Monthly Archives: May 2008

loved Mark Penn’s Microtrends [book]

Microtrends — The Small Forces Behind Tomorrow's Big Changes
By Mark Penn

Mark Penn, until recently the strategist and pollster for Senator Clinton's bid for President, wrote this gem of a book called Microtrends.   i absolutely loved this book.     the book detailed little trends that move markets and presidential elections.   This book has great nuggets and is an easy read.   I highly recommend this book.

Black Hat Tariffs – The Black Hat Taxes on consumer Internet companies are on the rise

Web sites are spending more than a quarter of their time fighting bad guys

Consumer Internet companies are spending more and more mindshare from the engineering and the executive teams to thwart bad guys, rather than actually improving their product. This is a really big problem. The Black Hat Tax is costing consumer Internet companies billions. And the cost of this tax, as a percentage, is much worse than what offline brick-and-mortar shops pay to invest in security and anti-fraud measures.

In May 2006, I made mention of the Black Hat Tax, in which most consumer Internet sites have an inherent time, resource, and mindshare tax of roughly 25% due to scamming, phishing, hacking, and government requests. And this drainage has gotten worse two years later which is extremely troubling.

A great example is PayPal. As PayPal matured, they fought an intense battle against fraudsters, one of the most consuming issues within the company. Now with PayPal being a legitimate financial institution, you expect lots of attempted fraud. But this is now the norm for most sites.

Companies in the dating or social networks space are increasingly spending their time thwarting bad guys. Dating sites, for instance, face an exorbitant number of scammers. The classic “my husband is beating me here in Moscow, please send $2000 so I can buy a plane ticket and escape” still ensnares many unsuspecting men. There are scam factories in the Philippines and other places that have thousands of people, paid on commission, working to rip-off unsuspecting dupes in this way. And while buyer beware should reign, caveat emptor is not in the lexicon of the barrage of customer service emails.

Spam is becoming increasingly common on social networks. I’ve received more MySpace friend requests from strippers and pornographers than real requests. In fact, MySpace just sued and won a $230 million judgment against some of the world’s biggest spammers. This is in addition to people actually hacking into your site (but that is a whole other cat-and-mouse game). Facebook, Twitter, and blog comments are also prime attractions for spammers.

All these little, annoying things consume time … and not just the time of customer service people, but time of the company’s executives and engineers as well. The Black Hat Tax exceeds 25% for most consumer Internet companies right now, with some approaching 40%. That means that 25% of your engineering and management time is about preventing fraud or dealing with these annoyances. That is one onerous tax!

In the side conversations at the Founders Brunches, it seems that all the attendants talk about is the black hat tax. One key item of note is invite/email deliverability. Many B2C companies go viral by convincing current users to upload their address books and email their friends. You can do all the viral tuning you want, but if your emails are getting blocked by someone’s spam filter, they are not going to see your genius. As a result, social network execs spend an inordinate amount of time on email deliverability.

Review sites like Yelp, Digg, and TripAdvisor have thousands of people trying to game the system. Better reviews on TripAdvisor can equate to hundreds of thousands of dollars in additional annual income. Getting your article Digg’ed could mean a huge spike in readership and pageviews. And what’s interesting is that it’s been estimated that almost half the reviews on some of these sites are fake.

Another strain on time are government or federal requests. An IT person at a social network can be consumed for three days with a government request for information on someone promoting pedophilia.

While it’s troubling to note that the nefarious characters are getting more sophisticated, thousands of sites are working feverishly to implement best security practices. But all that the bad guys need is to find just one hole.

(special thanks to James Currier for pointing out the Black Hat Tax to me two years ago)

Rapleaf study of friends — full data

This is an interesting study we did last month about where people’s friend data comes from and how it relates to gender.

