If you’re an entrepreneur or are thinking about starting a company, Steve Blank’s blog is must-read material.

Steve’s latest series of posts establishes the reasons why Customer Development and Lean Startup methodologies are so important (and why prior models of startup development often resulted in failure).  Read them in order:

The Leading Cause of Startup Death

Customer Development Manifesto Part I

Customer Development Manifesto Part II

Customer Development Manifesto Part III

Customer Development Manifesto Part IV

See my last post for context:  http://framethink.wordpress.com/2009/08/08/what-does-an-eir-do/

There are some really great benefits that come from being associated with a venture fund as an entrepreneur-in-residence (EIR).

EIRs have a unique position that makes it easier to launch a company.  In some ways, being an EIR actually inverts the typical resource-gathering exercise that most entrepreneurs go through — the partners at a venture firm will often pitch ideas to their EIR’s and they continuously introduce their EIR’s to interesting and talented people who could be potential co-founders or business partners.  The first time that happened to me as an EIR, I was completely bowled over by the fact that a venture capitalist was actually pitching me on an idea instead of the other way around — it’s an interesting role reversal to say the least!

EIR roles are also fantastic for research.  EIR’s get direct access to their firm’s partners for feedback, advice, and brainstorming. They get to sit in on business pitches and help evaluate them from the VC’s perspective.  Participating in pitches and listening to how your venture firms partners think about companies is a truly precious learning experience…  Think about how many VC pitches you might be involved with directly as an entrepreneur — through the span of an entire career, how many VC pitches do you think might give?  Ten?  Twenty?  An EIR might get to see that many pitches within a few weeks if they wanted to.  Getting exposure to that volume of pitches in a compressed time frame really helps an EIR develop a comparative study of business pitches and gives you an opportunity to see what happens when teams come in to pitch in various states of preparedness & maturity, with varying styles, and different team compositions.   With full advantage of those learnings and direct access to their firm’s partners, an EIR should end up with a very good understanding of what pitches will work for their firm (and which ones won’t).

And let’s not forget the great fringe benefits of being at a venture fund!  Most VC’s have very nice office buildings that are quiet, secure, ergonomic places to work (much nicer than trying to do conference calls while hunched over a noisy cafe table).  Firms always have free snacks, coffee, and sodas to power you through long days.  Plus they have comfy couches to crash on after that all-nighter.

It’s not all sugar and spice, though — there are serious downsides to being an EIR, too…

It’s seductively easy to hang out in a swanky office, sit in on meetings all day long, listen to other entrepreneurs pitch, and dispense your opinions.  It’s fun to play “the connector” role — introducing that entrepreneur you met at a conference to the firm’s partners.  The partners appreciate it.  The entrepreneur who is raising a round really appreciates it.  And you get to give your ego a smug pat on the back for being so smart and well-connected.  All of that is so fun and easy that an EIR might literally spend entire days taking calls, doing meetings, vetting ideas, and introducing people (mea culpa).  That may be fine if the EIR is trying to add value to the firm by essentially playing an associate’s role, but definitely is not helping the EIR directly learn about use-cases that a customer would actually pay for or launch a new company per se.  So there is this unfortunate but very real tension between spending time helping the firm vs. working on launching a new venture.

This notion of the balance between an EIR’s firm vs. an EIR’s startup leads me to the The One Big Risk for EIRs…

