On Techmeme – Saw this article on CNet, re Tim O’Reilly’s talk at Web Expo New York:

“(These are) pretty depressing times in a lot of ways,” O’Reilly said in an address that first had looked like it would simply be a starry-eyed discussion of enterprise opportunities for Web 2.0. “And you have to conclude, if you look at the focus of a lot of what you call ‘Web 2.0,’ the relentless focus on advertising-based consumer models, lightweight applications, we may be living in somewhat of a bubble, and I’m not talking about an investment bubble. (It’s) a reality bubble.”

There is a limit to Ad funding for Web 2.0 businesses. Allow me a little fag-packet analysis here. The total global Ad industry is c $0.5 trillion, the online biz globally is about 10% of that at most, and the 80/20 of that goes to Google, Microsoft, Yahoo and AOL. That leaves about $10bn for everybody else, and much of that (say 80/20 again) is being hoovered up by existing high quality and/or high volume existing web assets, leaving in the order of $2bn for everyone else. Assuming every Web 2.0 startup wants to be worth at least $100m, and assuming that is on a 10x multiple of revenues, that means every successful company is running at $10m ad revenues pa. Thus, $2bn / $10m = c 200 startups can live on Ad funding globally on average. Even if I’m 10x out, so its 2,000, you can see that 100% Ad supported business models are not a majority play. And Advertising overall is likely to be in the decline for a few cycles now.

Tim also pointed out another issue, that of allocation of resources in the current market:

“And what are the best and the brightest working on?” O’Reilly asked, displaying a slide of the popular Facebook application SuperPoke, which invites you to, among other things, “throw sheep” at your friends.

“Do you see a problem here?” he posed, showing another slide of the popular iPhone app “iBeer,” which simulates chugging a pint. “You have to ask yourself, are we working on the right things?”

What O’Reilly is talking about here is a typical example of what happens if everything is free – in those sort of markets, there is no way to extract extra value from delivering quality, so cheap-to-produce cr*p drives it out.

( At the O’Reilly Web Expo in Berlin I’ll be talking about this and other Limits to FreeConomics – which after this week I suspect have become a lot closer to home )

Howard Anderson, founder of The Yankee Group (independent technology research and consulting firm, provides technology research, primary data and counsel on connectivity change) is known for its sense of humor, and he puts that sense of humor to good work when discussing why startups could be situated elsewhere than Silicon Valley:

1. The weather sucks in some of these towns (not Tallahassee) so your people will actually work instead of bugging out at 5:15 to train for a marathon, triathlon or Ultimate Frisbee.

2. You can recruit better outside the fishbowl. Every technology company hits the wall — some multiple times. In the Valley your employees will bail at the first sign of trouble and jump to a better job in the next parking lot. That means you will have to spike salaries to rebuild your team. Other places in the world aren’t quite so spoiled – or they come to you already cynical and stay through the rough times.

3. You won’t get lost in the startup maze. In the Valley, every VC has a portfolio company in each flavor – their own LP’s can’t tell them apart.

4. In my experience, other startup communities aren’t as pre-occupied with the “exit” as Da Valley. SV VC’s have attention spans measured in picoseconds and will sell/merge your company at the first sign of trouble. I can say that in Boston, at least, we are used to gutting out long “winters.”

5. Academics make great board members. Each of these cities has a rich educational environment and are great places to recruit sartorial advisors. And unlike at Stanford, you wont have to give up 1 percent of your equity just to put the provost’s name on your board!

All good stuff, but there is the niggling issue that many have tried already – Silicon X’s litter the planet, and in the main most have not taken off. There are also some lessons around the clustering of Ecosystems, from Web 0.0 guru Michael Porter, that are still pertinent:

… in the mid- to late 1990s, several successful computer technology related companies emerged in Silicon Valley in California. This led anyone who wished to create a startup company to do so in Silicon Valley. The surge in the number of Silicon Valley startups led to a number of venture capital firms relocating to or expanding their Valley offices. This in turn encouraged more entrepreneurs to locate their startups there.

In other words, venture capitalists (sellers of finance) and dot-com startups (buyers of finance) “clustered” in and around a geographical area.

The cluster effect in the capital market also led to a cluster effect in the labor market. As an increasing number of companies started up in Silicon Valley, programmers, engineers etc realized that they would find greater job opportunities by moving to Silicon Valley. This concentration of technically skilled people in the valley meant that startups around the country knew that their chances of finding job candidates with the proper skill-sets were higher in the valley, hence giving them added incentive to move there. This in turn led to more high-tech workers moving there.

This sort of puts the finger on my issue with non SV plays – the above 5 points are nearly all “supply side” of willing startups. but the other key is the “demand side” of people to buy into – and then buy – them. And that I think is far rarer outside SV.

I find it interesting this week that both TechCrunch 50 and DEMO are parading startups, the majority of which are valley based in both cases. Where are the other big shows like tgis globally? There is a steady drift of UK entrepreneurs to the valley, typically after they have failed to find any interest in funding their ideas here.

