my values as an investor: an open letter to founders

dear founders,

over the past few years, i have invested small amounts of money where the founders have given me an opportunity to do so. for each such opportunity to share in their quest, i have learnt something – and i am thankful.

as i talk to the founder(s) and the team, i find that some teams are naturally curious and want to know why i’d invest and what my relationship to that startup would be. one word that rarely gets used in these conversations and questions is ‘values’. i have written previously about startup values and as an investor, want to make sure that founders talking to me about angel/seed investments understand my values.
my values are expressions of some simple viewpoints and actions i strive to live by and bring to the table as an investor. these are:

  • are you taking enough risk?
  • optimize for the long term – always.
  • do I identify with, understand, and agree with your mission, not just your idea, technology, products, and startups.
  • the small amount of money ($5K to $50K) i invest carries with it the ability to turn to zero or be padded with zeroes. if it enabled you to make an effort you couldn’t otherwise make, it will be well spent.
  • while i will make an effort to help whichever way I can, you should understand that:
    • i am not your product manager
    • i am not your rolodex. access without context means nothing.
    • i am not a visionary. i am investing in your vision which is tuned constantly, by every day interaction with your users, technologies, products, and your peers. chase what you see, not what i or others ask you to chase.
  • i have failed many times at many things. i have learnt from failures. successes taught me more, but failures caused me to learn more.
  • while you focus on user growth and customer associated metrics, don’t lose sight of personal growth metrics.  i pay particular attention to personal and inter-personal growth within your startup.

and finally, the most important metric for me – your success as a founder isn’t measured in dollars raised or valuation or money earned for investors, it is measured in how many other people did you make successful. this is my yardstick for a founder.


On relevance, guided discovery, and curating commerce for serendipity


a venn diagram

Relevance is one of the most sought after qualities for any kind of content presented to a user. Clicks are a user’s declaration of relevance within our conventional browser UX for presenting content, media, news, and information. Relevance becomes a critical tool for navigating information as the amount of information available on the Internet grows every second. Measured in terms of physical size, we are approaching ‘Nebula‘ scale, measured in lightyears for the amount of information available on the internet today.

Presented with this interstellar scale of information, the challenge in navigating the mass of information is no less daunting than figuring out information-entropy (Shannon entropy) of online content filtered/ranked by relevance. Put another way, all information is high entropy (high uncertainty) unless sorted, presented by relevance to each user.

Ideally, all content should be customized such that the presented content is relevant to that particular user and more likely to engage the user without requiring inefficient actions (searching, clicking, scrolling) on the part of the user or requiring a constant declaration of relevance on every tab and every site.

In this post, I attempt to understand how relevance works for content recommendations on some of the big sites and examine applying this model of determining relevance to commerce online.

In the context of relevancy, the 2D wall of content at Pinterest is very conducive to more browsing but not necessarily deeper engagement as content is not sorted (or sortable) by relevance. While categories help, they are not personalized and presentation of content does not sense any other evanescent declaration of user interest on their site or other sites. Thus, it is clear that:

Relevance != Social Proof

Quora’s UX surfaces high quality but not necessarily high relevance by relying on democratic votes (1 vote per user regardless of their Quora-ranking/clout/points). As their product evolves, I hope we will see more relevance – perhaps by picking topics as well people of interest. This is a form of declared relevance relying on declaration made by the user, not necessarily determined by a user’s ongoing interaction with content on the site. The takeaway:

Relevance != Quality of Content

Twitter’s #Discover tab is the most advanced relevance-filter yet with its mix of tweets by people you follow as well as people who share your interests as determined by cookie tracking on sites you visit + interests of people you follow. I think this is the closest determination (ongoing) of relevance in an online product.

Relevance = A mix of [Social Proof + Quality + Personalized-Interest matched Content + …]

Relevance and Commerce: curating for serendipity

While Google, Twitter, and to some extent Quora address relevance for the world’s entire corpus of information, e-commerce companies can and should apply similar techniques to determine the right products for the right buyers. While narrowing down choices presented to a potential buyer or browser, the content selection should permit some amount of delightful discovery. This need for counterbalancing narrow, algorithmic selection and presentation speaks to the emotional part of a user’s browsing experience.

