Category data

Sandy and how the technology we build could serve us more effectively

Last week was a rough one here in New York City. People lost their homes, some a lot worse. We were lucky. I live downtown and all that my family and I had to deal with was no electricity for most of the week, no cell access and a lot of water in our kitchen, no one got hurt and the damage is all fixable. But the lack of basic technology services got me thinking about what could have worked differently. With all the technology that has been placed in the hands of users since the first personal computer I found it remarkable how little was useable. Let me start with a personal overview of our situation and then lay out some ideas about what could be done differently.

When Sandy hit my family and I found ourselves with:
– no power
– no cell phone access (ATT, our provider was down)
– Lack of reliable connectivity

For four days our only access to the internet at home was via one Verizon enabled iPad. Luck would have it, that this turned out to be the one Apple device you want. The iPad has the best battery of any the options available (iPhone, android phone, laptop), and the Verizon network proved to be far superior to ATT.

Yet many of the web sites we needed barely functioned. Con Edison was the worst. After 45 mins of dropped connections the ConEd website told us that they weren’t aware of an outage in our area . Power in all of lower manhattan was out and somehow the site couldn’t tell us that.  The map they had of outages had a few flags on it — those were the brave souls who persisted and reported an outage with pitch black all around them.  And from what I gather ConEd was way better than Connecticut Light and Power — their home page was still saying “Prepare for Sandy” days after the storm hit. News sites were too general, what I wanted was hyper local news. Twitter wasn’t useful. Twiter is hard to filter and the content stream moved too quickly to use effectively given intermittent connectivity. Facebook wasn’t useful, I wasn’t interested in pushing information out, I wanted to get information.

So what could have have been done differently? Here are five ideas:

1. Data and accessibility:

The data is there it just needs to be made accessible. ConEd and other utility service providers could design their websites for constrained circles of accessibility. Think of an inner most circle with no web access, just SMS. One ring outwards represents low bandwidth or intermittent access, mostly email, some web — and then the furthermost ring represents high bandwidth access. Ideally, utility websites should be adaptive across all these rings, at a minimum they should offer users the ability to navigate it at different levels, depending on the situation. So when an emergency hits users shouldn’t be faced with a site that is optimized for high bandwidth access with videos expelling things. What I wanted from the ConEd site was a simple status update of power restoration in our neighborhood. All the rest of the media and information on the website was of no use, in fact, it detracted from what should have been a simple experience.

Going one step further if ConEd and utility service providers made their basic service data accessible via API’s then it could easily be reformatted and delivered to people using the channel best suited to the situation. In the case of Sandy that would have been a simple web site, optimized for low bandwidth and intermittent connectivity, with neighborhood navigation. Someone would have made that site if ConEd and other utility providers made block level service status data available.

[update: there are a few end points that people found to ConEd data, that generated some data, for a good example see this thanks to @cmenscher who sent this to me and @ckundo who created the visualization]

And if service providers had basic API’s they could share them with each other. As @Auerbach reminded me ConEd may not actually know if power is down in your building but Time Warner Cable knows it. And the street lights have connectivity back to a central station. A little bit of data sharing could go a long way here.

2. Usability:

Utility web sites seem to have been designed primarily as marketing tools. This is backwards. The sites shouldn’t be managed by the marketing department, particularly in the case of a utility where customer churn is basically nonexistent. Take a look at the coned twitter feed: https://twitter.com/conedison. The number of messages with media, essentially promotional,is high. But ConEd and CLP are were at least active on Twitter this past weekend. In contrast AT&T’s marketing department seem to have gone home for the weekend.

Socialmedia is opening up channels for people to talk to companies and companies to talk to customers. The departmental lines between marketing and customer service are a fabrication of an era that is past. Customer service is becoming marketing and it should have primacy in situations like this. Companies and brands are starting to think they need to produce media in order to talk with customers. This makes sense in a marketing context but in a situation like Sandy it doesn’t. I’m not interested a Utilities video channel. What I want is usable information.

3. Simplify, Simplify, think /status

As technology advances systems become complex. During emergency situations that complexity needs to be unwound so that basic services remain available and accessible – the first and most basic is an awareness in an organization that systems, critical systems need to scale up and down this curve of complexity. If that awareness can become part of how we design technology then as new, more, complex functionality is added to a product will make the roll back actually possible.

Another approach to simplifying or unwinding a complex systems is for there to be basic standards that system providers agree to. Consider really simple things — i.e.: what if service providers adopted a standard so that users knew that if they went to www.coned.com/status or www.ATT.com/status or Twitter.com/status they would get a network status update. In emergencies simplicity of navigation goes a long, long way. There are simple solutions and while this disaster is fresh in our minds is a good time to consider a few.

4. City, local, government data hubs:

Government and city government’s first job is to keep citizens safe to that end government could play an important role as a hyper local data aggregator. If the service providers made service/status data accessible via API’s then cities could easily aggregate that down to a neighborhood level. What I really needed was a single page with aggregate information for power, cell access, flood levels for our neighborhood or even block.  This is a prototypical public good that local governments could offer citizens. Match that page with a simple notification system to alert me of changes and we would have a very simple, usable, local status page.  Note the data I’m talking about is not account level data, its simple service level availability data. This isn’t a radical shift in the role of government, or governments access to data — at some level data becomes a public good and government are the most natural and benign aggregator of that data.

5. Towards a Machine readable city:

By the end of this year there will be approximately 2.3bn people connected to the network. Thats a big number, but we are on the cusp of an explosion in that number. Sensors that communicate with purpose built devices are going to be everywhere (think fuel bands and Nests for consumers and for the enterprise think about all the industrial hardware that will be wired up with sensors to monitor use and state of wear).  Additionally, I believe, cities will become machine readable. Imagine if a city simply added to its street signs simple QR codes. Not only would this give added information to citizens but information could be programmatically updated in the case of an emergency like Sandy. Over the coming decade billions of sensors get wired into the network, many of them in our cities. Most of these sensors primary purpose will be commercial yet there will be some level of aggregate data that the city government should have access to aggregate.  Weatherunderground had some useful maps of the tide levels on monday night as Sandy approached but the detail needed on a local level to make informed decisions was missing.

What happened here in NYC was nothing compared to the earthquake in Japan and the nuclear fallout that followed. Yet alot of our technology failed us. Technology needs to be designed as flexible, adaptable to the context that it exists in. Over the coming decade we will see contextual computing upend many of the services that today we take for granted. Building and designing technology with events like Sandy as a consideration are a first step down the path of making computing and the machines we depend on, function regardless and in regard of the context they exist in.

 

betaworks 2012 shareholder letter

Related links:

Ongoing tracking of the real time web …

The last post that I did about real time web data mixed data with a commentary and a fake headline about how data is sometimes misunderstood in regards to the real time web.    This post repeats some of that data but the focus of the post is the data.   I will update the post periodically with relevant data that we see at betaworks or that others share with us.   To that end this post is done in reverse order with the newest data on top.

Tracking the real time web data

The measurement tools we have still only sometimes work for counting traffic to web pages and they certainly dont track or measure traffic in streams let alone aggregate up the underlying ecosystems that are emerging around these new markets.  At betaworks we spend a lot of time looking at and tracking this underlying data set.   It’s our business and its fascinating.   Like many companies each of the individual businesses at betaworks have fragments of data sets but because betaworks acts as ecosystem of companies we can mix and match the data to get results that are more interesting and hopefully offer greater insight

——————————-

(i) tumblr growth for the last half of 2009

Another data point re: growth of the real time web through the second half of last year through to Jan 18th of this year.  tumblr continues to kill it.     I read this interesting post yesterday about how tumblr is leading in its  category through innovation and simple, effective, product design.   The compete numbers quoted in that post are less impressive than these directly measured quantcast numbers.


(h) Twitter vs. the Twitter Ecosystem

Fred Wilson’s post adds some solid directional data on the question of the size of the ecosystem.   “You can talk about Twitter.com and then you can talk about the Twitter ecosystem. One is a web site. The other is a fundamental part of the Internet infrastructure. And the latter is 3-5x bigger than the former and that delta is likely to grow even larger.”

(g) Some early 2010 data points re: the Real Time Web

  • Twitter: Jan 11th was the highest usage day ever (source: @ev via techcrunch)
  • Tweetdeck: did 4,143,687 updates on Jan 8, yep 4m. Or, 48 per second (source: Iain Dodsworth / tweetdeck internal data)
  • Foursquare: Jan 9th biggest day ever.    1 update or check-in per second (source: twitter and techcrunch)
  • Daily Booth: in past 30 days more than 10mm uniques (source: dailybooth internal data)
  • bit.ly: last week was the largest week ever for clicks on bit.ly links. 564m were clicked on in total. On the Jan 6th there were a record of 98m decodes.    1100 clicks every second.

(f) Comparing the real time web vs. Google for the second half of 2009

Andrew Parker commented on the last post that the chart displaying the growth trends was hard to decipher and that it maybe simpler to show month over month trending.  It turns out the that month over month is also hard to decipher.   What is easier to read is this summary chart.    It shows the average month over month growth rates for the RT web sites (the average from Chart A).   Note 27.33% is the average growth rate for the real time web companies in 2009 — that’s astounding.    The comparable number for the second half of 2009 was 10.5% a month — significantly lower but still a very big number for m/m growth.

