Sunday, July 14, 2013

Distribution's Day - Why the Rise of the Growth Engineer (or Growth Hacker) is now

In the late 1990's when you wanted to build a startup, a good chunk of your first expenditures went to building the tech, including renting a cage, putting boxes and switches in it, software for databases, code, and content management systems, storage space, and all of the talent to architect, build out, and manage these systems, back ups, and load peaks.  Additionally, you were building all your code, front and back end, from pretty much scratch.  It was rare to even run into a problem that a commercial solution existed for, much less at a reasonable price with fast easy integration.  But today, we benefit from a ton of what used to be the overhead of a tech startup being commoditized, virtualized, and democratized.  For example, servers on AWS, database at Amazon on Red Shift, open source content management systems, open source front end libraries (ok, mostly jquery), hosting for API's at Engine Yard or Heroku, with low cost pre-built off the shelf modules for all of the above, vastly reduces operational overhead.  And you can leverage solutions to send SMS with Twilio, email with a bevy of providers, take payments with Stripe or half a dozen mobile payment providers. Even services to manage all these cloud tools have been virtualized by companies like Pager Duty and many others.  The time and cost to build a tech startup are both dramatically down (Moore's Law dramatic) and the quality has increased simultaneously as these scaled point solutions grow up.

Now I would never suggest that there is not still bust your tail hard tech work that differentiates companies.  And I have seen the right platform choices give companies significant advantages over competitors plenty of times too.  But what I am saying is that the relative landscape is changed.  I am seeing more and more companies with great tech products stalled on distribution than ever before.  With product and marketing being intertwined, and design being a big part of the fabric that binds that together, I have lumped the whole lot into the overarching label "distribution," and the merger of these areas is probably the subject of another blog post another time.  But customer acquisition, or growth, or quantitative marketing, and the speed of it, can make or break two companies competing now.  Company A starts before company B but does not have strong distribution talent.  Company B starts later, but with tech hull speed so high now, they won't be far behind.  And if company B engineers the magic growth button for the market, company B wins.  As I have said many times before, you don't need the best product to win, and you don't need to be first to market to win, you just need to be first as the market consolidates, and then by definition you are winning, and displacing you in that market which you now own will be expensive and difficult.  At that point, you might not have to outrun the bear, just be an unattractive enough market that tech talent will go elsewhere to make their mark rather than try to do battle with you.

Several smart tech leaders I have worked with predicted this time to me.  Rob Meyer at Washington Mutual, Sunil Bopardikar at, and John Malek at Practice Fusion all foreshadowed this pretty clearly in conversations we had.  And some of my NextCard friends like Dave Schwartz at Cold Creek Technology, Rebecca Lynn at Morganthaler, and others way back when even talked about the markets that had been ripped open by scalable distribution techniques like the ones we helped develop in the late 1990's, and the ones that hadn't YET.  I think we all believed it a foregone conclusion that one by one every market would roll eventually.  And so at last we have Agile Marketing (go to the Agile Marketing Meetup in San Francisco if you can), Growth Engineering or Growth Hacking depending on your flavor, and the rise of Quantitative Marketing all employing user experience design, behavioral design, virality, direct marketing, inbound marketing, and optimization to try to win the distribution battle first.

So as you are spinning up your tech, make sure you either have a co-founder with some solid distribution background, or get help fast from an adviser or investor that is a growth engineer.  And avoid being one of those companies wondering how that competitor just ran you over with a lesser product.

Tuesday, July 2, 2013

Why I like 12 Month Break-Even as a Hurdle for Paid Marketing

A lot of people ask me how much they should spend to get a customer.  And I tell them there is no one magic number.  In the early days of a startup you might use one number, but that is only because there might not be enough volume to segment your return measurements meaningfully yet.  But as soon as possible, you would like to measure the return and cost of every campaign you run so long as you can do so at negligible cost, which you should be able to do with modern tools.

Anyway, as a rough rule of thumb, I like to suggest that startups might like to use a 12 month break even for a spending hurdle, so long as it is applied on a campaign by campaign basis and not an average for all channels and campaigns.  There are three reasons I think a roughly 12 month break even is a very comfortable place to start.