The tension between firm vs. EIR becomes most apparent if/when the entrepreneur seeks financing for their new startup.  VentureHacks would tell you (and I would agree) that the key to closing a financing quickly with favorable terms is to have a strong BATNA.  But an EIR is at a fundamental disadvantage in getting their company favorable financing terms relative to a non-EIR making the exact same pitch…  because EIRs have a harder time creating strong BATNAs.  Why?  There is a fundamental information asymmetry between an EIR’s host firm and other venture firms.  Whether or not the EIR’s host firm actually does know more about the EIR and her/his company, they appear to have access to much deeper information about the EIR’s deal than other venture firms do.  So, as such, if an EIR’s firm does not participate in an EIR’s deal, then you can imagine the partners at other firms wondering: “What does this EIR’s host firm know that we don’t know?” , “There’s got to be something wrong with this deal…” or “Maybe there’s something wrong with the EIR her/himself!”  This information asymmetry gives an EIR’s host firm a strong upper-hand in financing negotiations.  That dynamic can prevent other investors from participating in what otherwise would have been a “fundable” deal or cause them to come in with reduced commitment at lower pre-money valuations.  Every EIR I’ve spoken with has said that their firm brought them in with a promise of “no strings attached, you can work with whomever you want” — but when it was fundraising time, everyone felt palpable pressure to do the deal with their host firm.  Usurious firms can take advantage of an EIR’s lack of negotiating leverage to drive down pre-money valuation and thereby inflate their post-money stake in the firm.  Even well-meaning firms that have great relationships with their EIRs may cause an EIR’s company to accept sub-optimal valuations if the EIR fails to create a market for their shares as aggressively as a typical (non-EIR) entrepreneur would have done.

This is the biggest pitfall for an EIR and potentially a dire/fatal situation for a hatchling startup…  If a startup’s cap table becomes too tilted towards investors in Series A, then the founder(s) may give up control of their company too quickly, or become too diluted to make the startup worthwhile to pursue.  Obviously, everyone loses when a startup gets pushed to the point that the founders are demotivated.  But that’s a very fuzzy boundary and EIRs seem more prone than non-EIRs to end up pushing that boundary in a bad way.

So, is being an EIR the right thing to do?  Depends on your goals and how you manage the risks mentioned above.  I’ll wrap up this series on EIRs in my next post with a list of venture hacks for EIRs to mitigate these risks.

I’m back after a looooong blogging hiatus. Yay, glad to be getting back into the swing of things.

So, @vijayv recently asked me:

Would you be able to tell me more about being an eir? Mainly Interested in role specifics/responsibility

I’ve had the honor of being an entrepreneur-in-residence (EIR) with two VC firms, Venrock and Matrix Partners.  And through those programs, I’ve been lucky to have met and learned from many other entrepreneurs who have had way more success and experience than me.  And if there’s anything I’ve learned about the EIR role, it’s that there’s no such thing as a “standard” EIR program.  It’s kind of a “make it up as you go along” role (and that actually suits entrepreneurs very well).  Quite frankly, there aren’t that many EIRs running around Silicon Valley all the time because most venture firms do not support EIR positions at all.  Those that do will customize the role on a case-by-case basis.

At the highest level, I think we could say that EIR programs involve:

• working with partners at a venture firm whom you’ve previously worked with or gotten to know very well
• researching existing startups to find promising ones that you’d like to personally join or introduce to the firm
• ideating and creating new businesses
• helping the firm vett business pitches

Within those general activities, roles do vary a lot depending on each individual’s prior experience and their goals.  E.g., some EIR’s are seasoned executives who are specifically looking for teams that they can pair up with to launch a startup.  Other EIR’s are product innovators who are trying to launch new companies while incubated at the VC firm.  Still others are entrepreneurs who are considering switching to become investors and are using an EIR program as a way of getting to know a firm.

And the specific arrangements that an EIR has with their host firm will vary a lot, too.  Some EIRs are actual employees of the firm, some are contractors/consultants, others have no contractual relationship with the firm at all other than coming by to use a spare desk every once in a while.  Most, but not all, EIRs are compensated by their firms; and compensation levels seem to vary significantly from corporate-executive-equivalent to ramen-subsistence-stipend.

There are significant benefits and risks associated with being an EIR and I’ll talk about those more in my next post.

I’m a co-founder of a startup and I’ve noticed that our advisors are beginning to form “teams” around two opposing schools of thought for gaining early user adoption.  These two philosophies are mostly mutually exclusive so I think entrepreneurs need to make a choice about which camp they fall into…   Which are you?

I won’t call out individual advisors/directors to preserve any “secret-sauce” that these folks may be building around their own businesses, but suffice it to say that some folks much smarter than me are championing these philosophies.

