Andrew Chen: Growth Hacker is the new VP Marketing →

Great piece by Andrew Chen.  Some quotable bits below, but the piece itself also includes an awesome discussion/analysis of how Airbnb created / hacked a Craigslist integration with no API.

“Growth hackers are a hybrid of marketer and coder, one who looks at the traditional question of “How do I get customers for my product?” and answers with A/B tests, landing pages, viral factor, email deliverability, and Open Graph. On top of this, they layer the discipline of direct marketing, with its emphasis on quantitative measurement, scenario modeling via spreadsheets, and a lot of database queries. If a startup is pre-product/market fit, growth hackers can make sure virality is embedded at the core of a product. After product/market fit, they can help run up the score on what’s already working.”

“The fastest way to spread your product is by distributing it on a platform using APIs, not MBAs.  Business development is now API-centric, not people-centric.”

“The role of the VP of Marketing, long thought to be a non-technical role, is rapidly fading and in its place, a new breed of marketer/coder hybrids have emerged.”

Biz Dev Is A Clever Name For Dirty Work (via Christopher Steiner) →

This is true.

“Hello there, son: this is biz dev.  This is the beating, pumping heart of biz dev.”

“I get the impression, from a lot of these biz dev’ers, that they think of biz dev as fun and sexy.  One minute you’re grabbing lunch with Ron Conway and Ashton Kutcher and the next minute you’re closing a deal on the phone while you wait in the lobby at Microsoft to give Steve Ballmer the bad news: “No, we will not accept your acquisition offer of 3 trillion dollars.”  From there, you head out for cocktails and swirl single-malt Scotch while discussing why Apple is so badass.”

“That might be biz dev at Facebook, but biz dev in the true startup world is 90% dirty work.  The “fun” stuff, I’m afraid, is the hacking and the product development.  That’s usually not in the job description for biz dev’ers.”

Uber and the Importance of Amazing First-Time User Customer Service

I think it’s pretty well-known that a huge differentiator for startups (either vs. other startups or vs. the “bigco” whose market they’re trying to disrupt) is insanely great customer service. To cite a few posts I’ve seen recently on this, see Sarah Tavel’s post on the importance of amazing customer service (in the e-commerce context); Spencer Fry’s post on Bootstrap Marketing (in particular for this post, see the section on “Sometimes you have to Issue Refunds”); and Ethan Austin’s post on customer service lessons he learned from Naval Ravikant at Angel List.  (Also Seth Godin is awesome on customer service stuff).

I was in NYC this past weekend, and I decided when it was raining last night to pull the trigger on trying out Uber. I cancelled my car when it took longer than I had expected and we found a cab (I cancelled before a driver signalled he’s coming, so I avoided the $10 cancellation fee).  Today — within 24 hours of the attempted usage — I received this email from Uber NYC’s customer service team [with the awesome email title of “$10 Uber Credit - Uber Fail :(” ]: 

———

Hey Arpan,

I see you were looking to get a ride with us in NYC recently and I’m sorry we let you down. We’re working hard to get more cars on the road so we can always be there when you need us.

I’ve added $10 in Uber credit in your account to make up for the inconvenience, and I hope you’ll try riding with us again soon!

Feel free to email me directly with any questions you have. I’m always happy to help.


Cheers,

Ed Casabian
Uber NYC Community Manager

———

That’s what I call amazing customer service.  I was impressed enough that (a) I wrote them back saying thank you, and (b) I’m writing this blog post.

I’m not sure if this is an offer that gets sent to others that are already engaged users, but I’m sure their system is aware that this was my first time engaging with the product, and they smartly know how important the first impression is.  I’m guessing I got this offer because this was my first usage, it didn’t go as planned, and they really really want to convert me because I’ve now gotten so close to becoming a paying customer and they know I’m more than just a passive user (i.e. someone that’s just downloaded the app and never tries it).  In other words they know I’m right at the bottom of the marketing purchase funnel.  This is precisely the moment when amazing customer service can make the difference.