1) There is so much spillage in marketing measurement that I am certain that even in pretty tight channels, you are going to get a bunch of customers that you are not able to attribute to the spend.  Want to learn about channel interaction and spillage?  I think my friend Dave Schwartz is going to share some of his immense knowledge and experience at this month's Agile Marketing Meetup, so follow it and sign up when his talk is announced.  But basically, for every account that clicked through on your banner ad, setting a utm (urchin still really?) tag, there was another that just typed your domain into their browser or a google search bar that showed up as branded search or direct type in traffic.  And unless you have a solution that can nail down every banner impression to later traffic like Cold Creek Tech's or you are paying an agency like AdRoll that can do something similar when they serve your ads, you are going to identify that customer as direct type in traffic or branded search if you are on your game enough to track granularly with blunt instruments like Google Analytics.  Similarly, even if you are using a best in class conference lead tracking solution like Bloodhound, there will be some people that saw your booth, maybe even talked to you or approached it while you are busy, and they Googled your brand later.  So you won't be able to attribute every lead to their source.  The same can be said about every channel.  I will write another post sometime about measuring spillage.

2) There will likely be many customers that continue to generate revenue beyond 12 months.  So if you break even at 12 months, you will be building out the gravy train for all those longer term customers.  That will help you put snow on the revenue snowball and barrel down the hill.

3) Using the value that a new customer brought in over the trailing 12 months should be conservative.  I hope that any startup worth their salt can provide immensely more value and extract more revenue out of customers in the next year than they did in the last year.  If you can't, stop reading this blog and go fix that before you figure out how to ramp up paid marketing : )  In my favorite vernacular, I would say that your forward looking cohorts should be a lot better then your backward looking ones.  So if you spend to break even on your backward looking ones, you should be fine.

Now if you know you can beat these things, I would say do whatever you are comfortable with.  For instance, if you know that you have 50% spillage on a banner campaign, then consider relaxing even more to account for that.  And if you know that over the next twelve months your cohorts will generate 50% more revenue than the past 12 months, consider raising the bar 50% higher.  And if your attrition is really low and only getting lower, consider using more than 12 months of revenue for a customer.  Heck, consider discounting a long tail of years of revenue if you can model it and feel confident in it.  If you can make investors confident in it then more power to you, right?  And if 90% of your revenue arrives in the first 7 days of a cohort, then there is likely no need to wait twelve months to call it.  But I have seen 12 months applied to a lot of different industries and it has worked out pretty well as a rough starting point.

What?  You can't wait 12 months to see if something worked out or not?  I will write another post about working out proxies for 12 month value.

Happy distribution and growth engineering  : )

Thursday, May 23, 2013

Conversion = Desire - Friction, more or less

One of my favorite equations for a while has been the very simple Conversion = Desire - Friction,  I have always said that I did not think the math was right but it was so simple and deliciously directionally perfect.  Serious credit to Sean Ellis on it (I believe this is his baby).  More desire, less friction, all good. Made me happy too : )  One day I was thinking that the right answer is actually conversion = p(desire>friction). So if you have a distribution of desire and a distribution of friction for a population, the actual conversion will be those where, for an individual, desire is greater than friction.

All kind of questions start swirling.  Are we better off making desire just a tiny bit better than friction everywhere?  Stop effort once we have motivated conversion, anything beyond that is wasted.  Are there business models where desire distributions or friction distributions should be dictating approaches that we are not thinking about that well yet?  Probably.  Gimme some time to grok on that or some help at least.

Simple enough I guess. But it is rare that the conversion event is enough. Loyalty, LTV, advocacy all go way past conversion.  So even if we get the conversion event perfectly modeled it may not help us succeed better. If upfront conversion and promoter score were independent, maybe, but we all know they are not. 
So if you have the data to think about audience desire and friction distribution, and can build these things independently and impact downstream behavior. You should use a more refined equation perhaps. But for most of us, we are better off keeping it simple probably.  Geez, it is hard enough getting statistical significance on a test as we fragment markets more and more anyway.  I will probably stay with the directional goal of increase desire and reduce friction broadly most of the time for now.  But I am keeping my eye out for a place to apply a more refined view to good effect.  I am sure it is out there for some high scale consumer model.  Seen it?

Monday, April 8, 2013

Growth Hacker: What's in a name?