Philosophy #1:  I’ll call this the “Loop Experimentalist” or “New School” approach.  This approach focuses on building and experimenting with a number of viral loops (email, web, scrapers, mobile, etc.) in a completely quantitatively-driven manner.  First step is to build a viral loop (e.g., register for your site, add friends from Gmail importer, site sends invitation emails to selected friends, friends receive email and clickthru to register at your site).  2nd step is to try throwing users into the loop(s) with minimal generically-good-sounding instructions (“Add friends to your GoodPalsNetwork!”).  No product necessary, a broken flow at the end of the loop is OK (“Thanks!  More features coming soon!”).  Find a loop that has K > 1.0 and then see what kind of users are going through it.  Build a product around those users.

Philosophy #2:  Let’s call this the “Use-case Driven” or “Classic” approach.  This approach centers on gathering qualitative data through consumer focus groups, interviews, ethnographies, and BD/pre-sales discussions.  Use qualitative data to understand customer pain points and find a vertical use-case or problem that you can define your product around.  Build a product that delights some users.  Goto market with the same consumers/partners that you talked with initially.  Get linear adoption within that target set first, then figure out how to grow exponentially from there.

Do these models jive with your observations of the startup-o-sphere?  Lemme know!

I recently had the pleasure of connecting with TS Ramakrishnan.  Super smart guy and clearly one who know a thing or two about how to launch app platforms/APIs for social networks.

TS has an interesting short-list of four requirements for a successful social network app platform:

1. Users — the social network must be large enough to bring lots of distribution to app publishers
2. Language — platform must be backwards compatible with existing web development languages/frameworks
3. Marketing — the social network must expend significant effort to recruit, retain, and support app developers
4. Transactions –  the social network must facilitate secure transactions (i.e., payments)

I found his last requirement to be really thought-provoking…  It sounds like a pre-requisite for ecommerce transactions, but we haven’t seen a whole lot of apps pursue ecommerce models yet on social networks.  The vast majority of social apps are 100% ad-supported, but we’re starting to see some “freemium” models develop.  For instance, Slide’s SuperPoke app has Premium poke actions that users can get access to via a monthly subscription.

Even in an advertising-dominated economy, I wonder if the social apps on Facebook might monetize more efficiently if Facebook were to facilitate the payments/collections process between ad networks and app publishers?  E.g., would social ad networks operate more efficiently if ad units were rendered in FBML and Facebook provided standardized tools for measuring impressions, clicks, follow-on actions, pathing; and financial transaction support for buying/selling social ads…

A lot of folks have asked for more details on the way we measured and optimized viral app growth in the Stanford class I co-taught recently. So here’s a bit more info on methodology for measuring virality and what it means for an app to “go viral.”

K-factor and R-zero

Terms like “K-factor” (contagion) and “R-zero” (reproduction rate) are often used to describe the growth rate of viral apps. These terms come from the fields of medicine and biology — they’re originally intended to describe the spread of of viral diseases, but they’re nice analogies for how web/SN apps grow. Some would even describe widgets and apps as “diseases” that have “corrupted” popular social networks like MySpace and Facebook! Of course, having worked at Slide and authored some FB apps of my own, that’s clearly not my belief… So, read on if you’re interested in viral apps!

Whether we’re talking about apps or diseases, the key factors in determining virality are the same:

1. Distribution: how many people, on average, will an “infected” host make contact with while the host is still “infectious”?
2. Infection: how likely is a person, on average, to also become “infected” after contact with a viral host?

If you multiply these factors together, that’s your viral growth rate (or “K” or “R-zero” or “viral coefficient”). The product of these factors answers an important question:

“How many people will be infected by a single viral host while the host remains infected?“

With real-world viruses, the infectious period has very dramatic outcomes. E.g., a host remains infectious until either the virus kills the host or until the host’s immune system fights off the virus. If K=1, then the host basically passes the virus on to one new person before either the host dies or the virus is expelled. Either way, if K=1, then the host exactly replaces him or herself in the population of infected people before becoming non-infectious.

Hopefully, the growth of social apps will never involve physical death or illness! [Disclaimer: No readers were harmed for the writing of this post.] Instead, we would consider a host to be “no longer infectious” if they either uninstall the app or stop actively using the app. Using that definition, an app with a K-factor of 1 will have a userbase in steady-state – no growth, no decline, just flatline; where every current user replaces themselves before leaving the userbase. K>1 means an app is growing its userbase virally (exponentially). And, conversely, K<1 means an app’s userbase is exponentially decaying.