Paraphrasing Tufte, all design is choice – and a failure to engineer correct information flow underlying presentation [balancing relevance vs. discovery] will surely result in clutter and confusion. The balancing act for narrow relevance in commerce is serendipity – let the user discover adjacent information/products albeit in a delightful way. And thats where I think we’re headed in commerce – augmenting relevance with sufficient serendipity to deliver the right user experience. While algorithms do well with determination and tracking social proof, quality, personalization using user-interests, serendipity requires blending in a measure of user and domain-expert curation. And, therefore

Relevance + Serendipity = Algorithms & Machine Learning + User curation + Expert Curation

Within online commerce, there have been three broad waves of innovation:

Wave 1: Digitization of product information, browsing, and fulfilment

Amazon is clearly the best example of this class of innovation with its broadly horizontal digitization of product information followed by a simple layer of product-interest matching and recommendations. If you saw product X, you may also be interested in product Y where Y may be the most viewed/purchased item along with X. There are no social or other user-level connections that Amazon seems to use other than the user’s history on its site. Currently it presents six items in at least six categories if I visit the homepage (logged in). It hasn’t even asked me a style wizard to narrow down ‘recommendations’ or increase relevance to me.

Wave 2: Propelling discovery by economic compulsion (ok, by surfing the curves of indifference)

Groupon and other daily-deal sites induce discovery by providing an economic compulsion for users. These intermediaries harvest a user at their point of indifference in the face of compelling economic value for the presented product. With enough data points, Groupon et al will have their own version of consumer demand curves. I expect they will move beyond offering a single daily-deal towards a smorgasbord of carefully chosen goods that are seen as acceptable substitutes given a certain budget constraint. They certainly have vast consumer purchase data to do so within local commerce – a valuable dataset vs. Amazon which is purely online. Groupon Goods, I hope is the first move in this direction. If I was at Groupon, I would hire Economists as well as statisticians and data-scientists to figure out indifference curves and match it to a variety of local commerce.

Wave 3: Guided discovery – engineering serendipity

Faced with an unprecedented data storm, consumers need/want fewer choices but the right choices. Balancing this need for narrow personalization is serendipity. Serendipity is pleasant and welcome because it helps users make a useful discovery even though they were not explicitly not looking for it. This middle ground is guided discovery. Lets examine how information/content sites deal with engineering for serendipity.

Serendipity doesn’t happen on a Google search results page as a user (and PageRank) explicitly rules it out in favor of surfacing the information users are searching for from a sea of information.

Amazon recommendations hint at some serendipity but is strictly dependent on user’s previous purchases, items browsed, and most popular items related to a user’s purchases. The form of guided discovery on Amazon doesn’t leverage a user’s behavior or interest-profiles that exist elsewhere.

Pinterest at this point (May 2012) is random serendipity which is not very time-efficient pursuit for the user though it yields great time-on-site and other vanity metrics for Pinterest. In effect, there is no incentive for Pinterest (yet) to boost relevance vs. pageviews. Guided discovery only takes place along canned categories or along content classified by the users in various boards.

Quora in some ways is guided-serendipity by walking the user along the axis of quality content. The only axis of serendipitous discovery is following people and their Questions/Answers/Boards/Posts. If one could do Quora score/votes based recommendations for products/brands and integrate some level of sentiment analysis of Quora answers, it could become a compelling front-end for products with better insights vs. Consumer Reports.

Twitter brings together some nice elements of guided discovery by mapping interests, people, and recent events/topics of interest to your chosen geography at city/national levels of the twitterverse. I think Twitter is ideally placed to guide users towards all kinds of media in addition to news and discussions. It can help me find media, content, news, and information based on:

  • Interests I follow (on/off Twitter)
  • People I follow
  • Interests of People I follow
  • Activities of People I follow (people followed by them, their retweets, favorites, …)

As far as I know, there are no equivalent efforts in online commerce applying data mining based recommendations to guide the users towards the right mix of guided and serendipitous discovery. Merely suggesting some ‘recommendations’ in a side-bar don’t suffice. What we need is a relevance based content-display and navigation system.

This I believe is the next big wave of commerce – data curated commerce to help the users browse less, find more.



The best question VCs can ask you and you can ask VCs.

When founders and startups meet with Venture Capitalists, Angel investors, or potential advisors, most of the time is spent talking about the founder’s insights, technology, product, or the market they intend to innovate, disrupt, or create. In my experience across both sides of the money-table as a VC and as a founder, the hardest and the most insightful question is often not about the knowledge founders or startups have, but rather, what have they learnt. This concise question embodies just about everything the VCs want to know about you as well as your company.

