The Future of Social Networking at Singularity U

/ Adam Nash

Last week, I was asked to give a guest lecture at Singularity University on the topic “The Future of Social Networking”

To frame the discussion, I chose to walk through the following structure:

  • Web 1.0 vs. Web 2.0
  • Social Networking as a disruptive platform
  • LinkedIn as an example of a social platform
  • Mobile as a disruptive accelerator for social platforms
  • Thoughts on future disruptions

On a personal note, I hadn’t actually been back to visit NASA Ames Research Center since my internship during my senior year in high school (21 years ago).  Back then, I was helping develop simulation software for fluid dynamics simulations in Fortran.  Thankfully, no one asked me to code in Fortran during the Q&A.

The team at Singularity U was incredibly gracious, and I appreciated the opportunity to talk to the class.

User Acquisition: Viral Factor Basics

/ Adam Nash / 18 Comments

This is the second post in a three post series on user acquisition.

In the first post in this series, we covered the basics of the five sources of traffic to a web-based product.  This next post covers one of the most important, albeit trendy, aspects of user acquisition: virality.

Lot-of-Rabbits

It’s About Users Touching Non-Users

Look at your product and ask yourself a simple question: which features actually let a user of your product reach out and connect with a non-user?   The answer might surprise you.

At LinkedIn, we did this simple evaluation and discovered that out of thousands of features on the site, only about a half-dozen would actually let a user create content that would reach a non-user. (In fact, only a couple of these were used in high volume.)

I continue to be surprised at how many sites and applications are launched without having given careful thought to this exactproblem.  Virality cannot easily be grafted onto a service – outsized results tend to be reserved for products that design it into the core of the experience.

Useful questions to ask, from a product & design perspective:

  • How can a user create content that reaches another user?
  • How does a users experience get better the more people they are connected to on it?
  • How does a user benefit from reaching out to a non-user?

Understanding Viral Factors

One of the most useful types of metrics to come out of the last five years of social software is the viral factor.  Popularized by the boom of development on the Facebook platform in 2007, a viral factor is a number, typically between 0.0 and 1.0.  It describes a basic business problem that affects literally every business in the world:

“Given that I get a new customer today, how many new customers will they bring in over the next N days?”

“N” is a placeholder for a cycle time that makes sense for your business.  Some companies literally track this in hours, others 3 days, or even 30.  Let’s assume for now that 7 is a good number, since it tells you given a new customer today, how many new customers will they bring in over the next week.

Basic Viral Math

The good news is, once you identify the specific product flows that allow users to reach non-users, it’s fairly easy to instrument and calculate a viral factor for a feature or even a site.  But what does the number really mean?

Let’s assume a viral factor of 0.5, and an N of 7.  If I get a new user today, then my user acquisition will look like this over the next few weeks:

1 + 0.5 + 0.25 + 0.125 ….

It’s an infinite series that adds up to 2.  By getting a new user, the virality of this feature will generate a second user over time.

Two obvious epiphanies here:

  • A viral factor is a multiplier for existing sources of user acquisition.  0.5 is a 2x, 0.66 is a 3x, etc.
  • Anything below 0.5 looks like a percentage multiplier at best.

What about a viral factor of 1.1?

One of the memes that started to circulate broadly in 2008 was getting your viral factor to “1.1”.  This was just a proxy for saying that your product or service would explode.  If you do the math, you can easily see that any viral factor or 1.0 or higher will lead to exponential growth resulting in quickly having every human on the planet on your service.

I don’t want to get into a Warp 10 debate, but products can in fact have viral factors above 1.0 for short periods of time, particularly when coming off a small base.

Learning from Rabbits

The key to understanding viral math is to remember a basic truth about rabbits.  Rabbits don’t have a lot of rabbits  because they have big litters.  Rabbits have a lot of rabbits because they breed frequently.

When trying to “spread” to other users, most developers just focus on branching factor – how many people they can get invited into their new system.  However, cycle time can be much more important than branching factor.

Think of a basic exponential equation: X to the Y power.

  • X is the branching factor, in each cycle how many new people do you spread to.
  • Y is the number of cycles you can execute in a given time period.

If you have a cycle that spreads to 10 people, but takes 7 days to replicate, in 4 weeks you’ll have something that looks like 10^3.  However, if you have a cycle that takes a day to replicate, even with a branching factor of 3 you’ll have 3^27.  Which would you rather have?

In real life, there is decay of different viral messages.  Branching factors can drop below 1.  The path to success is typically the combination of a high branching factor combined with a fast cycle time.