With these factors in mind, designers of viral applications have four levers to pull on in order to increase virality:

The Four Viral App Objectives

• Increase the percentage of “active hosts” who actively make contact with uninfected people
• Increase the contact rate for each active host (average number of contacts per time period)
• Increase the duration of each active host’s infectious time period
• Increase the likelihood that contacts turn into infections (i.e., infection conversion)
  

Sidenote on app metrics

Note that this also implies that in order to affect any of these, you, as an app developer, need to be able measure each of these stats for your userbase. You can’t tell if you’re driving any of these numbers up (or down) until you know how many contacts/invitations each of your users sends out per day/week/month that they have the app installed; how many days/weeks/months each of your users tends to keep the app installed; and what the conversion rate from a contact/invite into a new infected user is.

Collection and analysis of metrics for social apps is a meaty topic in and of itself, so we’ll leave that for another day. But for now, it should suffice to say that it’s really important to have an effective way to collect statistics on what your users are doing with your app!

Assuming that we’ve got a reliable way of collecting metrics, here’s a quick list of some techniques for achieving each of the four viral app objectives.

Some example methods for optimizing virality

Active Hosts

• Require users to invite more people to join the app before they can view/use the app. Typically paired with premium or high value content. E.g., “Invite 10 friends in order to unlock this pr0n video in high-definition” or “Invite 15 friends to see how who has a crush on you.” Some users complain about this tactic, but you may be surprised at how many users will effective. (just kidding about the pr0n, kiddies — that stuff doesn’t fly on most social networks.
• Opportunism — you can’t always predict how people will utilize an application, so give your users multiple ways to share your app. Ideally, every app pageview should contain one or more ways for a user to share the app (and thereby become an active viral host).

Contact Rate

• Create incentives for inviting more people. E.g., “invite 10 more friends to level up and become a Black Belt Ninja”
• Specific requests tend to work better than vague encouragements. E.g., don’t just ask users to “please invite friends”, specifically ask for a number, “invite 10 friends” (don’t laugh, it actually works!)
• Simplify, simplify, simplify. If your #1 goal is to go viral, then that should be the #1 action-request that “pops” out to a user. Make it easy to invite more people. Utilize address book importers. Auto-select large(r) distribution lists for invitations. Basically, minimize the amount of hunting-and-clicking it takes to get a user through your invitation process. Ideally, it should just be 1 click.

Activity Duration

• User-to-user messaging is a great way to keep users coming back to an app. If pokes, walls, comments or private messaging fit into the context of your app, you should seriously consider building those in.
• User generated content and media — in general, apps that have some form of UGC/media built into them (music, photos, videos, drawings, etc.) do a better job at drawing repeat visits. I’d also group collaborative filtering functionality in this bucket — e.g., ratings, rankings, top playlists, “most viewed” lists, etc.

Infection Conversion

• Social context — when you’re writing the content/copy for your app invitations, be sure to keep in mind the fact that all your app invitations are occurring in the context of a social relationship between two friends. Use that knowledge as you phrase every call-to-action and craft each sentence to reinforce the social relationship and play on influence mechanisms between these two friends.
• Images and buttons — beyond writing the actual content/copy, app authors should also experiment with design and layout of their invitations. Some top tips include: use buttons instead of plain text links; and use images of people to draw the eye.

Of course, the list above is not exhaustive, it’s just a sampling of top-of-mind viral engineering techniques. If you have other favorite/top tips for tweaking virality, please post a comment below.

A note on prioritization:

In general, all other things equal, it’s most effective to pull on the Contact Rate and Activity Duration levers first — followed by the Host Activation and Infection Conversion.

By definition, your Host Activation and Infection Conversion rates are capped at 100% — the best you can do is to get 100% of hosts to invite other people, or 100% of contacted users to become infected. In contrast, the Contact Rate and Activity Duration are theoretically unbounded. (Well, I guess all human users must eventually expire, but I haven’t seen any Facebook apps that specifically optimize on age of users, yet!!) In any case, for our purposes, the total number of viral contacts initiated by your userbase is theoretically unbounded.