What you “know” is the platform that you stand upon and the framework for building your product. What you “learnt” is the  valuable part that allows you to create something of value, hopefully – a lot of value – for your customers. This is where you have the opportunity to figure out something that others have not understood yet. Thus, ‘learning’ is your unfair edge in an otherwise irrational pursuit where the odds are against you most of the time till you trump them with your learning, not knowledge.

If knowledge is velocity, what you have learnt determines your acceleration, i.e. the second derivative.

(Thanks @jessefarmer)

This seemingly simple question is in fact quite complex. When a VC asks you this question, they are judging multiple things at the same time:

what does it tell them about your learning style and pace of learning
what does it say about your willingness to learn
what does it say about your willingness to fail while learning
how does it educate them about your market, your technology area, your competitors

And when VCs ask this question of their portfolio companies, they are keenly focused on the acceleration (or deceleration) of your company, not the somewhat static ‘knowledge’ you started off with when they invested.

I also think this is also the question founders should ask potential investors. Rather than talk about fund size, investing philosophy, market-trends,.. (all things you must know before meeting them), ask them the following two questions:

1. What have they learnt in the past 2 years.
2. What new behavior, investments, or market developments do they expect to occur given that learning.

If you hear answers that are rambling, unfocused, or evasive, it will tell you more than their past record or their current investing ‘thesis’.

When you hear clueful answers, it should signal to you that the VC asking this question is more likely to be thinking ‘long-term’ vs. ‘flavor of the day’. VCs that can discuss what they have learnt and how they see it influencing the next few years are rare and good for early stage startups.

p.s. The words ‘learnt‘ and ‘learned‘ are interchangeable here. i have a preference for using ‘learnt’, having learnt my english language skills reading newspapers and listening to the BBC in India and later during graduate studies in Canada. “learned” is the more commonly used form of the word in U.S.A.



Picking Advisors for Your Startup

Somewhere in the entrepreneurial journey from an idea to a startup, founders will often meet friends and colleagues to brainstorm and develop their ideas. In some of these conversations “Oh I think you should meet XYZ person who’d be great for feedback” event happens multiple times. Some of these people are potential advisors for your startup. Here are some thoughts on how to think about advisors at various stages of the idea-to-company odyssey.

Remember your Advisor’s job is to help you make non-obvious choices in the face of imperfect and sometimes non-existent data. Recruit accordingly.

The Six Cardinal Directions of Effective Advisors

1. The most important skill an advisor can bring to you and your idea is a way to improve your idea by asking you the right and often ‘hard’ questions. People who want to replicate the success they had even if in the same area as your startup by repeating the same approach/execution/recipe are not the right ones for you. Beyond the usual “Oh Its nice” or “Its great” responses, listen for something that signals that your idea made them think. If they then come back with questions you haven’t yet asked yourself, they may be a good match as an advisor.

2. Don’t confuse mentor with advisor. Mentors are a rare breed of individuals. They are good at asking questions and making you learn regardless of what they or you are working on. Conflating the two may not necessarily be good for you or your  startup.

3. How do they talk about failure and what they’ve learnt from the failure matters as much as what they’re successful at. Ask them what they have learnt in the last three years as a result of a failure that has now changed their thinking or behavior in a meaningful way.

4. Make sure you ask them if they have played the role (paid in equity usually) with at least one other startup. You want to ensure that they are not going to play ‘Product Manager’ for you with good intentions and potentially disastrous results. Advisors are not going to invent your product or your market or your product-features. They can be invaluable in pointing out the voids in your product strategy or feature-list or competitive dynamics. Advisors who are good at pointing out what doesn’t exist are often far more helpful than the ones who suggest a specific feature or two.

5. Ask them for a specific commitment of time, effort, and introductions you expect from them over the first year of your collaboration. Introduce them to your other advisors and create some opportunities for them to collaborate – enabling them to think beyond their usual domain is effectively delightful compensation for them beyond the equity you will give them.

6. Your advisors are not your investors. Keep these two roles separate. While there may be some overlap, they have distinct responsibilities for you and your startup.

The Entourage Approach

For certain startups and founders, an ‘entourage’ may be more appropriate which functions as early adopters and influencers in your marketplace. Perhaps the best example of this approach was where @tonysphere and other founders were well connected and signed up 26 advisors to help them push to a million users within a year and an acquisition by AOL. If you’re not as well connected as the fine folks at, this may not be the way to go. A weak entourage is baggage, not balloons.

Advisor Compensation

I will write about Advisor compensation in a future post but here are some guidelines for silicon valley startups:
for early stage (between idea stage and funding) formal advisors, expect to share about 1% equity which goes down to approx 0.25% for seed-funded startups and often between 0.1 and 0.25% for developing stage startups. Typically the equity vests monthly over a year without any cliff and there is no other compensation (e.g. cash).