If your funder and your eventual exit targets are in the valley, its probably odds on easier to go there yourself.

Saw this on Huffington Post via Tim O’Reilly, about how datafeeds will allow light to penetrate into dark places:

It seems to me that we also need more regulation, but we certainly need to make sure whatever is imposed is also as technologically sophisticated as the financial transactions it’s meant to monitor!

One Internet innovation, automated data feeds, might simultaneously meet the smart regulation requirement, improve banks’ internal operating efficiency, and even win back public trust as well. Obama has specifically called for data feeds from government agencies as part of his transparency strategy to rebuild public confidence in government, especially as a result of the bailout crisis.

Sound marvellous at frst reading – but then, you think a bit – OK, I can hear you lining up with The Big Objection – but hang on……

Technological limits used to mean that any kind of data had to be laboriously culled and aggregated before being submitted to regulators. Now, innovations such as XML tags and data syndication in formats such as RSS (as a Huffington subscriber, you get the Post via an RSS feed) or KML (used for Google map mashups) make it simple for companies to automatically combine the data and release it, whether internally or to regulators — and even to the public.

The District of Columbia, long plagued by corruption, began a transparency initiative under former Mayor Anthony Williams. It shifted into high gear under Mayor Adrian Fenty, and CTO Vivek Kundra. They now publish, on a real-time basis, more than 260 different data streams of statistics as varied as violent crime, building starts, and even requests to fill potholes. All of those statistics are available for anyone to analyze and interpret, and current uses range from tracking development around the new Nationals Park to showing crime reports on a Google Map.

And even better….

If the same system was applied to banking, critical statistics could flow automatically to federal regulators, while also being available to the banks’ own staff — many of whom have never had real-time data access in the past. Combined with innovative web-based tools to turn obscure data into easy-to-understand visualizations, for the first time the workforce, as well as regulators, would have the kind of real-time information that’s essential in today’s global economy, whether to regulate businesses or to run them.

OK, its time for the Big Objection – Garbage In, Garbage Out.

Undoubtedly using the most modern tech to get data from systems is a Good Idea, but that doesn’t guarantee its accuracy in and of itself. Who shall ensure that what goes into the feeds is accurate? The minute this data becomes valuable, it will be gamed. As anyone who has implemented a new system will verify, accuracy comes from cleaning up databases, putting in workflows that cannot be subverted, and ensuring management oversight (or other forms of effective oversight). Except in these cases its harder, as management (the ones wot got us into all this) oversight needs to be replaced by independent 3rd party oversight.

Technorati has just released its 5th State of the (Blog)Nation report (seen on TechCrunch). We of course are fascinated by The Money and how it cascades down the Long Tail, but that will apparently be in Day 4 of the report, and this is just Day 1 so I just had to do a bit of actual analysis myself. Here is the graph of average revenue per blog type per user from the tabulated data in the report.

Blog ARPU by Type (Broadsight Analysis of Technorati)

Although the monthly unique user bases of Corporate and Professional blogs are higher than Personal blogs on average (39,000 and 44,000 vs 12,000 respectively) the net revenues make personal blogs apparently more profitable, with figures of $50, $150 and $100 per annum respectively. This leads to respective 0.13c, 0.34c, and 0.83c Net Annual Revenues Per User (Net ARPU), assuming that the monthly average unique users stays roughly constant in a year. These have not been adjusted to strip out the non-Ad supported ones, which are about 45% on average. Stripping those out and upgrading gives respective Net ARPUs of 0.20c (Corp), 0.57c (Pro) and a whopping 1.57c (Personal).

The last column is of all Ad supported blogs – Net Revenue $100, 46,000 users on average (doesn’t make sense given that all the subcategories have smaller average user bases, but its here for reference anyway)

Moral – By these figures, Pro Blogging in any sense or form reduces wealth rapidly – rather do loads of Amateur blogs:)

>From the report one gets a slightly different view:

The majority of bloggers we surveyed currently have advertising on their blogs. Among those with advertising, the mean annual investment in their blog is $1,800, but it’s paying off. The mean annual revenue is $6,000 with $75K+ in revenue for those with 100,000 or more unique visitors per month. Note: median investment and revenue (which is listed below [See our Analysis]) is significantly lower. They are also earning CPMs.

Bloggers are sophisticated in using self serve tools for search, display, and affiliate advertising, and are increasingly turning to ad and blog networks. Many bloggers without advertising may consider it when their blogs grow – the inability to set up advertising will not be a factor.

In other words, that hit head is making nearly all the money, if the Mean revenue is $6,000 and the Median is $200.

Now we have committed all sorts of analysins, for eg dividing median annual revenues by mean monthly unique visitors, but the data is directionally correct albeit dimensionally useless – so we await Day 4 with eager anticipation

Update – AVC gives another touchpoint – c150k visitors pm (I assume uniques by the way its written, c $30k max income pa – thats about 20c per year, an order of magnitude above the Thechnorati figures – the implication being, (as I stated above) that as you start to get to the bigger blogs, the values rise sharply.

Tags: Network, tools

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