So as an app developer, you should explore the upper limits of how rapidly you can grow your viral contacts before circling back to optimize conversion rates. E.g., if you think of each of your current users as an “infected host”, then your first priority should be to get a maximal number of invites/contacts sent out by each of your hosts while you have them on the app.

Benchmarks

Just for comparison, I’ve included some common ranges for Host Activity, Contact Rate, Activity Duration, and Infection Conversion below. These are derived from my own experience with Facebook apps, observations of my Stanford Facebook class’es apps in Fall 2007, and also observations from companies that I have worked at or advised.

Active Hosts

• App age is an important consideration — newly launched apps will tend to have more active hosts
• Anything above 50% is pretty good for early-stage apps
• Single-step funnels perform best for maximizing host activation (e.g., select and invite friends from a single page, ideally the FIRST page that a potential new host sees)
• In general, minimize the number of steps/pages that you ask hosts to go through in order to invite their friends. Each additional page/step in a funnel will drop 50% to 60% of users, so each step in a funnel carries a very steep penalty. (Note this is a LOT steeper drop off than the rule of thumb 33% dropoff for page-to-page conversion rates that ecommerce or content sites see!)

Contact Rate

• For Facebook apps, 15+ total invitations per user is very good (Note that Facebook imposes a daily limit of 20 invitations per app per user)

Activity Duration

• Activity rates and user tenure will vary widely, depending on the purpose and design of app.
• Healthy ranges are typically between 5% and 40% of an app’s userbase will be active on any given day. (Starting high for young apps and then decaying over time for older apps)
• Good retention practices should generate 8+ repeat visits per month per user

Infection Conversion

• Expect net conversion rates from invites-to-infections in the range of 5% to 8%

K-Factor / R-zero / Viral Coefficient

• Ranges between 1.4 – 2.1 (or higher) are typical for apps experiencing “hot” viral growth

Summary

OK, so good luck to all you app developers out there seeking app virality! As you can see, none of this stuff is “secret sauce” or anything — you can readily view all of these techniques in action on Facebook, MySpace and other social network sites today.  Still, I hope that summarizing this stuff in one place is useful and many apologies in advance if I’ve misrepresented anything, especially the biomedical stuff.  (Is there a doctor in the house?!)  Please leave comments or corrections below!

And, of course, if you’ve got some viral ideas or would like to collaborate on viral apps, drop me a line: yeelee at gmail (or connect to me on Facebook, LinkedIn, etc.)

Mark Davis of DFJ Gotham Ventures posted this nice summary list of six types of risk that venture capitalists typically examine when evaluating a potential investment.

1. Management Risk
2. Product Risk
3. Revenue Model Risk
4. Market Risk
5. Competitive Risk
6. Partnership Risk

Read the full article here

I mentioned AlphaBlox in my last post and that made me think of something I learned from Michael Skok (CEO and Founder of AlphaBlox, now Partner at North Bridge Venture Partners).

Michael had a great framework for explaining how each person’s daily activities fit into the larger company objectives. He called it “VMGOSPA”, an acronym for the following framework:

• Vision — The company’s long term vision. E.g., “Acme Widgets is the world’s leading provider of basket weaving technology”
• Mission — Short-term (1-2 year) mission statement that builds toward the company Vision. E.g., “Acme Widgets’ mission is to dominate equipment sales in the fastest growing segment of basket weaving technology: underwater basket weaving”
• Goals — Immediate goal statements that build towards the Mission. E.g., “Successful completion of human trials for Acme’s innovative noninvasive underwater basket weaving equipment”
• Objectives — Current objective statements for executives, business units, functional departments, or teams that collectively achieve the company’s Goals. E.g., “The R&D department’s Q1 2008 objective is to produce 20 units of UBW equipment for trials.”
• Strategies for achieving Objectives
• Plans for implementation of Strategies
• Actions on a day-to-day basis that execute the Plans

Now, the seven layers of VMGOSPA clearly will not apply to all companies. Small companies and startups, especially, may not have enough team members to subdivide and delegate actions to!

The key concept here, though, is absolutely critical to scaling up an organization: every individual’s daily activities should aggregate up to achieve the company’s mission and thereby propel the company towards its vision. The way to do that is to visualize and define each person’s and team’s objectives in a recursively nested structure.