Also, in terms of the amount of the credit, it’s an obvious statement but worth mentioning that presumably it’s small enough that the $10 loss on the credit would be exceeded by whatever Uber’s average customer lifetime value is (i.e. how much they’d expect to make off me once I did start becoming an active user).

Big props, Uber.

Profitably | Blog: The Ultimate 6-Week Startup Crash Course →

profitably:

I met another young man today who is en route to a world class MBA program to fill in the gaps in his knowledge prior to starting his life in a startup.

I gave him the same metaphor I have given droves of others. If you wanted to be a world-class cyclist and told me you were going to spend the…

Great Posts on SaaS, Metrics, and Business Models

I’ve spent some time pulling together a few awesome posts on metrics and business models/market structures, including a bunch of stuff on SaaS.  This is by no means exhaustive and there’s a huge amount of valuable resources out there on metrics but these are a few I’ve come across that I really like.  

All of this is insightful and practical, and some of this stuff is so good you can’t put it down.  Briefly, a couple quick rules of thumb in SaaS are (a) LTV should ideally be 3x CAC, and (b) you should try to recover CAC in <12 months (i.e., CAC Ratio < 1) from a cash flow perspective.

Obviously it’s easy to get caught up in metrics and lose sight of the bigger picture — i.e., are you building something insanely great that customers can’t live without.  But metrics help bring some science to the art of startups (in keeping with the lean startup view of applying the scientific method to startups).  And I think particularly in the context of SaaS businesses, they’re crucial.

Really good stuff.  Read it all and make it work for your startup.

SaaS Metrics and Other Considerations for Cloud/SaaS Businesses

Bessemer’s Top 10 Laws of Cloud Computing and SaaS. Invaluable insights, cover to cover.  The “6 Cs of Cloud Finance” (Law #2) are where the metrics-specific material lies: Committed Monthly Recurring Revenue (CMRR); Cash Flow; CMRR Pipeline; Churn; Customer Acquisition Cost (CAC) and the CAC Ratio; Customer Lifetime Value (CLTV).  Bessemer has also open-sourced a working Excel “SaaS Reporting Template” that allows you to track MRR, CMRR, profitability, and cash.

SaaS Metrics - A Guide to Measuring and Improving What Matters, by David Skok at Matrix Partners.  An exhaustive deep dive into profitability, cash, growth, and other metrics.  David’s blog is chock full of in-depth posts, both SaaS and non-SaaS-related.  He also embeds working spreadsheets in some.  A few posts I’ve read that I liked are Designing Startup Metrics to Drive Successful Behavior; Startup Killer: The Cost of Customer Acquisition; and SaaS CEOs: Measure Customer Engagement — Increase Conversions & Lower Churn (with reviews of a couple cool products in this space).

Paid Acquisition for SaaS Startups, by Ada Chen. A breakdown of the LTV > CAC calculation.

Measuring Churn for Recurring Revenue Businesses, by Sarah Tavel at Bessemer.  On the value of measuring churn on an MRR basis instead of just on a customer count basis.

SaaS Business Metrics: Why Are They Different?, by Philippe Botteri.  Explains why the traditional “bookings” metric for software license model businesses doesn’t work for SaaS businesses.  (For some real banker-style fun, check out this SaaS valuation worksheet I came across on Philippe’s blog, in Google Docs format — fyi, doesn’t look like it’s been updated in about a year). 

Business Model / Market Structures

8 Essential Questions You Need To Ask About Your Business Model, by Alex Osterwalder.

Business Model Analysis.  A 10-part series by Tom Eisenmann, a professor at HBS.  Among many other topics, he touches on startup cash flow, platforms, network effects, switching costs, to scale or not to scale, virality, LTV and CAC, bundling, and vertical integration.