(e) Ongoing growth of the real time stream in the second half of 2009

This is a question people have asked me repeatedly in the past few weeks.  Did the real time stream grow in Q4 2009?    It did.    Not at the pace that it grew during q1-q3, but our data at betaworks confirms continued growth.   One of the best proxies we use for directional trending in the real time web are the bit.ly decodes.   This is the raw number of bit.ly links that are clicked on across the web.    Many of these clicks occur within the Twitter ecosystem, but a large number are outside of Twitter, by people and by machines — there is a surprising amount of diversity within the real time stream as I posted about a while back.

Two charts are displayed below.    On the bottom are bit.ly decodes (blue) and encodes (red)  running through the second half of last year.    On the top is a different but related metric.   Another betaworks company is Twitterfeed.    Twitterfeed is the leading platform enabling publishers to post from their sites into Twitter and Facebook.    This chart graphs the total number of feeds processed (blue) and the total number of publishers using Twitterfeed, again through the second half of the year (note if the charts inline are too small to read you can click though and see full size versions).   As you can see similar the left hand chart — at Twitterfeed the growth was strong for the entire second half of 2009.

Both these charts illustrate the ongoing shift that is taking place in terms of how people use the real time web for navigation, search and discovery.    My preference is to look at real user interactions as strong indicators of user behavior.   For example I actually find Google trends more useful often than comScore, Compete or the other “page” based measurement services.   As interactions online shift to streams we are going to have to figure out how measurement works. I feel like today we are back to the early days of the web when people talked about “hits” — it’s hard to parse the relevant data from the noise.  The indicators we see suggest that the speed at which this shift to the real time web is taking place is astounding.   Yet it is happening in a fashion that I have seen a couple of times before.

(d) An illustration of the step nature of social growth. bit.ly weekly decodes for the second half of 2009.

Most social networks I have worked with have grown in a step function manner.  You see this clearly when you zoom into the bit.ly data set and look at weekly decodes, illustrated above.   You often have to zoom in and out of the data set to see and find the steps but they are usually there.     Sometimes they run for months — either up or sideways.    You can see the steps in Facebook growth in 2009.    I saw effect up close with ICQ, AIM, Fotolog, Summize and now with bit.ly.   Someone smarter than me has surely figured out why these steps occur.    My hypothesis is that as social networks grow they jump in a sporadic fashion from one dense cluster of relationships to a new one.   The upward trajectory is the adoption cycle of that new, dense cluster and the flat part of the step is the period between the step to next cluster.     Blended in here there are clearly issues of engagement vs. trial.   But it’s hard to weed those out from this data set.   As someone mentioned to me in regards to the last post this is a property of scale-free networks.

(c) Google and Amazon in 2009

Google and Amazon — this is what it looked like in 2009:

It’s basically flat.     Pretty much every user in the domestic US is on Google for search and navigation and on Amazon for commerce — impressive baseline numbers but flat for the year (source: Quantcast).  So then lets turn to Twitter.

(b) Twitter – an estimate of Twitter.com and the Twitter ecosystem

Much ink has been spilt over Twitter.com’s growth in the second half of the year.   During the first half of the year Twitter’s experience hyper growth — and unprecedented media attention.    In the second half of the year the media waned, the service went through what I suspect was a digestion phase — that step again?     Steps aside — because I dont in anyway seek to represent Twitter Inc. — there are two questions that in my mind haven’t been answered fully:

(i) what international growth in the second half of 2009?, that was clearly a driver for Facebook in ’09.  Recent data suggests growth continued to be strong.

(ii) what about the ecosystem.

Unsurprisingly its the second question that interests me the most.    So what about that ecosystem?    We know that approx 50% of the interactions with the Twitter API occur outside of Twitter.com but many of those aren’t end user interactions.     We also know that as people adopt and build a following on Twitter they often move up to use one of the client or vertical specifics applications to suit their “power” needs.   At TweetDeck we did a survey of our users this past summer.     The data we got suggested 92% of them then use Tweetdeck everyday — 51% use Twitter more frequently since they started using TweetDeck.  So we know there is a very engaged audience on the clients.     We also know that most of the clients arent web pages — they are flash, AIR, coco, iPhone app’s etc. all things that the traditional measurement companies dont track.

What I did to estimate the relative growth of the Twitter ecosystem is the following.   I used Google Trends and compiled data for Twitter and the key clients.    I then scaled that chart over the Twitter.com traffic.   Is it correct? — no.   Is it made up? — no.   It’s a proxy and this is what it looks like (again, you can click the chart to see a larger version).

Similar to the Twitter.com traffic you see the flattening out of the ecosystem in the summer.    But you see growth in the forth quarter that returns to the summer time levels.     I suspect if you could zoom in and out of this the way I did above you would see those steps again.

(a) The Real Time Web in 2009

Add in Facebook (blue) and Meebo (green) both steaming ahead — Meebo had a very strong end of year.    And then tile on top the bit.ly data and the Twitterfeed numbers (bit.ly on the right hand scale) and you have an overall picture of growth of the real time web vs. Google and Amazon.   As t

charting the real time web
OR
the curious tale of how TechCrunch traffic inexplicably fell off a cliff in December

For a while now I have been thinking about doing a post about some of the data we track at betaworks.   Over the past few months people have written about Twitter’s traffic being up, down or sideways — the core question that people are asking is the real time web growing or not, is this hype or substance?     Great questions — the answer to all of the above is from the data set I see: yes.   Adoption and growth is happening pretty much across the board — and in some areas its happening at an astounding pace.    But tracking this is hard.   It’s hard to measure something that is still emerging.    The measurement tools we have still only sometimes work for counting traffic to web pages and they certainly dont track or measure traffic in streams let alone aggregate up the underlying ecosystems that are emerging around these new markets.  At betaworks we spend a lot of time looking at and tracking this underlying data set.   It’s our business and its fascinating.

I was inspired to finally write something by first a good experience and then a bad one.    First the good one.    Earlier this week I saw a Tweet from Marshall Kirkpatrick about Gary Hayes’s social media counter.    It’s  very nicely done — and an embed is available.     This is what it looks like (note the three buttons on top are hot, you can see the social web, mobile and gaming):

The second thing was less fun but i’m sure it has happened to many an entrepreneur.    I was emailed earlier this week by a reporter asking about some data – I didnt spend the time to weed through the analysis and the reporter published data that was misleading.    More on this incident later.

Lets dig into some data.    First — addressing the question people have asked me repeatedly in the past few weeks.  Did the real time stream grow in Q4 2009?    It did.    Not at the pace that it grew during q1-q3, but our data confirms continued growth.   One of the best proxies we use for directional trending in the real time web are the bit.ly decodes.   This is the raw number of bit.ly links that are clicked on across the web.    Many of these clicks occur within the Twitter ecosystem, but a large number are outside of Twitter, by people and by machines — there is a surprising amount of diversity within the real time stream as I posted about a while back.  Two charts are displayed below.    On the left there are bit.ly decodes (blue) and encodes (red)  running through the second half of last year.    On the right is a different but related metric.   Another betaworks company is Twitterfeed.    Twitterfeed is the leading platform enabling publishers to post from their sites into Twitter and Facebook.    This chart graphs the total number of feeds processed (blue) and the total number of publishers using Twitterfeed, again through the second half of the year (note if the charts inline are too small to read you can click though and see full size versions).   As you can see similar the left hand chart — at Twitterfeed the growth was strong for the entire second half of 2009.

Both these charts illustrate the ongoing shift that is taking place in terms of how people use the real time web for navigation, search and discovery.    My preference is to look at real user interactions as strong indicators of user behavior.   For example I actually find Google trends more useful often than comScore, Compete or the other “page” based measurement services.   As interactions online shift to streams we are going to have to figure out how measurement works. I feel like today we are back to the early days of the web when people talked about “hits” — it’s hard to parse the relevant data from the noise.  The indicators we see suggest that the speed at which this shift to the real time web is taking place is astounding.   Yet it is happening in a fashion that I have seen a couple of times before.

Most social networks I have worked with have grown in a step function manner.  You see this clearly when you zoom into the bit.ly data set and look at weekly decodes.   This is less clear but also visible when you look at daily trending data (on the right) — but add a 3 week moving average on top of that and you can once again see the steps.   You often have to zoom in and out of the data set to see and find the steps but they are usually there.     Sometimes they run for months — either up or sideways.      I saw this with ICQ, AIM, Fotolog, Summize through to bit.ly.   Someone smarter than me has surely figured out why these steps occur.    My hypothesis is that as social networks grow they jump in a sporadic fashion to a new dense cluster or network of relationships.   The upward trajectory is the adoption cycle of that new, dense cluster and the flat part of the step is the period between the step to next cluster.     Blended in here there are clearly issues of engagement vs. trial.   But it’s hard to weed those out from this data set.   I learnt a lot of this from Yossi Vardi and Adam Seifer.    Two people I had the privilege of working with over the years — two people whose DNA is wired right into this stuff.  At Fotolog Adam could take the historical data set and illustrate how these clusters moved — in steps — from geography to geography, its fascinating.