                              Friends of Men vs. Women on Social Networks

                              Men tend to be more transactional and less relationship building
when it comes to their friends on social networks. Women tend to have
slightly more friends on average.
In the largest social networking study ever done, Rapleaf sampled over
30 million people looking at social graph information across various
social networks including Bebo, Facebook, Friendster, Hi5, LiveJournal,
Myspace, Flickr, and others. We looked at the number of friends that
women have vs. men across these social networks. The following are
highlights of the information we extracted:
                              – Rapleaf sampled 30.74 million people with at least 1 friend

                              – Of the people with at least 1 friend, 53.57% are female and 46.43% are male

                              – Social Networkers (1-100 friends):

  • ~80% of the sample set
  • Women have on average 62 friends
  • Men have on average 57 friends
  • Women are more likely to be Social Networkers

                              – Connectors (100-1000 friends):

  • ~19% of the sample set
  • Women have on average 185 friends
  • Men have on average 172 friends
  • Women are more likely to be Connectors

– Super Connectors (1000-10000 friends):

  • 0.66% of the sample set
  • Women have on average 1,837 friends
  • Men have on average 1,944 friends
  • Men are more like to be Super Connectors

– Uber Connectors (10000+ friends)

  • 0.02% of the sample set
  • Women have on average 24,077 friends
  • Men have on average 24,584 friends
  • Men are more likely to be Uber Connectors


                              Our analysis:
                              As per Rapleaf’s original study [link],
women spend more time on social networks. While the full data below
demonstrates that women do have slightly more friends than men on
social networks, the difference isn’t substantial.

While we theorize that women spend more time on social networks,
building and nurturing relationships, we also theorize that men are
less likely to spend as much time nurturing relationships as they are
acquiring relationships from a transactional standpoint. Spending less
time on a social network but transacting more equates to having roughly
the same number of friends as women, who spend more time on social
networks, but are busier sustaining relationships.
Full in-depth report:











































































  Women Men
  Count % Avg. Count % Avg.
1 friend 3,477,849 21.12%   3,139,918 22.00%  
2-5 friends 3,127,321 18.99%   2,904,458 20.35%  
6-10 friends 1,506,900 9.15%   1,306,375 9.15%  
11-20 friends 1,452,552 8.82%   1,266,455 8.87%  
21-30 friends 809,235 4.91%   703,960 4.93%  
31-40 friends 583,339 3.54%   499,574 3.50%  
41-50 friends 469,606 2.85%   396,328 2.78%  
50-100 friends 1,593,346 9.68%   1,303,557 9.13%  
100-1,000 friends 3,336,626 20.26%   2,655,297 18.60%  
1-100 friends (Social Networkers) 13,020,148 79.07% 62 11,520,625 80.72% 57
101-1,000 friends (Connectors) 3,336,626 20.26% 185 2,655,297 18.60% 172
1,001-10,000 friends (Super Connectors) 107,062 0.65% 1,837 93,676 0.66% 1,944
10,000+ friends (Uber Connectors) 1,989 0.01% 24,077 2,371 0.02% 24,584
At least 1 friend 16,465,825 100.00% 81 14,271,969 100.00% 78




some of the places that wrote about this report include:




































May 7, 2008 – Men and Women Differ on Social Networks (eMarketer)


May 5, 2008 – More Women Than Men on Social Networks, Have More Friends Than Men Do (MarketingVOX)


May 5, 2008 – Rapleaf: More Men are Uber Connectors (BizReport)


May 5, 2008 – Women Make More Friends On Social Network (WebProNews)


May 4, 2008 – Study: Men More Likely to Use Social Networking for Business (Ars Technica)


May 2, 2008 – More Women Than Men on Social Networks, Have More Friends Than Men Do (Marketing Charts)


May 2, 2008 – Women Like to Socialize but Men are All Business on Social Networks (All Things Digital)


May 1, 2008 – Women Like to Socialize but Men are All Business on Social Networks (The Industry Standard)


May 1, 2008 – Women Like to Socialize but Men are All Business on Social Networks (VentureBeat)

read Predictably Irrational [books]

Jeremy Philips sent me this book last month and downed it in one long plane ride. This is a fantastic book and one definitely worth reading. (and if you want me to send you my copy, free book to the first friend of mine that replies).