E-Commerce Metrics

Bessemer’s Top 10 Laws of E-Commerce.  Another “6 Cs” rule (Rule #3), as well as material on things like the perils of affiliates and problems with “last-click” marketing (including the “navigational search” phenomenon).  

An interesting insight here on the LTV > CAC metric in the e-commerce context: while ideally you should spend to acquire customers right up until the marginal contribution of each new customer is positive (i.e., spend so long as LTV > CAC for each new customer), in practice it’s difficult to estimate a customer’s LTV and super-risky to spend to acquire in excess of LTV.  The suggestion then is for early-stage companies, an alternative approach is only to spend to acquire customers up to the average gross profit generated on the customer’s first product order, and from there focus on generating repeat usage.

Other Stuff on Metrics

KISSmetrics blog is generally great, and is written in a direct, colloquial style.

How To Measure Your Way To Startup Success, a guest post on the KISSmetrics blog, contains five guiding principles that Josh Ledgard at Kickoff Labs uses in his business: (1) Generate weekly and monthly reports of key metrics (including, crucially I think, customer success metrics); (2) Don’t automate every report; (3) Track where your customers are coming from; (4) Real time or daily email alerts; (5) Don’t get addicted.

Ajay Agarwal: Marketing is the next big money sector in technology

GigaOm posted an excellent article a few days ago by Ajay Agarwal from Bain Capital Ventures.  Ajay presents some great insights into the history of enterprise software, namely that it started with back-office functions like HR (PeopleSoft), finance (Oracle), and manufacturing (SAP), then moved into the front office into sales (Salesforce and Siebel), with big companies in enterprise marketing notably absent (other than Omniture).

He then argues that the shift to web-based businesses enables valuable enterprise marketing-focused companies to be created based on the various data on prospects/potential customers widely available now.  He cites companies in Bain Cap Ventures’ portfolio like BloomReach, CQuotient, HookLogic, and TellApart as companies participating in creating this wave of marketing innovation, and suggests that modern techniques such as data mining, machine learning, and analytics deployed against “big data” will drive success in this area.  It’s a very intriguing investment thesis.  

One particularly interesting tidbit was Ajay’s point that these companies are shifting to a “performance” pricing model as opposed to the traditional enterprise software license model.  This jives with the broader shift to the cloud/SaaS model of software delivery: a successful modern marketing-focused enterprise software company that utilizes and mines web-based data should ideally charge customers solely based on ability to deliver conversions (or other relevant metric) for their marketing campaign efforts, i.e. pay-for-performance, similar to the pay-for-what-you-use model of cloud computing.  Winners that deliver successful outcomes based on those data mining and machine learning techniques will profit as their customers re-engage going forward.

Changes to long-held pricing structures are happening all over as a result of the shift to web-based delivery, and it seems like this enterprise marketing software segment should experience the same phenomenon.  Perhaps this change in pricing structure is not merely the result of the products presumably being delivered via web (as opposed to being installed), but is also being driven by the fact that the various sources of data for the marketing research work these products do are themselves generally web/mobile-based as well (though certainly some of the source data would also come from physical in-store customer actions too).

UPDATE: To clarify, I think the right partition / comparison of pricing structures is between (a) traditional pricing models for installed software (i.e. pay for each release/update, like Windows); (b) SaaS pay-as-you-go subscription pricing; and (c) pay-for-performance (the category being discussed above in the context of enterprise marketing companies).

I think the point is that SaaS subscription pricing models (with focus on particular metrics like churn, avg recurring revenue, etc) are an innovation on installed software pricing and also themselves relatively new (though a few yrs old now), but the concept of pay-for-performance may be a more recent phenomenon, and/or may be specific to marketing-style businesses that involve a campaign with observable metrics that result.

philphys:

” The main things which seem to me important on their own account, and not merely as means to other things, are knowledge, art, instinctive happiness, and relations of friendship or affection. “

- Bertrand Russell, Problem of China

Up & Right: Square, the Apple of Payments? →

tomloverro:

When my colleague Jim Robinson III bought First Data Corp while he was at American Express in 1980 for about $80 million it was probably pretty hard to imagine the company growing to become a $30 billion enterprise even if you were Jim.