TechCrunch falls off a cliff

Ok I’m sure there are some people reading who are thinking — well this is interesting but I actually want to read about TechCrunch falling off a traffic cliff.   I’m sorry – I actually don’t have any data to suggest that happened.  After noting yesterday that provocative headline is  sometimes a substitute for data I thought — heck I can do this too!    This section of the post is more of a cautionary tale — if you are confused by this twist let me back up to where I started.   I mentioned that there were two motivations for me sitting down and writing this post.   The second one was that earlier this week  TechCrunch story ran this week saying that bit.ly market share had shifted dramatically.     It hasn’t.   The data was just misunderstood by the reporter.   The tale (I did promise a tale) began last August when TechCrunch ran the following chart about the market share of URL shorteners.

The pie chart showed the top 5 URL shorteners and then calculated the market share each had  — what percent each was *of* the top five.     The  data looks like this:

bit.ly 79.61%
TinyURL 13.75%
is.gd 2.47%
ow.ly 2.26%
ff.im 1.92%
(79.61+13.75+2.47+2.26+1.92 = 100)
The comparable data from yesterday is:

bit.ly = 75%
TinyURL = 10%
ow.ly = 6%
is.gd = 4%
tumblr = 4%
(again this adds up to 100%)

Not much news in those numbers, especially when you consider they come from the Twitter “garden hose” (a subset of all tweets) and swing by as much as +/- 5% daily.   The tumblr growth into the top 5 and the ow.ly bump up is nice shift for them – but not really a story.     The hitch was that the reporter didn’t consider that there are other URL’s in the Twitter stream aside from these five.   Some are short URL’s and some aren’t.   So this metric doesn’t accurately reflect overall short URL market share — it shows the shuffling of market share amongst the top five.   But media will be media.   I saw a Tweet this week about how effective Twitter is at disseminating information — true and false — despite all the shifts that are going on headlines in a sense carry even more weight than in the “read all about it” days.

The lesson here for me was the importance of helping reporters and analysts get access to the underlying data — data they can use effectively.   We sent the reporter the  data but he saw a summary data set that included the other URL’s and didn’t understand that back in August there were also “other” URL’s.   After the fact we worked to sort this out and he put a correction in his post.   But the headline was off and running — irrespective of how dirty or clean the data was.   Basic mistake — my mistake — and this was with a reporter who knows this stuff well.   Given the paucity of data out there and the emergent state of the real time web  this stuff is bound to happen.

Ironically, yesterday, bit.ly hit an all time high in terms of decodes — over 90m.   But back to the original question — there is a valid question the reporter was seeking to understand, namely: what is the market share of dem short thingy’s?      We track this metric — using the Twitter garden hose and identifying most of the short URL’s to produce a ranking (note its a sample, so the occurrences are a fraction of the actuals).     And it’s a rolling 24 hr view — so it moves around quite a bit — but nonetheless it’s informative.  This is what it looked like yesterday:

Over time this data set is going to become harder to use for this purpose.    At bit.ly we kicked off our white label service before the holidays.   Despite months of preparation we weren’t expecting the demand.   As we provision and setup the thousands of publishers, blogger and brands who want white label services its going to result in a much more diverse stream of data in the garden hose.

Real Time Web Data

Finally I thought it would be interesting to try to get a perspective on the emergence of the real time web in 2009 — how did its growth compare and contrast with the incumbent web category leaders?    Let me try to frame up some data around this.   Hang in there, some of the things I’m going to do are hacks (at best) — as I said I was inspired!   Lets start with the user growth in the US among the current web leaders — Google and Amazon — this is what it looked like in 2009:

It’s basically flat.     Pretty much every user in the domestic US is on Google for search and navigation and on Amazon for commerce — impressive baseline numbers but flat for the year (source: Quantcast).  So then lets turn to Twitter.    Much ink has been spilt over Twitter.com’s growth in the second half of the year.   During the first half of the year Twitter’s growth, I suspect, was driven to a great extent by the unprecedented media attention it received — media and celebrities were all over it.    Yet in the second half of the year that waned and the traffic numbers to the Twitter.com web site were flat for the second half of the year.    That step issue again?

Placing steps aside — because I dont in anyway seek to represent Twitter Inc. — there are two questions that haven’t been answered  (a) what about international growth, that was clearly a driver for Facebook in ’09, where was Twitter internationally?   (b) what about the ecosystem.     Unsurprisingly its the second question that interests me the most.    So what about that ecosystem?

We know that approx 50% of the interactions with the Twitter API occur outside of Twitter.com but many of those aren’t end user interactions.     We also know that as people adopt and build a following on Twitter they often move up to use one of the client or vertical specifics applications to suit their “power” needs.   At TweetDeck we did a survey of our users this past summer.     The data we got suggested 92% of them then use Tweetdeck everyday — 51% use Twitter more frequently since they started using TweetDeck.  So we know there is a very engaged audience on the clients.     We also know that most of the clients arent web pages — they are flash, AIR, coco, iPhone app’s etc. all things that the traditional measurement companies dont track.

What I did to estimate the relative growth of the Twitter ecosystem is the following.   I used Google Trends and compiled data for Twitter and the key clients.    I then scaled that chart over the Twitter.com traffic.   Is it correct? — no.   Is it made up? — no.   It’s a proxy and this is what it looks like (again, you can click the chart to see a larger version):

Similar to the Twitter.com traffic you see the flattening out in the summer.    But similar to the data sets referenced above you see growth in the forth quarter.     I suspect if you could zoom in and out of this the way I did above you would see those steps again.     So lets put it all together!    Its one heck of a busy chart.   Add in Facebook (blue) and Meebo (green) both steaming ahead — Meebo had a very strong end of year.    And then tile on top the bit.ly data and the Twitterfeed numbers (both on different scales) and you have an overall picture of growth of the real time web vs. Google and Amazon.

Ok.   One last snap shot then im wrapping up.    Chartbeat — yep another betaworks company — had one of its best weeks ever this past week — no small thanks to Jason’s Calacanis’s New Year post about his Top 10 favorite web products of 2009.   To finish up here is a video of the live traffic flow coming into Fred Wilson’s blog at AVC.com on the announcement of the Google Nexus one Phone.    Steve Gilmore mentioned the other week how sometimes interactions in the real time web just amaze one.    Watching people swarm to a site is a pretty enthralling experience.    We have much work to do in 2010.    Some of it will be about figuring out how to measure the real time web.   Much of it will be continuing to build out the real time web and learning about this fascinating shift taking place right under our feet.

random footnote:

A data point I was sent this am by Iain that was interesting — yet it didnt seem to fit in anywhere?!   Asian twitter clients were yesterday over 5% of the requests visible in the garden hose.

diversity within the real time stream

I got a call on Friday from a journalist at the Financial Times who was writing on the Twitter ecosystem. We had an interesting conversation and he ran his piece over the weekend Twitter branches out as London’s ‘ecosystem’ flies.

As the title suggests the focus was on the Twitter ecosystem in London.    Our conversation also touched on the overall size and health of the real-time ecosystem — this topic didn’t make it into the article. It’s hard to gauge the health of a business ecosystem that is still very much under development and has yet to mature into one that produces meaningful revenues. Yet the question got me thinking — it also got me thinking that it has been a while since I had posted here. It was one busy summer. I have a couple of long posts I’m working on but for now I want to do this quick post on the real-time ecosystem and in it offer up some metrics on its health.

Back in June I did a presentation at Jeff Pulver’s 140conf, the topic of which was the real-time / Twitter ecosystem.   Since then, I have been thinking about the diversity of data sources, notably the question of where people are publishing and consuming real-time data streams. At betaworks we are fairly deep into the real time / Twitter ecosystem.  In fact, every company at betaworks is a participant, in one manner or another, in this ecosystem, and that’s a feature, not a bug! Of the 20 or so companies in the betaworks network, there is a subset that we we operate; one of those is bit.ly.

2puffsIn an attempt to answer this question about the diversity of the ecosystem, let me run through some internal data from bit.ly.   bit.ly is a URL shortener that offers among other things real-time tracking of the clicks on each link (add “+” to any bit.ly URL to see this data stream).   With a billion bit.ly links clicked on in August — 300m last week — bit.ly has become almost part of the infrastructure of the real time cloud.  Given its scale bit.ly’s data is a fair proxy for the activity of the real-time stream, at least of the links in the stream.

On Friday of this week (yesterday) there were 20,924,833 bit.ly links created across the web (we call these “encodes”). These 20.9m encodes are not unique URL’s, since one popular URL might have been shortened by multiple people. But each encode represents intentionality of some form. bit.ly in turn retains a parent : child mapping, so that you can see what your sharing of a link generates vs. the population (e.g., I shared a video on Twitter the other day; my specific bit.ly link got 88 clicks, out of a total of 250 clicks on any bit.ly link to that same video.  see http://bit.ly/Rmi25+).