Predictably Irrational: The Hidden Forces That Shape Our Decisions by Dan Ariely is a great book by a revealing and insightful economist and social scientist. if you liked freakonomics, you’ll love this book. in fact, if you don’t love this book, you’re probably not very interesting. really. it is that good.

more information available at Ariely’s web site:

Coca-Cola needs math tutoring

BigcokeCoca-Cola (NYSE:KO) might need a little math help on their calorie counts.

A standard 12-ounce can of coke, according to the can, has 140 calories.

but the 8-ounce bite size cans say they have just 100 calories.

one of the cans has to be wrong. either the 12-ounce actually has 150 calories or the 8-ounce has wee bit more than 93 calories.

all this SAT math failures hasn’t affected Coke’s stock price which has skyrocketed in the last year … making Mr. Buffet still a happy man.

Implicit is the New Explicit

There are more opportunities to take advantage of content then to create it yourself

Taking advantage of existing user generated content (UGC) can be more far-reaching and impactful than trying to generate new UGC from scratch.

There are a lot of new startups that coin themselves as “Web 2.0” and are focused on creating user generated content. These companies try to get people to come to their site and create content in order to create a community, as well as to increase page views and uniques which invariably capitalizes on their advertising business model. There are impressive players in the explicit UGC space, including brands we all know like Facebook, Digg, Yelp, TripAdvisor, Flickr, Slide, and RockYou. Some of these sites are really good at linking people (e.g. Facebook), helping you find UGC through search (e.g. YouTube), and search engine optimizations (e.g. Digg, Yelp).

All these sites written up on TechCrunch have essentially the same mission – obtain a ton of users to come to the site to create original content that cannot be found elsewhere. Think of a Web 2.0 company and there is a high likelihood it fits the description above.

But (and this is a HUGE ‘but’) these companies are not taking enough advantage of the content that already exists on other sites. Given the trend towards openness of data, this content obtained from other sites is implicit information that can be easily indexed (across thousands of these sites) and then be compiled.

Moreover, there is a growing amount of content being created on niche sites like forums, blogs (and blog comments), and discussion boards. While few of these niche sites will become big businesses, in aggregate they contain a lot of valuable content that can be mined and processed.

Zillow, Trulia, and real-estate aggregators focus and rely on implicit information and data. Travel search (e.g. SideStep) is also implicit-based. And the most dominant player on the Internet, Google, is implicit – search engines don’t create their own content but instead rely on the content of others.

In order for traditional companies that focus on explicit UGC to be effective, they often need to build a walled garden. Because the content is proprietary to their site, they lose out if users are leaving their site. They don’t want to make things open. Some explicit new wave companies (e.g. Twitter, Flickr) have bucked that trend by being open, but most are closed in Web 0.6 Prodigy-style.

Let’s take a look at one of my favorite sites: Yelp. Yelp is awesome and has done a great job encouraging people to write explicit reviews on their site. If I was going to build a competitor to Yelp, I would not compete with them on gathering explicit reviews but would instead gather implicit information on local restaurants. You can gather this information from other review sites like the San Francisco Chronicle, government agencies that rate the cleanliness, legal databases that document lawsuits, and more. And restaurants and other brick and mortars have great identifiers – phone number and address – that are usually unique and therefore easy to find and collect information.

The other problem for companies collecting explicit UGC is that they encounter a huge marketing problem and therefore must have a gargantuan budget. This is why all these explicit companies are raising large capital rounds (often over $25 million) right now. They also require a real skill at viral tuning, street marketing, or search engine optimization (and often all three). If you are really good at marketing, then you should create a company dedicated to getting users and having them generate content.

Implicit companies, by contrast, encounter a huge technology problem and their budget is focused on building out that technology. If you are a technologist then you should be opting to take advantage of content on other sites. That is, of course, what makes Google so successful.

If you’re neither the marketing guru nor the technologist, you might want to sit this new technology wave out and watch from the sidelines as implicit companies will benefit from and give benefit to its explicit counterparts.