As per the last blog post, different platforms and traffic channels have different engagement patterns and implicit cycle times.  The fact that people check email and social feeds multiple times per day makes them excellent vectors for viral messages.  Unfortunately, the channels with the fastest cycle times also tend to have the fastest decay rates.  Fast cycle times plus temporary viral factors above 1 are how sites and features explode out of no where.

Executing on Product Virality

To design virality into your product, there really is a three step process:

  1. Clearly articulate and design out the features where members can touch non-members.  Wireframes and flows are sufficient.  Personally, I also recommend producing a simple mathematical model with some assumptions at each conversion point to sanity check that your product will produce a strong viral factor, layered over other traffic sources (the multiplier).
  2. Instrument those flows with the detailed metrics necessary for each step of the viral cycle to match your model.
  3. Develop, release, measure, iterate.  You may hit success your first time, but it’s not unusual to have to iterate 6-8 times to really get a strong viral factor under the best of conditions.  This is the place where the length of your product cycles matter.  Release an iteration every 2 days, and you might have success in 2 weeks.  Take 3-4 weeks per iteration, and it could be half a year before you nail your cycle.  Speed matters.

You don’t need hundreds of viral features to succeed.  In fact, most great social products only have a few that matter.

What about mobile?

Now that we’ve covered the five scalable sources of web traffic and the basics of viral factors, we’ll conclude next week with an analysis of what this framework implies for driving distribution for mobile web sites vs. native applications.

User Acquisition: The Five Sources of Traffic

/ Adam Nash / 12 Comments

This is the first post in a three post series on user acquisition.

The topic of this blog post may seem simplistic to those of you who have been in the trenches, working hard to grow visits and visitors to your site or application.  As basic as it sounds, however, it’s always surprising to me how valuable it is to think critically about exactly how people will discover your product.

In fact, it’s really quite simple.  There are only really five ways that people will visit your site on the web.

The Five Sources of Traffic

With all due apologies to Michael Porter, knowing the five sources of traffic to your site will likely be more important to your survival than the traditional five forces.  They are:

  1. Organic
  2. Email
  3. Search (SEO)
  4. Ads / Partnerships (SEM)
  5. Social (Feeds)

That’s  it.  If someone found your site, you can bet it happened in those five ways.

The fact that there are so few ways for traffic to reach your site at scale is both terrifying and exhilarating.  It’s terrifying because it makes you realize how few bullets there really are in your gun.  It’s exhilarating, however, because it can focus a small team on exactly which battles they need to win the war.

Organic Traffic

Organic traffic is generally the most valuable type of traffic you can acquire.  It is defined as visits that come straight to your site, with full intent.  Literally, people have bookmarked you or type your domain into their browser.  That full intent comes through in almost every produto metric.  They do more, click more, buy more, visit more, etc.  This traffic has the fewest dependencies on other sites or services?

The problem with organic traffic is that no one really knows how to generate more of it.  Put a product manager in charge of “moving organic traffic up” and you’ll see the fear in their eyes.  The truth is, organic traffic is a mix of brand, exposure, repetition, and precious space in the very limited space called “top of mind”.  I love word of mouth, and it’s amazing when it happens, but Don Draper has been convincing people that he knows how to generate it for half a century.

(I will note that native mobile applications have changed this dynamic, but will leave the detail for the third post in this series.)

Email Traffic

Everyone complains about the flood of email, but unfortunately, it seems unlikely to get better anytime soon.  Why?  Because it works.

One of the most scalable ways for traffic to find your site is through email.  Please note, I’m not talking about direct marketing emails.  I’m referring to product emails, email built into the interaction of a site.  A great example is the original “You’ve been outbid!” email that brought (and still brings) millions back to the eBay site every day.

Email scales, and it’s inherently personal in its best form.  It’s asynchronous, it can support rich content, and it can be rapidly A/B tested and optimized across an amazing number of dimensions.  The best product emails get excellent conversion rates, in fact, the social web has led to the discovery that person to person communication gets conversion person over 10x higher than traditional product emails.  The Year In Review email at LinkedIn actually received clickthroughs so high, it was better described as clicks-per-email!

The problem with email traffic generally is that it’s highly transactional, so converting that visit to something more than a one-action stop is significant. However, because you control the user experience of the origination the visit, you have a lot of opportunity to make it great.

Search Traffic

The realization that natural search can drive traffic to a website dates back to the 90s.  However, it really has been in the past decade in the shadow of Google that search engine optimization scaled to its massive current footprint.