So where were these 20.9m encodes created? Approximately half of the encodes took place within the Twitter ecosystem. No surprise here: Twitter is clearly the leading public, real-time stream and about 20% of the updates on Twitter contain at least one link, approx half of which are bit.ly links.   But here is something surprising: less than 5% of the 20.9m came from Twitter.com (i.e., from Twitter’s use of bit.ly as the default URL-shortener). Over 45% of the total encodes came from other services associated in some way with Twitter – i.e. the Twitter ecosystem — a long and diverse list of services and companies within the ecosystem who use bit.ly.

The balance of the encodes came from other areas of the real time web, outside of Twitter. Google Reader incorporated bit.ly this summer, as did Nokia, CBS, Dropbox, and some tools within Facebook. And then of course people use the bit.ly web site — which has healthy growth — to create links and then share them via instant-messaging services, MySpace, email, and countless other communications tools.

The bit.ly links that are created are also very diverse. Its harder to summarise this without offering a list of 100,000 of URL’s — but suffice it to say that there are a lot of pages from the major web publishers, lots of YouTube links, lots of Amazon and eBay product pages, and lots of maps. And then there is a long, long tail of other URL’s. When a pile-up happens in the social web it is invariably triggered by link-sharing, and so bit.ly usually sees it in the seconds before it happens.

This data says to me that the ecosystem as a whole is becoming fairly diverse. Lots of end points are publishing (i.e. creating encodes) and then many end points are offering ways to use the data streams.

In turn, this diversity of the emerging ecosystem is, I believe, an indicator of its health. Monocultures aren’t very resilient to change; ecosystems tend to be more resilient and adaptable. For me, these few data points suggest that the real-time stream is becoming more and more interesting and more and more diverse.

Distribution … now

In February 1948, Communist leader Klement Gottwald stepped out on the balcony of a Baroque palace in Prague to address hundreds of thousands of his fellow citizens packed into Old Town Square. It was a crucial moment in Czech history – a fateful moment of the kind that occurs once or twice in a millennium.

Gottwald was flanked by his comrades, with Clementis standing next to him. There were snow flurries, it was cold, and Gottwald was bareheaded. The solicitous Clementis took off his own fur cap and set it on Gottwald’s head.

The Party propaganda section put out hundreds of thousands of copies of a photograph of that balcony with Gottwald, a fur cap on his head and comrades at his side, speaking to the nation. On that balcony the history of Communist Czechoslovakia was born. Every child knew the photograph from posters, schoolbooks, and museums.

Four years later Clementis was charged with treason and hanged. The propaganda section immediately airbrushed him out of history, and obviously, out of all the photographs as well. Ever since, Gottwald has stood on that balcony alone. Where Clementis once stood, there is only bare palace wall. All that remains of Clementis is the cap on Gottwald’s head.

Book of Laughter and Forgetting, Milan Kundera

The rise of social distribution networks

Over the past year there has been a rapid shift in social distribution online.    I believe this evolution represents an important change in how people find and use things online. At betaworks I am seeing some of our companies get 15-20% of daily traffic via social distribution — and the percentage is growing.    This post outlines some of the aspects of this shift that I think are most interesting.   The post itself is somewhat of a collage of media and thinking.

Distribution is one of the oldest parts of the media business.    Content is assumed to be king so long as you control the distribution flow to that content. From newspapers to NewsCorp companies have understand this model well.   Yet this model has never suited the Internet very well.     From the closed network ISP’s to Netcenter.   Pathfinder to Active desktop, Excite Lycos, Pointcast to the Network computer.   From attempts to differentially price bits to preset bookmarks on your browser — these are all attempts at gate keeping attention and navigation online.    Yet the relative flatness of the internet and its hyperlinked structure has offered people the ability to route around these toll gates.   Rather than client software or access the nexus of distribution became search.    Today there seems to be a new distribution model that is emerging.   One that is based on people’s ability to publically syndicate and distribute messages — aka content — in an open manner.    This has been a part of the internet since day one — yet now its emerging in a different form — its not pages, its streams, its social and so its syndication.    The tools serve to produce, consume, amplify and filter the stream.     In the spirit of this new wave of Now Media here is a collage of data about this shift.

Dimensions of the now web and how is it different?

Start with this constant, real time, flowing stream of data getting published, republished, annotated and co-opt’d across a myriad of sites and tools.    The social component is complex — consider where its happening.    The facile view is to say its Twitter, Facebook, Tumblr or FriendFeed — pick your favorite service.    But its much more than that because all these sites are, to varying degrees, becoming open and distributed. Its blogs, media storage sites (ie: twitpic) comment boards or moderation tools (ie: disqus) — a whole site can emerge around an issue — become relevant for week and then resubmerge into the morass of the data stream, even publishers are jumping in, only this week the Times pushed out the Times Wire.    The now web — or real time web — is still very much under construction but we are back in the dark room trying to understand the dimensions and contours of something new, or even to how to map and outline its borders. Its exciting stuff.

Think streams …

First and foremost what emerges out of this is a new metaphor — think streams vs. pages.     This seems like an abstract difference but I think its very important.    Metaphors help us shape and structure our perspective, they serve as a foundation for how we map and what patterns we observe in the world.     In the initial design of the web reading and writing (editing) were given equal consideration – yet for fifteen years the primary metaphor of the web has been pages and reading.     The metaphors we used to circumscribe this possibility set were mostly drawn from books and architecture (pages, browser, sites etc.).    Most of these metaphors were static and one way.     The steam metaphor is fundamentally different.  Its dynamic, it doesnt live very well within a page and still very much evolving.    Figuring out where the stream metaphor came from is hard — my sense is that it emerged out of RSS.    RSS introduced us to the concept of the web data as a stream — RSS itself became part of the delivery infrastructure but the metaphor it introduced us to is becoming an important part of our eveyday day lives.

A stream.   A real time, flowing, dynamic stream of  information — that we as users and participants can dip in and out of and whether we participate in them or simply observe we are are a part of this flow.     Stowe Boyd talks about this as the web as flow: “the first glimmers of a web that isnt about pages and browsers” (see this video interview,  view section 6 –> 7.50 mins in).       This world of flow, of streams, contains a very different possibility set to the world of pages.   Among other things it changes how we perceive needs.  Overload isnt a problem anymore since we have no choice but to acknowledge that we cant wade through all this information.   This isnt an inbox we have to empty,  or a page we have to get to the bottom of — its a flow of data that we can dip into at will but we cant attempt to gain an all encompassing view of it.     Dave Winer put it this way in a conversation over lunch about a year ago.    He said “think about Twitter as a rope of information — at the outset you assume you can hold on to the rope.  That you can read all the posts, handle all the replies and use Twitter as a communications tool, similar to IM — then at some point, as the number of people you follow and follow you rises — your hands begin to burn. You realize you cant hold the rope you need to just let go and observe the rope”.      Over at Facebook Zuckerberg started by framing the flow of user data as a news feed — a direct reference to RSS — but more recently he shifted to talk about it as a stream: “… a continuous stream of information that delivers a deeper understanding for everyone participating in it. As this happens, people will no longer come to Facebook to consume a particular piece or type of content, but to consume and participate in the stream itself.”    I have to finish up this section on the stream metaphor with a quote from Steve Gillmor.    He is talking about a new version of Friendfeed, but more generally he is talking about real time streams.     The content and the language — this stuff is stirring souls.

We’re seeing a new Beatles emerging in this new morning of creativity, a series of devices and software constructs that empower us with both the personal meaning of our lives and the intuitive combinations of serendipity and found material and the sturdiness that only rigorous practice brings. The ideas and sculpture, the rendering of this supple brine, we’ll stand in awe of it as it is polished to a sparkling sheen. (full article here)

Now, Now, Now

The real time aspect of these streams is essential.  At betaworks we are big believers in real time as a disruptive force — it’s an important aspect of many of our companies — it’s why we invested a lot of money into making bit.ly real time.  I remember when Jack Dorsey first saw bit.ly’s  plus or info page (the page you get to by putting a “+” at the end of any bit.ly URL) —  he said this is “great but it updates on 30 min cycles, you need to make it real time”.   This was August of ’08 — I registered the thought, but also thought he was nuts.    Here we sit in the spring of ’09 and we invested months in making bit.ly real time —  it works, and it matters.   Jack was right — its what people want to see the effects on how a meme is are spreading — real time.   It makes sense — watching a 30 min delay on a stream — is somewhere between weird and useless.   You can see an example of the real time bit.ly traffic flow to an URL  here. Another betaworks company, Someecards, is getting 20% of daily traffic from Twitter.   One of the founders Brook Lundy said the following “real time is now vital to what do.    Take the swine flu — within minutes of the news that a pandemic level 5 had been declared — we had an ecard out on Twitter”.    Sardonic, ironic, edgy ecards — who would have thought they would go real time.    Instead of me waxing on about real time let me pass the baton over to Om — he summarizes the shift as well as one could:

  1. “The web is transitioning from mere interactivity to a more dynamic, real-time web where read-write functions are heading towards balanced synchronicity. The real-time web, as I have argued in the past, is the next logical step in the Internet’s evolution. (read)
  2. The complete disaggregation of the web in parallel with the slow decline of the destination web. (read)
  3. More and more people are publishing more and more “social objects” and sharing them online. That data deluge is creating a new kind of search opportunity. (read)”

Only connect …

The social aspects of this real time stream are clearly a core and emerging property.   Real time gives this ambient stream a degree of connectedness that other online media types haven’t.  Presence, chat, IRC and instant messaging all gave us glimmers of what was to come but the “one to one” nature of IM meant that we could never truly experience its social value.    It was thrilling to know someone else was on the network at the same time as you — and very useful to be able to message them but it was one to one.    Similarly IRC and chats rooms were open to one to many and many to many communications but they usually weren’t public.   And in instances that they were public the tools to moderate and manage the network of interactions were missing or crude.   In contrast the connectedness or density of real time social interactions emerging today is astounding — as the examples in the collage above illustrate.    Yet its early days.    There are a host of interesting questions on the social front.    One of the most interesting is, I think, how willthe different activity streams intersect and combine / recombine or will they simple compete with one another?      The two dominant, semi-public, activity streams today are Facebook and Twitter.    It is easy to think about them as similar and bound for head on competition — yet the structure of these two networks is fairly different.    Whether its possible or desirable to combine these streams is an emerging question — I suspect the answer is that over time they will merge but its worth thinking about the differences when thinking about ways to bring them together.      The key difference I observe between them are:

#1. Friending on Facebook is symmetrical — on Twitter it’s asymmetrical.    On Facebook if I follow you, you need to follow me, not so on Twitter, on Twitter I can follow you and you can never notice or care.   Similarly, I can unfollow you and again you may never notice or care.   This is an important difference.   When I ran Fotolog I observed the dynamics associated with an asymmetrical friend network — it is, I think, a closer approximation of the way human beings manage social relationships.    And I wonder the extent to which the Facebook sysmetrical friend network was / is product of the audience for which Facebook was intially created (students).   When I was a student I was happy to have a symmetrical social network, today not so much.

#2. The data on Facebook is assumed to be mostly private, or shared within private groups, Facebook itself has been mostly closed to the open web — and Facebook asserts a level of ownership over the data that passes through its network.   In contrast the data on Twitter is assumed to be public and Twitter asserts very few rights over the underlying data.    These are broad statements — worth unpacking a bit.    Facebook has been called a walled garden — there are real advantages to a walled garden — AOL certainly benefited from been closed to the web for a long long time.   Yet the by product of a closed system is that (a) data is not accessible or searchable by the web in general –ie: you need to be inside the garden to navigate it  (b) it assumes that the pace innovation inside the garden will match or exceed the rate of innovation outside of the garden and (c) the assertion of rights over the content within the garden means you have to mediate access and rights if and when those assets flow out of the garden.   Twitter takes a different approach.     The core of Twitter is a simple transport for the flow of data — the media associated with the post is not placed inline — so Twitter doesnt need to assert rights over it.    Example — if I post a picture within Facebook, Facebook asserts ownership rights over that picture, they can reuse that picture as they see fit.    If i leave Facebook they still have rights to use the image I posted.    In contrast if I post a picture within Twitter the picture is hosted on which ever service I decided to use.   What appears in Twitter is a simple link to that image.   I as the creator of that image can decide whether I want those rights to be broad or narrow.

#3. Defined use case vs. open use case.    Facebook is a fantastically well designed set of work-flows or use cases.   I arrive on the site and it present me with a myriad of possible paths I can follow to find people, share and post items and receive /measure associated feedback. Yet the paths are defined for the users.   If Facebook  is the well organized, pre planned town Twitter is more like new urban-ism — its organic and the paths are formed by the users.    Twitter is dead simple and the associated work-flows aren’t defined, I can devise them for myself (@replies, RT, hashtags all arose out of user behavior rather than a predefined UI.   At Fotolog we had a similar set of emergent, user driven features.  ie:  groups formed organically and then over time the company integrated the now defined work-flow into the system).    There are people who will swear Twitter is a communications platform, like email or IM — other say its micro-blogging — others say its broadcast — and the answer is that its all of the above and more.   Its work flows are open available to be defined by users and developers alike.   Form and content are separated in way that makes work-flows, or use cases open to interpretation and needs.

As I write this post Facebook is rapidly re-inventing itself on all three of the dimensions above.    It is changing at a pace that is remarkable for a company with its size membership.     I think its changing because Facebook have understood that they cant attempt to control the stream — they need to turn themselves inside out and become part of the web stream.   The next couple of years are going to be pretty interesting.       Maybe E.M. Forrester had it nailed in Howard’s End:  Only connect! That was the whole of her sermon  … Live in fragments no longer.

The streams are open and distributed and context is vital

The streams of data that constitute this now web are open, distributed, often appropriated, sometimes filtered, sometimes curated but often raw.     The streams make up a composite view of communications and media — one that is almost collage like (see composite media and wholes vs. centers).     To varying degrees the streams are open to search / navigation tools and its very often long, long tail stuff.  Let me run out some data as an example.     I pulled a day of bit.ly data — all the bit.ly links that were clicked on May 6th.      The 50 most popular links  generated only 4.4% (647,538) of the total number of clicks.    The top 10 URL’s were responsible for half (2%) of those 647,538 clicks.  50% of the total clicks (14m) went to links that received  48 clicks or less.   A full 37% of the links that day received only 1 click.   This is a very very long and flat tail — its more like a pancake.   I see this as a very healthy data set that is emerging.

Weeding out context out of this stream of data is vital.     Today context is provided mostly via social interactions and gestures.    People send out a message — with some context in the message itself and then the network picks up from there.   The message is often re-tweeted, favorite’d,  liked or re-blogged, its appropriated usually with attribution to creator or the source message — sometimes its categorized with a tag of some form and then curation occurs around that tag — and all this time, around it spins picking up velocity and more context as it swirls.    Over time  tools will emerge to provide real context to these pile up’s.   Semantic extraction services like Calais, Freebase, Zemanta, Glue, kynetx and Twine will offer a windows of context into the stream — as will better trending and search tools.      I believe search gets redefined in this world, as it collides with navigation– I blogged at length on the subject last winter.   And filtering  becomes a critical part of this puzzle.   Friendfeed is doing fascinating things with filters — allowing you to navigate and search in ways that a year ago could never have been imagined.

Think chunk
Traffic isnt distributed evenly in this new world.      All of a sudden crowds can show up on your site.     This breaks with the stream metaphor a little — its easy to think of flows in the stream as steady — but you have to think in bursts — this is where words like swarms become appropriate.    Some data to illustrate this shift.   The charts below are tracking the number of users simultaneously on a site.    The site is a political blog.    You can see on the left that the daily traffic flows are fairly predictable — peaking around 40-60 users on the site on an average day, peaks are around mid day.    Weekends are slow  — the chart is tracking Monday to Monday, from them wednesday seems to be the strongest day of the week — at least it was last week.   But then take a look at the chart on the right — tracking the same data for the last 30 days.   You can see that on four occasions over the last 30 days all of a sudden the traffic was more than 10x the norm.   Digging into these spikes — they were either driven by a pile up on Twitter, Facebook, Digg or a feature on one of the blog aggregation sites.    What do you do when out of no where 1000 people show up on your site?

CB traffic minnesotaindependent.com

The other week I was sitting in NY on 14th street and 9th Avenue with a colleague talking about this stuff.   We were accross the street from the Apple store and it struck me that there was a perfect example of a service that was setup to respond to chunky traffic.     If 5,000 people show up at an Apple store in the next 10 minutes — they know what to do.   It may not be perfect but they manage the flow of people in and out of the store, start a line outside, bring people standing outside water as they wait. maybe take names so people can leave and come back.   I’ve experienced all of the above while waiting in line at that store.   Apple has figured out how to manage swarms like a museum or public event would.    Most businesses and web sites have no idea how to do this.    Traffic in the other iterations of the web was more or less smooth but the future isnt smooth — its chunky.    So what to do when a burst takes place?   I have no real idea whats going to emerge here but cursory thoughts include making sure the author is present to manage comments etc., build in a dynamic mechanism to alert the crowd to other related items?    Beyond that its not clear to me but I think its a question that will be answered — since users are asking it.    Where we are starting at betaworks is making sure the tools are in place to at least find out if a swarm has shown up on your site.    The example above was tracked using Chartbeat — a service we developed.    We dont know what to do yet — but we do know that the first step is making sure you actually know that the tree fell — real time.

Where is Clementis’s hat? Where is the history?