As it turns out, payments can be a pretty big business….

Information Arbitrage: Thoughts on VC portfolio construction →

informationarbitrage:

Issues such as “portfolio construction,” “reserve policy” and “forced rankings” don’t make for sexy reading, but in my opinion are critical elements to building and managing a successful venture investment portfolio. Given that I am trying to build the best venture partnership I can for the…

Existential Quantification: Armchair Critics →

In many ways, the work of a critic is easy. We risk very little yet enjoy a position over those who offer up their work and their selves to our judgment. We thrive on negative criticism, which is fun to write and to read. But the bitter truth we critics must face, is that in the grand scheme of…

Professional Communities Online

One startup area I’ve been thinking a fair amount about lately is professional communities.  Some thoughts follow:

The web has long existed as a place where people with particular interests congregate.  While I don’t have particular examples of *professional* communities that have been in existence for awhile readily available, I’m certain they’ve existed historically (though perhaps more as utilities / shareware and forums, and less as for-profit entities).

Post-Facebook, one might think of professional communities as specialized instances of the social networking model — not merely interest-based, but profession-based social networks, based on the concept of someone having a  ”profile” (or perhaps “portfolio” in the professional context).  Professional communities also often simultaneously serve a marketplace function, bringing buyers and sellers together, but I think of professional communities as something more than just serving a marketplace function.

There are a few recent prominent examples of interesting professional community startups that come to mind. GrabCAD is a mechanical engineering community, and Academia.edu  is a community for academic researchers.  The market for academics is certainly large, and as has been well-chronicled elsewhere, academic publishing is ripe to be “disintermediated.”  And while presumably smaller, a community for mechanical engineers to meet, get technical feedback, and share 3D CAD models (and find manufacturers/customers) also makes sense, to the extent that these are professionals with a specific area of technical expertise that can benefit when their peers comment, critique, advise, etc.  [This is distinct from building actual CAD modeling software, which itself is ripe for innovation too, as was reported recently.]

I think I’d also add something like Visual.ly to this list, at least the side that focuses on allowing “data visualizers” to share their portfolio of work (as opposed to their new feature that enables users to generate quick customized infographics — in itself a very cool and interesting idea).  Skillshare might also fit into this category, though they’re less focused on a particular profession, and more on the marketplace concept of bringing together “buyers” and “sellers” of non-academic knowledge (though there certainly is a strong community feel among Skillshare users).

These are surely just a few examples of the many out there — I’m sure professional communities like this exist, or should exist, in the medical arena, for example.  There are also surely more examples where vertical/profession-specific community sites have failed than have succeeded.  I think at least part of this is because community-focused sites (and social-networking style sites broadly) suffer from the problem of trying to create something that requires network effects to succeed at scale.

Why are startups such as these burgeoning now (putting aside for the moment the very real possibility that this isn’t a new phenomenon but that I’m just now becoming more aware of them)?  I think there are at least a few factors.  One is the previously-mentioned social networking model that created the template for profession-specific communities and more broadly enabled and created comfort with sharing online.

Another is simply improving web technologies — I don’t think you saw communities focused on 3D CAD modeling or on infographics/data visualization until now because these are fairly rich mediums and technologies, and perhaps couldn’t flourish in an environment in which the subject matter couldn’t be fully appreciated online (though this argument is less applicable to something like Academia.edu which doesn’t necessarily involve rich technology-driven products).

I think other important characteristics required for such professional communities to flourish online are (i) the profession or industry in question probably needs to be one in which sharing and soliciting feedback is valued and important, as would seem to be the case in the examples mentioned above, and (ii) it should also ideally be an industry that conducts some meaningful portion of its business online.

UPDATE:  Behance is another awesome startup in this category.  It enables showcasing and discovery of creative professionals’ portfolio work, and also serves a marketplace function, bringing creative professionals and companies seeking talent together.