I love all the attention that distribution people have been getting thanks to rise of the Growth Hacker label in tech lexicon.  In all my time working in tech, I have never seen as much demand as now for quantitative, analytical, distribution people with heavy code, product, data, and testing backgrounds similar to me.  And I always felt like it was an unappreciated art by the masses, though I think there has always been a smaller knowledgeable crowd that understood the potential of this kind of approach.  I remember the rise of the Data Scientist label, and I felt like it similarly brought great new attention to a particular kind of person in the analytics world.  So it looks like Growth hacking is having the same effect on a particular breed of distribution style that has been around for a bit but maybe flown under the radar previously.  It is really encouraging to see.

But as someone whose degree is in engineering who wrote code for 7 years before becoming an internet product guy, I must confess that I have never liked to look upon myself as a hacker of any sort.  I know there are hackathons, and maybe I am just a little too old school and taking it personally.  But I remember staying up late nights and busting to get a change done right instead of hacking something together.  And I took great pride in considering myself NOT a hacker.  So I am reluctant to accept this label today even though I have not written real code for a long time. 

Personally I always always spoke of distribution.  I always felt like Marketing as a title was frowned upon by some folks deep in tech.  I remember a time when I met one of the iconic tech founders for the first time, introduced by another former hardcore tech CEO now turned venture capitalist.  And both wrote plenty of code for sure.  And at the time I had a Marketing title as opposed to some points in my career where I held a Product title.  As soon as I was introduced, there were qualifications thrown out.  "But he is not a Marketer, he worked for Boeing as an engineer."  It confirmed what I had already felt previously.  So I always tried to speak of distribution as I felt it did not have a stigma attached.

But I do like the growth label, as that is definitely what it is all about.  So I wish the label were Growth Engineer.  Perhaps it is not because folks without engineering degrees feel less comfortable calling themselves engineers?  Not sure, would love to hear some feedback.  I think there is some real process focus that is engineering-esque, but there is definitely some art as well.  Growth Maestro or Growth Conductor might have been fun too, but perhaps it does not respect the tech enough?  I stole the word Maestro applied to this game from Geoff Clapp, who I heard use it once for this.

Anyway, the boat left a while ago, and I love the direction it is sailing, but I had to go on the record just to get it off my chest.  And for the small unrealistic hope that lives somewhere within me that hopes others might prefer to be Growth Engineers as well.  hehehe

Tuesday, March 19, 2013

Updated Reading List

Books and other more permanent quintessential works

My favorite all time behavioral economics book - by the master, Cialdini.  Lemme know if you have read his latest book, Yes! co-authored by Noah Goldstein.  I have hung out with Noah and think he is also a very bright behavioral economist but I don't know if the book is do-over/improvement or covering new ground.  But Noah has done some great research also and I am sure reports on some of it in there.
Predictably Irrational - Dan Ariely's book on decision making.  Dan makes the case that buying decisions are not as rational on the micro level as economics on the macro level would have us believe, but it is at least predictable and can therefore be engineered to be effective on that basis. Dan is a very sharp guy.
Designed Addiction - this is a talk by Nir Eyal about his desire engine structure of looking at the world.  It is rock solid.
User Experience
UXD, About Face 3 - from our own local Alan Cooper, the freakin' man
UX testing, Gorilla Style - Steve Krug is classic and spot on
Designer Portfolio Sites - I like looking at the well reviewed portfolios for inspiration : ) 
Dave McClure's - Startup Metrics for Pirates - is a classic and solid growth structure
Sean Ellis' blog - He invented the term Growth Hacker and also has a company called Qualaroo (formely KISS insights) that is interesting.  My favorite quote form him is Conversion = Desire - Friction
Andrew Chen's favorite articles - This guys articles are what led to the popularization of the growth hacker label.  He is a solid product and distribution guy in his own right, legit.
Tom Eisenmann's best blog posts of 2012 - solid reading list, perhaps a bit verbose
Links and stories online - may be MUCH more temporal, even flava' of the month level
01/03/2013 Conversion Best Practices - Low hanging fruit tips from KISS metrics
11/25/2012 How to be a better manager, spouse, and parent, all in one11/23/2012 Peter Theil's startup class - Pretty solid stuff all the way around wrt to startup
11/09/2012 article on AB Testing10/30/2012 - optimizing the email channel
10/29/2012 Quantifying Event Impact - ideas from around the web
05/25/2012 Why startups fail - data from Noam Wasserman based on thousands of startups over a decade
07/14/2013 (when I found it) Some basic mobile app store tips