I love that quote from Kundera.    The activity streams that are emerging online are all these shards — these ambient shards of people’s lives.    How do we map these shards to form and retain a sense of history?     Like the hat objects exist and ebb and flow with or without context.    The burden to construct and make sense of all of this information flow is placed, today, mostly on people.    In contrast to an authoritarian state eliminating history — today history is disappearing given a deluge of flow, a lack of tools to navigate and provide context about the past.    The cacophony of the crowd erases the past and affirms the present.   It started with search and now its accelerated with the now web.    I dont know where it leads but I almost want a remember button — like the like or favorite.   Something that registers  something as a memory — as an salient fact that I for one can draw out of the stream at a later time.   Its strangely compforting to know everything is out there but with little sense of priority of ability to find it it becomes like a mythical library — its there but we cant access it.

Unfinished

This media is unfinished, it evolves, it doesnt get finished or completed.    Take the two quotes below — both from Brian Eno, but fifteen years apart — they outline some of the boundaries of this aspect of the stream.

In a blinding flash of inspiration, the other day I realized that “interactive” anything is the wrong word. Interactive makes you imagine people sitting with their hands on controls, some kind of gamelike thing. The right word is “unfinished.” Think of cultural products, or art works, or the people who use them even, as being unfinished. Permanently unfinished. We come from a cultural heritage that says things have a “nature,” and that this nature is fixed and describable. We find more and more that this idea is insupportable – the “nature” of something is not by any means singular, and depends on where and when you find it, and what you want it for. The functional identity of things is a product of our interaction with them. And our own identities are products of our interaction with everything else. Now a lot of cultures far more “primitive” than ours take this entirely for granted – surely it is the whole basis of animism that the universe is a living, changing, changeable place. Does this make clearer why I welcome that African thing? It’s not nostalgia or admiration of the exotic – it’s saying, Here is a bundle of ideas that we would do well to learn from.  (Eno, Wired interview, 1995)

In an age of digital perfectability, it takes quite a lot of courage to say, “Leave it alone” and, if you do decide to make changes, [it takes] quite a lot of judgment to know at which point you stop. A lot of technology offers you the chance to make everything completely, wonderfully perfect, and thus to take out whatever residue of human life there was in the work to start with. It would be as though someone approached Cezanne and said, “You know, if you used Photoshop you could get rid of all those annoying brush marks and just have really nice, flat color surfaces.” It’s a misunderstanding to think that the traces of human activity — brushstrokes, tuning drift, arrhythmia — are not part of the work. They are the fundamental texture of the work, the fine grain of it. (Eno, Wired interview, 2008)

The media, these messages, stream — is clearly unfinished and constantly evolving as this post will likely also evolve as we learn more about the now web and the emerging social distribution networks.

Gottwald minus Clementis

Addendum, some new links

First — thank you to Alley Insider for re-posting the essay, and to TechCrunch and GigaOm for extending the discussion.    This piece at its heart is all about re-syndication and appropriation – as Om said “its all very meta to see this happen to the essay itself”.     There is also an article that I read after posting from Nova Spivack that I should have read in advance — he digs deep into the metaphor of the web as a stream.    And Fred Wilson and I did a session at the social media bootcamp last week where he talked about shifts in distribution dynamics — he outlines his thoughts about the emerging social stack here.   I do wish there was an easy way to thread all the comments from these different sites into the discussion here — the fragmentation is frustrating, the tools need to get smarter and make it easier to collate comments.

bit.ly now

We have had a lot going on at bit.ly over the past few weeks — some highlights — starting with some data.

• bit.ly is now encoding (creating) over 10m URL’s or links a week now — not too shabby for a company that was started last July.

• We picked the winners of the API contest last week after some excellent submissions

• Also last week the bit.ly team started to push out the new real time metrics system. This system offers the ability to watch in real time clicks to a particular bit.ly URL or link  The team are still tuning and adjusting the user experience but let me outline how it works.

If you take any bit.ly link and add a “+” to the end of the URL you get the Info Page for that link.  Once you are on the info page you can see the clicks to that particular link updated by week, by day or live — a real time stream of the data flow.

An example:

On the 15th of February a bit.ly user shortened a link to an article on The Consumerist about Facebook changing their terms of service.  The article was sent around a set of social networks and via email with the following link http://bit.ly/mDwWb.   It picked up velocity and two days later the bit.ly info page indicates that the link has been clicked on over 40,000 times — you can see the info page for this link below (or at http://bit.ly/mDwWb+ ).

In the screenshot below

1.) you see a thumbnail image of the page, its title, the source URL and the bit.ly URL.    You also see the total number of clicks to that page via bit.ly, the geographical distribution of those clicks, conversations about this link on Twitter, FriendFeed etc and the names of other bit.ly users who shortened the same link.

2.) you see the click data arrayed over time.:

bit.ly live

The view selected in the screenshot above is for the past day — in the video below you can see the live data coming in while the social distribution of this page was peaking yesterday.

This exposes intentionality of sharing in its rawest form.   People are taking this page and re-distributing it to their friends.     The article from the Consumerist is also on Digg — 5800 people found this story interesting enough to Digg it.   Yet more than 40,000 people actually shared this story and drove a click through to the item they shared.     bit.ly is proving to be an interesting complement to the thumbs up.   We also pushed out a Twitter bot last week that publishes the most popular link on bit.ly each hour.    The content is pretty interesting.   Take a look and tell me what you think — twitter user name: bitlynow.

————–

A brief note re: Dave Winer’s post today on on bit.ly.

Dave is moving on from his day to day involvement with bit.ly — I want to thank him for his ideas, help and participation.     It was an amazing experience working with Dave.    Dave doesnt pull any punches — he requires you to think — his perspective is grounded in a deep appreciation for practice — the act of using products — understanding workflow and intuiting needs from that understanding.   I learnt a lot.     From bit.ly and from from me — thank you.

A pleasure and a privildege.

Creative destruction … Google slayed by the Notificator?

The web has repeatedly demonstrated its ability to evolve and leave embedded franchises struggling or in the dirt.    Prodigy, AOL were early candidates.   Today Yahoo and Ebay are struggling, and I think Google is tipping down the same path.    This cycle of creative destruction — more recently framed as the innovators dilemma — is both fascinating and hugely dislocating for businesses.    To see this immense franchises melt before your very eyes — is hard to say the least.   I saw it up close at AOL.    I remember back in 2000, just after the new organizational structure for AOL / Time Warner was announced there was a three day HBS training program for 80 or so of us at AOL.   I loath these HR programs — but this one was amazing.   I remember Kotter as great (fascinating set of videos on leadership, wish I had them recorded), Colin Powell was amazing and then on the second morning Clay Christensen spoke to the group.    He is an imposing figure, tall as heck, and a great speaker — he walked through his theory of the innovators dilemma, illustrated it with supporting case studies and then asked us where disruption was going to come from for AOL?    Barry Schuler — who was taking over from Pittman as CEO of AOL jumped to answer.   He explained that AOL was a disruptive company by its nature.    That AOL had disruption in its DNA and so AOL would continue to disrupt other businesses and as the disruptor its fate would be different.     It was an interesting argument — heart felt and in the early days of the Internet cycle it seemed credible.   The Internet leaders would have the creative DNA and organizational fortitude to withstand further cycles of disruption.    Christensen didn’t buy it.     He said time and time again disruptive business confuse adjacent innovation for disruptive innovation.   They think they are still disrupting when they are just innovating on the same theme that they began with.   As a consequence they miss the grass roots challenger — the real disruptor to their business.   The company who is disrupting their business doesn’t look relevant to the billion dollar franchise, its often scrappy and unpolished, it looks like a sideline business, and often its business model is TBD.    With the AOL story now unraveled — I now see search as fragmenting and Twitter search doing to Google what broadband did to AOL.

a5e3161c892c7aa3e54bd1d53a03a803

Video First

Search is fragmenting into verticals.     In the past year two meaningful verticals have emerged — one is video — the other is real time search.   Let me play out what happened in video since its indicative of what is happening in the now web.     YouTube.com is now the second largest search site online — YouTube generates domestically close to 3BN searches per month — it’s a bigger search destination than Yahoo.     The Google team nailed this one.    Lucky or smart — they got it dead right.    When they bought YouTube the conventional thinking was they are moving into media —  in hindsight — its media but more importantly to Google — YouTube is search.     They figured out that video search was both hard and different and that owning the asset would give them both a media destination (browse, watch, share) and a search destination (find, watch, share).  Video search is different because it alters the line or distinction between search, browse and navigation.       I remember when Jon Miller and I were in the meetings with Brin and Page back in November of 2006 — I tried to convince them that video was primarily a browse experience and that a partnership with AOL should include a video JV around YouTube.     Today this blurring of the line between searching, browsing and navigation is becoming more complex as distribution and access of YouTube grows outside of YouTube.com.    44% of YouTube views happen in the embedded YouTube player (ie off YouTube.com) and late last year they added search into the embedded experience.    YouTube is clearly a very different search experience to Google.com.       A last point here before I move to real time search.    Look at the speed at which YouTube picked up market share.  YouTube searches grew 114% year over year from Nov 2007 to Nov 2008!?!     This is amazing — for years the web search shares numbers have inched up in Google favor — as AOL, Yahoo and others inch down, one percentage point here or there.    But this YouTube share shift blows away the more gradual shifts taking place in the established search market.     Video search now represents 26% of Google’s total search volume.

summize_fallschurch

The rise of the Notificator

I started thinking about search on the now web in earnest last spring.    betaworks had invested in Summize and the first version of the product (a blog sentiment engine) was not taking off with users.   The team had created a tool to mine sentiments in real-time from the Twitter stream of data.    It was very interesting — a little grid that populated real time sentiments.   We worked with Jay, Abdur, Greg and Gerry Campbell to make the decision to shift the product focus to Twitter search.   The Summize Twitter search product was launched in mid April.   I remember the evening of the launch — the trending topic was IMAP — I thought “that cant be right, why would IMAP be trending”, I dug into the Tweets and saw that Gmail IMAP was having issues.    I sat there looking at the screen — thinking here was an issue (Gmail IMAP is broken) that had emerged out of the collective Twitter stream — Something that an algorithmically based search engine, based on the relationships between links, where the provider is applying math to context less pages could never identify in real time.