Search clearly scales.  The problem really is that everyone figured this out a long time ago.  First, that means that you are competing with trillions of web pages across billions of queries.  You need to have unique, valuable content measured in the millions of pages to reach scale.  SEO has become a product and technical discipline all it’s own. Second, the platform you are optimizing for (Google, Microsoft) is unstable, as they constantly are in an arms race with the thousands of businesses trying to hijack that traffic. (I’m not even going to get into their own conflicts of interest.)

Search is big, and when you hit it, it will put an inflection point in your curve.  But there is rarely anysuch thing as “low hanging fruit” in this domain.

Advertising (SEM)

The fourth source of traffic is paid traffic, most commonly now ads purchased on Google or Facebook.  Companies spend billions every year on these ads, and those dollars drive billions of visits.  When I left eBay, they were spending nearly $250M a year on search advertising, so you can’t say it doesn’t scale.

The problem with advertising is really around two key economic negatives.  The first is cash flow.  In most cases, you’ll be forced to pay for your ads long before you realize the economic gains on your site.  Take something cash flow negative and scale it, and you will have problems.  Second, you have solid economics.  Most sites conjure a “lifetime value of a user” long before they have definitive proof of that value, let alone evidence that users acquired through advertising will behave the same way. It’s a hyper-competitive market, armed with weapons of mass destruction.  A dangerous cocktail, indeed.

While ads are generally the wrong way to source traffic for a modern social service, there are exceptions when the economics are solid and a certain volume of traffic is needed in a short time span to catalyze a network effect.  Zynga exemplified this thinking best when it used Facebook ads to turbocharge adoption and virality of their earlier games like FarmVille.

Social Traffic

The newest source of scalable traffic, social platforms like Facebook, LinkedIn and Twitter can be great way to reach users.  Each platform is different in content expectations, clickthrough and intent, but there is no question that social platforms are massively valuable as potential sources of traffic.

Social feeds have a number of elements in common with email, when done properly.  However, there are two key differences that make social still very difficult for most product teams to effectively use at scale.  The first is permission.  On social platforms, your application is always speaking through a user.  As a result, their intent, their voice, and their identity on the platform is incredibly important.  Unlike email, scaling social feed interactions means hitting a mixture of emotion and timing.  The second issue is one of conversion.  With email, you control an incredible number of variables: content, timing, frequency.  You also have a relatively high metrics around open rates, conversion, etc.  With social feeds, the dynamics around timing and graph density really matter, and in general it always feels harder to control.

The Power of Five

Eventually, at scale, your site will likely need to leverage all of the above traffic sources to hit its potential.  However, in the beginning, it’s often a thoughtful, deep success with just one of these that will represent your first inflection point.

The key to exponential, scalable distribution across these sources of traffic is often linked to virality, which is why that will be the topic of my next post.

Product Leaders: User Acquisition Series

/ Adam Nash / 8 Comments

I can be pedantic about user acquisition.  The truth is that consumer web and mobile applications are under increasing pressure to demonstrate explosive exponential traction.  Building a great product is no longer sufficient, lest you be left with the best product in the world that no one has discovered.

As an engineer and designer by training, I didn’t always put this level of focus on traffic acquisition.  It wasn’t until we tried to build an entirely new site under the eBay brand (eBay Express) that I was forced to focus our team’s efforts on one large fundamental challenge: traffic acquisition.

Those struggles, some successful (and some not) led me to appreciate how profoundly the social web changed the metrics of distribution.  When we founded the growth team at LinkedIn in 2008, we were able to structure our thinking around user acquisition, measure it, and bend the curve significantly for the site. 

A special thanks to both Reid Hoffman and Elliot Shmukler, who both contributed significantly to my thinking on the subject.

History is Written by the Victors

History is written by the victors, and on the consumer web, victory is often defined by market distribution.  Growth does not just happen, it has to be designed into your product and service.

The following posts attempt to capture some of the fundamentals that I’ve personally found useful to structure thinking around social user acquisition, and extend those concepts from the web to mobile applications:

Remember, Product Leaders win games.  Now let’s get started.

How to Make Great Green Beer for St. Patrick’s Day

/ Adam Nash / 2 Comments

You learn a lot of things at a hypergrowth startup, mostly by doing.  For some reason, I love St. Patrick’s Day. St. Patrick’s Day wasnt always a big event at LinkedIn, at least until we figured out how to make green beer.

It may sound trivial, but making a great green beer is surprisingly delightful.  Throw in a leprechaun hat, some Irish whiskey, and a warm afternoon, and you’ve got yourself a party.

Step 1: The Beer

We tried quite a few varieties, but what you are really looking for is a bright, vibrant yellow color to start with.   Most people were happiest with Corona, although Beck’s was also popular.  Wheat beers tend to be too cloudy, and anything darker tends to look swampy.