I had the pleasure of hearing Avinash Kaushik, Google’s analytics evangelist, speak when he came to our CS377W class at Stanford this quarter (the “Stanford Facebook class“).  He’s an amazing speaker, really breathing life and purpose into the too-often dry topic of web analytics.

He’s promoting a new way of looking at web analytics, what he calls “Web Analytics 2.0″.  Avinash’es central message is that analytics cannot stand alone as a decision driver in organizations; rather analytics need to be considered in the context of additional data (from customers, competitors, and other internal sources) in order to drive rational decisions.

Avinash has a brilliant decision framework, consisting of the five decision inputs that should be considered in order to gain insight into customer behavior and drive optimal decisions.   He calls this “The Five Pillars” and here’s the cliff’s notes summary:

1. Clickstream — Typical web analytics can give you data on unique viewers, pageviews, session times, browser types, and geolocation.
2. Multiple Outcomes Analysis — The payload for most web analytics tools is goals/funnels and conversion rate analysis.  Having clearly defined website goals is necessary and a great starting point, but not sufficient for true user insight.  Analysts should recognize that users and companies may have many different reasons for visiting or hosting a website.  All those objective outcomes need to be measured to see if the site is really driving the desired outcomes.
3. Experimentation & Testing — In it’s simplest form, this means A/B testing the design of your website, including text, graphics, buttons, banner ads, everything.  Some free tools like Google Website Optimizer actually automate the process of running multivariate tests to help you quickly find the optimal.
4. Voice of the Customer — Even after taking your best stab at Multiple Outcomes Analysis (#2, above) ask website visitors through surveys: (1) why are you here?; (2) were you able to achieve what you came for?; (3) if not, why not?  The results can be tied back to analytics data and may reveal customers’ true motivations.
5. Competitive Analysis — Your site does not exist in a vacuum.  Your competitors may be running campaigns or launching products/features that are impacting your site’s performance (could be either up or down).

An important theme that runs throughout Avinash’es comments but doesn’t explicitly show up in his framework is:

• Analysts should not be the only people in an organization who see all this information.  The process of gaining customer insight is becoming more and more automated and this information can and should be put into the hands of more people throughout each organization.

This is really, really powerful stuff — everything I’ve seen in my experience at AlphaBlox, PayPal, and Slide confirms that (1) companies are hungry for this kind of analytically-driven insight; and (2) teams that really LIVE this analytical process are winners — when people talk about “cracking the code” on how to continuously improve a web-based business, this is analytical process is really what they’re referring to.  The early PayPal team established a metrics-driven culture that did a good job at upholding the Five Pillars (though we didn’t call them that at the time).  And the Slide team is doing an awesome job at this, using a slightly different but equivalent analytics framework.  The information is out there…  Avinash does a great job packaging it up, now companies need to really internalize his message.

If any of this strikes a chord with you at all, you should do yourself a big favor and read Avinash’es entire post (and watch the video!) on this topic:

http://www.kaushik.net/avinash/2007/09/rethink-web-analytics-introducing-web-analytics-20.html

He’s even got a primer at the bottom of his blog post on how to get started with this analytics methodology.

Setting objectives for yourself and for others is a critical organizational function.  This will be painfully clear to anyone who’s ever sat in a team meeting where some “critical corporate goal” was described but no specific actions were assigned and everyone left the meeting wondering, “Ummm, so what am I supposed to do now?”

The SMART framework helps make objectives crystal clear so that anyone who is on the assigning or the receiving end of a SMART objective really understands exactly what actions are going to take place, by when, and how to measure success.

SMART is an acronym for:

• Specific: is the objective described in concrete, actionable detail?
• Measurable: what quantitative measurements will tell us when the objective has been achieved?
• Attainable: is the objective really achievable within budget and schedule constraints?
• Results-oriented: what tangible work output does the objective produce?  (i.e., not just conversations and ideas)
• Time-driven: what is the due date for the objective?

I think the SMART framework for writing and communicating objectives is invaluable — it applies at all levels of any organization, whether setting corporate objectives for a business unit, specifying product initiatives/featuresets, or day-to-day management of individuals.