A few weeks later I was on a call with Dave Winer and the Switchabit team — one member of the team (Jay) all of a sudden said there was an explosion outside.   He jumped off the conference call to figure out what had happened.    Dave asked the rest of us where Jay lived — within seconds he had Tweeted out “Explosion in Falls Church, VA?”  Over the nxt hour and a half the Tweets flowed in and around the issue (for details see & click on the picture above).    What emerged was a minor earthquake had taken place in Falls Church, Virginia.    All of this came out of a blend of Dave’s tweet and a real time search platform.  The conversations took a while to zero in on the facts — it was messy and rough on the edges but it all happened hours before main stream news, the USGS or any “official” body picked it up the story.  Something new was emerging — was it search, news — or a blend of the two.   By the time Twitter acquired Summize in July of ’08 it was clear that Now Web Search was an important new development.

Fast forward to today and take a simple example of how Twitter Search changes everything.    Imagine you are in line waiting for coffee and you hear people chattering about a plane landing on the Hudson.   You go back to your desk and search Google for plane on the Hudson — today — weeks after the event, Google is replete with results — but the DAY of the incident there was nothing on the topic to be found on Google.  Yet at http://search.twitter.com the conversations are right there in front of you.    The same holds for any topical issues — lipstick on pig? — for real time questions, real time branding analysis, tracking a new product launch — on pretty much any subject if you want to know whats happening now, search.twitter.com will come up with a superior result set.

How is real time search different?     History isnt that relevant — relevancy is driven mostly by time.    One of the Twitter search engineers said to me a few months ago that his CS professor wouldn’t technically regard Twitter Search as search.   The primary axis for relevancy is time — this is very different to traditional search.   Next, similar to video search — real time search melds search, navigation and browsing.       Way back in early Twitter land there was a feature called Track.  It let you monitor or track — the use of a word on Twitter.    As Twitter scaled up Track didn’t and the feature was shut off.   Then came Summize with the capability to refresh results — to essentially watch the evolution of a search query.      Today I use a product called Tweetdeck (note disclosure below) — it offers a simple UX where you can monitor multiple searches — real time — in unison.    This reformulation of search as navigation is, I think, a step into a very new and different future.   Google.com has suddenly become the source for pages — not conversations, not the real time web.   What comes next?   I think context is the next hurdle.    Social context and page based context.    Gerry Campbell talks about the importance of what happens before the query in a far more articulate way than I can and in general Abdur, Greg, EJ, Gerry, Jeff Jonas and others have thought a lot more about this than I have.    But the question of how much you can squeeze out of a context less pixel and how context can to be wrapped around data seems to be the beginning of the next chapter.    People have been talking about this for years– its not that this is new — its just that the implementation of Twitter and the timing seems to be right — context in Twitter search is social.   74 years later the Notificator is finally reaching scale.

A side bar thought: I do wonder whether Twitter’s success is partially base on Google teaching us how to compose search strings?    Google has trained us how to search against its index by composing  concise, intent driven statements.   Twitter with its 140 character limit picked right up from the Google search string.    The question is different (what are you doing? vs. what are you looking for?)  but  the compression of meaning required by Twitter is I think a behavior that Google helped engender.     Maybe, Google taught us how to Twitter.

On the subject of inheritance.  I also believe Facebook had to come before Twitter.    Facebook is the first US based social network — to achieve scale, that is based on real identity.  Geocities, Tripod, Myspace — you have to dig back into history to bbs’s to find social platforms where people used their real names, but none of these got to scale.    The Twitter experience is grounded in identity – you knowing who it was who posted what.    Facebook laid the ground work for that.

What would Google do?

I love the fact that Twitter is letting its business plan emerge in a crowd sourced manner.   Search is clearly a very big piece of the puzzle — but what about the incumbents?   What would Google do, to quote Jarvis?   Let me play out some possible moves on the chess board.   As I see it Google faces a handful of challenges to launching a now web search offering.    First up — where do they launch it,  Google.com or now.Google.com?    Given that now web navigational experience is different to Google.com the answer would seem to be now.google.com.   Ok — so move number one — they need to launch a new search offering lets call it now.google.com.    Where does the data come from for now.google.com?    The majority of the public real time data stream exists within Twitter so any http://now.google.com/ like product will affirm Twitter’s dominance in this category and the importance of the Twitter data stream.    Back when this started Summize was branded “Conversational Search” not Twitter Search.     Yet we did some analysis early on and concluded that the key stream of real time data was within Twitter.    Ten months later Twitter is still the dominant, open, now web data stream.   See the Google trend data below – Twitter is lapping its competition, even the sub category “Twitter Search” is trending way beyond the other services.   (Note: I am using Google trends here because I think they provide the best proxy for inbound attention to the real time microbloggging networks.   Its a measure of who is looking for these services.    It would be preferable to measure actual traffic measured but Comscore, Hitwise, Compete, Alexa etc. all fail to account for API traffic — let alone the cross posting of data (a significant portion of traffic to one service is actually cross postings from Twitter).   The data is messy here, and prone to misinterpretation, so much so that the images may seem blurry).   Also note the caveat re; open.   Since most of the other scaled now web streams of data are closed / and or not searchable (Facebook, email etc.).

screenshot
gTrends data on twitter

Google is left with a set of conflicting choices.     And there is a huge business model question.     Does Ad Sense work well in the conversational sphere?   My experience turning Fotolog into a business suggests that it would work but not as well as it does on Google.com.    The intent is different when someone posts on Twitter vs. searching on Google.   Yet, Twitter as a venture backed company has the resources to figure out exactly how to tune AdSense or any other advertising or payments platform to its stream of data.    Lastly, I would say that there is a human obstacle here.     As always the creative destruction is coming from the bottom up — its scrappy and and prone to been written off as NIH.     Twitter search today is crude — but so was Google.com once upon a not so long time ago.     Its hard to keep this perspective, especially given the pace that these platforms reach scale.     It would be fun to play out the chess moves in detail but I will leave that to another post.   I’m running out of steam here.

AOL has taken a long time to die.    I thought the membership (paid subscribers) and audience would fall off faster than it has.    These shifts happen really fast but business models and organizations are slow to adapt.  Maybe its time for the Notificator to go public and let people vote with their dollars.   Google has built an incredible franchise — and a business model with phenomenal scale and operating leverage.   Yet once again the internet is proving that cycles turn — the platform is ripe for innovation and just when you think you know what is going on you get blindsided by the Notificator.

Note:    Gerry Campbell wrote a piece yesterday about the evolution of search and ways to thread social inference into  search.    Very much worth a read — the chart below, from Gerry’s piece, is useful as a construct to outline the opportunity.

gerry-campbell-emerging-search-landscape1

Disclosure.   I am CEO of betaworks.    betaworks is a Twitter shareholder.  We are also a Tweetdeck shareholder.  betaworks companies are listed on our web site.

Micro-giving on the Huff Po

Ran the following essay on the Huff Po over xmas. Piece by Ken Lerer and I on what we are learning from the charity water drive and the possibilities of micro-giving.

Picture 19.png

Here is the article from the Huff Post:

Micro-Giving: A New Era in Fundraising

Thirty years ago, a young economics professor named Muhammad Yunus started a new kind of banking in Bangladesh — tiny loans to small entrepreneurs. Few thought these dreamers in a dirt-poor country would ever repay. But most did — and in 2006, Yunus won the Nobel Peace Prize.

Micro-lending has changed lives, built communities and created unlikely leaders.

Now a wave of friends and “loose ties” within the social media community are bringing the micro-lending concept and applying it to charitable giving.

Call it “Micro-giving”.

Late last week Laura Fitton of Pistachio Consulting launched a new kind of fundraising drive: an effort to raise $25,000 for a nonprofit called charity: water, a cause that works to bring clean, safe water to developing countries. She chose Twitter as her platform for financial pledges. And because she was aware of the bleak economy bearing down on her friends, she didn’t want to lean on them for significant contributions. “I asked for $25,000,” she says, “which would be just $2 for each reader I have on Twitter.”

In four days, @wellwishes had raised over $5,000. Average pledge size has been $8.50, the median is $2. And the beneficiary has taken notice. “I see micro-giving as the next stage of online fund raising,” says Scott Harrison, founder and president of charity: water. “The idea of thousands of $2 gifts adding up to wells in Africa that impact thousands of lives is something everybody can get behind.”