Alex Loddengaard: 10 Facts About Working at a Startup vs. a Big Company →

Some insights from a great new blog I’ve recently come across.  No real surprises here, but still useful to see this list collected in one place (and a signal you’re a good fit for a startup if you read the list and get really excited by most or all of these).  I reposted #10 in its entirety because I think it’s potentially the most important and valuable reason to join one:

1. Responsibility, accountability, impact.  At a startup it’s unavoidable to have lots of responsibility and accountability.

2. Risk.  Working at a startup is riskier. A startup is risky because you’re building something from nothing.  You’re doing something ridiculously hard because you believe in it and want nothing more than to see it succeed.  You’re not failing even when all the odds are against you.  You’re the underdog in many ways.

3. Opportunities for generalists.  Generalists don’t do well at big companies.  Although specialization is still important at most startups, there are far more opportunities at startups for generalists. 

4. Ownership and leadership. At a big company you need to wait years and years to become a true leader with big ownership.  Not at a startup. 

5. Transparency.  Startups usually have far more transparency than big companies. 

6. Company Culture.  You get to help define it.  

7. Hiring.  You’ll do a lot of interviews, and you’ll be part of the decision to hire or not hire someone.

8. Financial incentive.  In general your salary will be lower than at a big company, but your equity, or ownership in the company, will be significantly bigger.

9. Politics.  I’ve never heard of a company with more than 50 people that didn’t have politics.  Small startups can have politics, too, but in the early days there’s generally too much camaraderie and too much daily work to worry about power or any other bullshit like that.

10. Be a part of something bigger than you.  At a startup you’re a part of something much bigger than just what your job asks of you.  Sure, you need to write code, publish blog posts, whatever, but you’re doing much more than that.  You’re building a company.  It’s hard to describe what that feeling is like, though.  Being a part of a small company is somewhat like creating a community or finding new best friends.  You’re making something from nothing, with people who are in it for the same reasons you are.  You’re at the apex of what might become something big, something meaningful and different.  And the excitement is amazingly powerful.

Paul Graham: Frighteningly Ambitious Startup Ideas →

“The biggest startup ideas are terrifying.The biggest ideas seem to threaten your identity: you wonder if you’d have enough ambition to carry them through.”

“This phenomenon is one of the most important things you can understand about startups.  You’d expect big startup ideas to be attractive, but actually they tend to repel you. And that has a bunch of consequences. It means these ideas are invisible to most people who try to think of startup ideas, because their subconscious filters them out. Even the most ambitious people are probably best off approaching them obliquely.”

“The popular image of the visionary is someone with a clear view of the future, but empirically it may be better to have a blurry one.”

1. A New Search Engine

2. Replace Email

3. Replace Universities

4. Internet Drama

5. The Next Steve Jobs

6. Bring Back Moore’s Law

7. Ongoing Diagnosis

SaveLocal / Constant Contact: The Next Iteration of Local Deals

I just read an interview in the NYTimes with Constant Contact’s CEO, about its new approach to deals for local merchants, called SaveLocal.  From the product’s description, this seems like a really interesting approach.  Essentially they’re focusing on tailoring deal structures that suit the local merchant and doing better targeting of potential customers via leveraging existing customers’ social networks.  Both of these are areas that Constant Contact can pursue because of their existing long-standing relationships with small businesses as a result of managing their e-mail marketing campaigns.

This appears to be an attempt to solve the well-known problems of Groupon/LivingSocial deals (i) not being tailored enough for either the audience (in terms of finding the right customers) or the merchant (in terms of the deal pricing/structure) and (ii) having a poor ability to generate repeat business/loyal customers after they take advantage of a deal.  Should be interesting to observe how this business performs for them.

The Four Golden Rules Of Partnerships

alexstechthoughts:

Here is my most recent Forbes piece: http://onforb.es/xQp553

Enjoy!