Facebook Lessons for Startups & Founders

Facebook filed their S-1 with SEC on February 1, 2012 and triggered yet another round of discussions in the valley digirati and digirazzi alike.  From computations of founder stakes to opinions on investment, tech and popular media made sure no one missed any aspects of the filing.

So what does it mean (If anything) for current and future founders of tech startups? Success at this scale – adoption, financial success, and pioneering a new segment of communications is rare and deserves much praise. The founders in this case – from Zuckerberg to Parker, Moskovitz, and even the Winklevii deserve all the praise they get for playing a role in the success.

Your first few employee matter a lot more than you think

I would also like to point out the critical role played by the first tens of engineers (hackers if you will) in building Facebook. Less heralded and often ignored all together by the media, this corps of engineers in my opinion deserves as much praise as the ones grabbing headlines in the press. Without the efforts of this group, Facebook could not have made it – founder foresight/passion/skills notwithstanding. Referred to as ’employees’ this group is as much of a co-founder as ‘the founder’ himself. They took nearly the same risks, likely contributed as much to product, platform, and technology, and helped it get from its early success to a product whose expansion beyond .edu domain was one of the most eagerly awaited consumer product introductions ever.

For founders, the aspects worth emulating aren’t the ones highlighted by blogs and media today – try and focus on the early parts of the arc of Facebook’s success. You will find many of the traits espoused by Eric Ries and Steve Blank when you examine the first year or so at Facebook (2004-2006). Some of the ones that stood out for me:

Build fast, release early, Find your Market-fit.

Famous for putting out the first iteration of the kernel of ‘TheFacebook’ in a week, this is a great example of lean development and testing market-fit. It wasn’t the first iteration either – Facemash which was a hot-or-not style site/application that Zuckerberg built prior to Facebook at Harvard and saw immediate adoption. Remember that hot-or-not was a circa 2000 phenomenon and Facebook’s first iteration was in 2004.

Focus on Users; user-adoption, user-experience.

In 2005, the valley was hearing whispers about Facebook and how Accel “went and got the deal” at an unheard of valuation (remember we were just coming off the dark years of 2002-2003), no one talked about Facebook’s technology or its platform or how it may one day be the dominant social-connector and app-platform.  But the first line one heard about Facebook was how many users they had, how much time these users were spending on Facebook, and the rapid growth rate that was easily the highest for any consumer app. This was a dramatic contrast with Google where the talk was about the outstanding infrastructure and how that gives them a unique advantage vs. everyone else in search and advertising. Unless you are building an application that needs to invent new systems and infrastructure, stay focused on users. Adoption will enable you to invent a platform and plenty of technology once you’re successful.

Surround yourself with people smarter than you

Graduating from a Harvard dorm room to University Avenue in Palo Alto, Facebook continued to find and learn from some of the best in their domain – whether it was Zuckerberg learning from Don Graham (Washington Post) or the stellar list of its board members and investors, it didn’t just happen by accident. I am not saying Zuckerberg is not smart, I am saying one of his smartest moves was to find people smarter than him at that point in time about an aspect of his startup. For founders, the clear lesson is find and pitch the smartest people you can find. I suggest a simple approach to accomplishing it:

When you meet prospective VCs (Partners or Associates) or Advisors, ask them to introduce you to two other people that they think are the smartest in the business.  Be persistent and chase down these introductions, turn them in to meetings, and ask them to introduce you to two more in turn.  In a few months you should be able to meet with enough people to learn from and who can be potential investors, advisors, or informal-advisors to your startup.

Think long term

This one is the easiest point to state and the hardest to follow. I believe there is a fair value at every step for a startup  if they have taken angel/venture money. And  they must be responsible in considering any offers that come their way. I also believe there is much (realizable) value in finding a way not to take that offer. Each such situation is unique but do consider that if you can find a way to build more value, you will have a chance to deliver life-changing rewards for yourself, your team, and your investors.

You know what’s cool? A Billion users. 

Building a startup that delivers a Billion+ in profits eight years after starting is Cool. But do you know what’s really cool – that Zuckerberg’s efforts changed and enriched the lives of thousands of employees and millions of users. A founder’s measure isn’t the capital they return or create, it is the number of lives they touch, improve, and change.

If all you wanted to make was money, there are easier paths to realize that goal. Be a founder if you want to make a difference. Money will follow.