(Listen, I know Corona doesn’t scream Irish, but we’re going for effect here.)

Step 2: Supplies

Before you can have your event, you need to assemble the following:

  • Case(s) of beer.  Theoretically could get a keg, but our parties were never that big.
  • Bottle openers.
  • Clear, 16 ounce plastic cups.
  • Green food coloring, liquid.

Step 3: The Process

The workflow is simple, but this detail is important.

  1. Put two (not one, not three) drops of food coloring in the bottom of a cup
  2. Open the beer
  3. Pour liberally, to get good mixing and a bit of a head

That’s it.  The magic is that you get almost perfect color distribution pouring the beyou over the food coloring.  Adding the food coloring afterward, even with stirring, is a giant fail. You won’t get what you want.

The Results

Happy St. Patrick’s Day! 🍀

Pinterest & LinkedIn: Identity of Taste vs. Expertise

/ Adam Nash / 4 Comments

It’s hard to go three feet in Silicon Valley these days without someone commenting on the phenomenal engagement and growth being seen from Pinterest and other curation-based social platforms.  What’s a bit surprising to me, however, is how many people refer to this demand as a growing interest and search for “expertise”.

As I have a passion for finding a more human understanding for what drives engagement in real life and then mapping it to online behavior, I think the use of the term “expertise” here is misleading.  Instead, I believe what we are seeing is an explosion of activity around an incredibly powerful form of identity and reputation: the identity of taste.

Expertise is Empirical

If you go to LinkedIn, you see a site that is rich with the identity of expertise.  LinkedIn has rich structured data around sources of expertise: degrees, schools, companies, titles, patents, published content, skills.  They also have rich sources of unstructured content about job responsibilities, specialties, questions & answers, group participation, status updates and comments.  There are even implicit indications of expertise related to other online identities (like Twitter) and relationships to other people with expertise (connections).

This expertise can be tapped by using LinkedIn’s incredibly powerful search engine, either on site or via API, or by browsing the talent graph displayed in catalog form on LinkedIn Skills.  Github has created a powerful identity for developers based on their actual interests and contributions in code.  Blogs, Tumblr, Quora and Twitter have helped people create identities based on the content they create and share.

The power of identity based on expertise is that it is concretely demonstrated.  Education, experience, content and relationships are all very structured and concrete methods for measuring and assessing expertise.  However, in some ways, expertise is limited by it’s literal nature.  Factual. Demonstrable. Empirical.

Taste is Inspiring

Pinterest, however, has unlocked an incredibly powerful form of reputation and identity that exists in the offline world – an identity of taste.  People don’t care about the expertise of people who are assembling pinboards.  They care about how those combinations make them feel – the concept, the aggregation, the flow of additions.  The Pinboard graph begins for most people with their friends, but people quickly learn to hop based on sources to people they don’t know, finding beautiful, interesting, intriguing or inspiring collections of images.

This isn’t an identity based on expertise, really.  It’s not even clear how closely related it is to a graph of interests. Curation-based social platforms evoke a different phenomenon, and with it, some very powerful emotions and social behaviors.

Taste is different than expertise.  Taste does not imply that you are a good person or a deep well of expertise on the domain.  Taste is not universal, although there are certainly those with a predilection for influencing and/or predicting the changes in taste for many.  But when we as human beings find people whose taste inspires us, it’s a powerful relationship.  We map positive attributes to them, ranging from kindness to intelligence to even authority.  Fame & taste are often intertwined.

You Are What You Curate

Curation-based social platforms are based on the interaction of three key factors:

  1. A rich, visual identity and reputation based on curated content
  2. An asymmetric graph based on not only following people, but specific feeds of curated content
  3. A rich, visual activity stream of curation activity

It’s the first item that I seem to see most under-appreciated.  Vanity, as one of the most common deadly sins in social software, drives an incredible amount of engagement and activity.  As people are inspired by those who create beautiful identities of curated content, they also become keenly aware of how their curated identity looks.  When people signal an appreciation for their taste, it triggers power social impulses, likely built up at an early age.

This, more than anything else, reflects the major step function in engagement of this generation of curation over previous attempts (anyone remember Amazon Lists?)

How Does Taste Factor into Your Experience?

I always like to translate these insights into actionable questions for product designers.  In this case, these are some good starting points:

  • How does taste factor into your experience?
  • Is the identity in your product better served by reputation based on taste or expertise?
  • Are the relationships in your product between users based on taste or expertise?
  • Are you creating an identity visually and emotionally powerful enough to trigger curation activity?
  • Are you flowing curation activity through your experience in a way that stimulates discovery and the creation of an identity of taste?

Don’t underestimate the power of good taste.