Though reminiscent of the Obama campaign’s decentralized funding, @wellwishes is a whole new model because it incorporates convenient, tiny donations made right on Twitter — the word-of-mouth powered social network and microblogging platform. Using payment service from a company called Tipjoy, it’s both simple and social to give. Your pledge shows up on Twitter as “p $2 @wellwishes for charity: water to save lives” (This is shorthand for “pay $2 to the Charity organization whose user name on Twitter is wellwishes.”) And that message goes — instantly — to all of the people who follow you on Twitter.

Laura Fitton (her Twitter user name is Pistachio) kicked off the campaign with an announcement of the experiment:

p $2 @wellwishes just to practice my hand at using micropayments on @tipjoy

In a later Tweet, she made her appeal:

I want something TOTALLY insane for Christmas: 12,500 people each to donate $2 for clean water @wellwishes.

And many did. Okay, these are pledges, not donations. But just as poor people pay their micro-loans, so micro-donors make good on their pledges — so far, an astonishing 86% have come through.

And then there’s the fact that the request gets personalized as people pass it on. Some add just a phrase: “very cool”. Others say the same thing, but with more characters: “small bits via Twitter + big audience = good xmas”.

The message is as important as the medium — using Twitter/Tipjoy, everyone who participates is both a donor and a broadcaster.

That suggests we’re entering a new era in fundraising and perhaps other social/political causes. What’s new? Virtual tribes — networks of caring people with more commitment than cash.

And that’s what excites us about micro-giving: It takes so little. You might not have much to spare, but you’ve got a penny jar — and we all know that if you reach in and remove a handful of change, you’ll feel no pain. What’s great about the new, frictionless online giving we’re testing here is that, if you’ve got a good cause, you no longer need to spend a fortune on real-world marketing. Online, with word of mouth and simple technology, pennies can become serious money.

Muhammad Yunus says that we can create a poverty-free world “if we collectively believe in it.” That’s a lot of belief. It will be easier to create that world if good causes have adequate funding — and if they can get that funding a few pennies at a time.

That, it seems to us, is a “very cool” idea. So give it a whirl. Give here and support charity: water, and be among the first to try what we hope is a new way to give online — micro-giving. For which you get large thanks.

disclosure note: betaworks is an investor in Twitter and Tipjoy. Tipjoy waived all fees for this effort, and, with betaworks, is making a matching gift.

We are making solid progress towards the goal. You can see a running total here.

Keep it Chunky, Sticky in 1996

Fred Wilson’s keynote this week at the Web 2.0 conference will be interesting. He is doing a review of the history of the internet business in New York, the slides are posted here. History is something we don’t do a lot of in our business we tend to run forward so fast that we barely look back. I shared some pictures with Fred and I am posting a few more things here.   I also found a random missive I scribed I think in 1996, its pasted below. I was running what we called a web studio back then — we produced a group of web sites, including äda ’web , Total New York and Spanker.


truism1.gif

äda ’web’s first project created in the fall of 1994 — Jenny Holzer’s, Please Change Beliefs. This project is still up and available at adaweb. The project was a collaboration between Jenny, ada and John F. Simon, Jnr. I learnt so much from that one piece of work. I am not putting up more ada pieces since unlike the other sites it is still up and running thanks to the Walker Arts Center.

Total NY sends Greg Elin across country for the Silicon Alley to Silicon Valley tour. Greg and this project taught me the fundamentals of what would become blogging

Greg_Elin_SA2SV.gif

Man meets bike meets cam … Greg Elin prepares for Silicon Alley to Silicon Valley. Don’t miss the connextix “eye” camera on the handle bar!?!

1995, Total NY’s Cosmic Cavern, my first forway into 2d+ virtual worlds, a collaboration with Kenny Scharf. This was a weird and interesting project. We created a virtual world with Scharf based on the cosmic cavern the artist had created at the tunnel night club. Then within the actual Cosmic Cavern we placed PC’s for people to interact with the virtual cavern. Trying to explain it was like a Borges novel. He is a picture of Scharf in the “real” cavern, feels like the 90’s were a long time ago.

kenny_scharf.jpg

Some other random pictures i found from that era:

Pics_from_mexico.jpg

borthwick_stallman.jpg

yahoo_1995-tm.jpg

Keep it Chunky, Sticky and Open:

As the director of a studio dedicated to creating online content, a question I spend a lot of time thinking about is: what are the salient properties of this medium? Online isn’t print, it isn’t television, isn’t radio, nor telephony–and yet we consistently apply properties of all these mediums to online with varied result. But digging deeper, what are the unique properties of online that make the experience interesting and distinct? Well, there are three that we have worked with here the Studio, and we like to call them: chunky, sticky and open.

Chunky
What is chunky content? It is bite sized, it is discrete and modular, it is quick to understand because it has borders. Suck is chunky, CNET and Spanker (one of our productions) are chunky. Arrive at these sites and within seconds you understand what is going on–the content is simple, its bite sized. Chunkiness is especially relevant in large database-driven sites. Yesterday, my girlfriend and I were looking for hardware on the ZD Net sites (PC Magazine, Net Buyer etc.). She had found a hardware review a day earlier and wanted to show them to me. She typed in the URL for PC Magazine but the whole site had changed. When she looked at the page she had no anchors, she had no bearings to find the review that was featured a day earlier. The experience would have been far less frustrating if the site had been designed with persistent, recursive, chunks. Chunky media offers you a defined pool of content, not a boundless sea. It has clear borders and the parameters are persistent. Bounded content is important; I want to know the borders of the media experience, where it begins and where it ends. What is more, given the distributed, packet-based nature of this medium, both its form and function evokes modularity. Discreet servings of data. Chunks.

Sticky
Some, but not all, content should stick. Stickiness is about creating an immersive experience. It’s content that dives deep into associations and relationships. The opposite of sticky is slippery, take basic online chat rooms: most of them aren’t sticky. You move from one room to another, chatting about this and that, switching costs are low, they are slippery. Contrast this to MUDS and MOO’s which are very sticky: in MUDS the learning curve is steep (view this as a rite of entry into the community), and context is high (they give a very real sense of place). What you get out of these environments is proportional to your participation and involvement, relationship between characters is deep and associative. When content sticks time slows down and the experience becomes immersive– you look up and what you thought was ten minutes was actually half an hour. Stickiness is evoked through association, participation, and involvement. Personalized information gets sticky as does most content that demands participation. Peer to peer communication is sticky. Community and games are sticky. People (especially when they are not filtered) are sticky. My home page is both chunky and sticky.

Open
I want to find space for me in this medium. Content that is open, or unfinished permits association and participation (see Eno’s article in Wired 3.05, where he talks about unfinished media). There is space for me. I often describe building content in this medium as drawing a 260 degrees circle. The arc is sufficient to describe the circle (e.g.: provide the context) but is open to let the member fill in the remainder. We laugh and cry at movies, we associate with characters in books, they move us. We develop and frame our identity with them and through them–to varying degrees they are all open. Cartoons, comedy, and most forms of humor, theatre, especially improvisational theater, are all open. A joke isn’t really finished till someone laughs, this is the closing of the circle, they got it. Abstraction, generalities and stereotypes, all these forms are open, they leave room for association, room for me and for you.

So, chunky, sticky and open. Try them out and tell me what you think (john@dci-studio.com). Lets keep this open, in the first paragraph I said I wanted to discuss the characteristics that make a piece of online content interesting, I did not use the words great or compelling. I don’t think that anything online that has been created to date is great. These are still early days and we still have a lot to learn and a lot to unlearn. No one has produced the Great Train Robbery of online–yet. But when they do, I would bet that pieces of it will be chunky, sticky and open.

Ok enough reminiscing, closing with Jenny Holzer.

web 2.0 & making money

Article in today's financial times about Web 2.0 companies making, and not, making money.   I think the article is right and we are likely heading for some consolidation — but the article misses the most interesting points about why and how that consolidation will take place.  Its a fairly typical turn of the tide article — replete with a bonus quotation from someone who just raised a lot of money.     Moving on from the drama of MSM — start with why there will be consolidation of some form.  

The web 1.0 companies who survived and prospered did so mostly on the back of Google —  its distribution and its monetization platform.    The fact that many web 2.0 companies have yet to turn a profit is an indication that (a) Google's  platform is still not optimized for this generation of web services and that (b) Facebook, the company everyone expected to provide an alternative, has thus far failed to  provide a platform to build a business.    A year ago this week I drafted an essay on why I believed the Facebook platform needed to offer Web 2.0 applications more than just distribution — its a year later and the data is starting to be tabulated.    Facebook has left a wide gaping opportunity for others to drive into –and companies driving in to fill this gap need to scale social graphs and in order to do that they are opening up — Facebook's misstep, accomplished two moves on the chess board!    They had a chance to build another walled garden but now they are in a struggle to the bottom (or top) of who can become more open — very good for the web as a whole and, specifically, very good for web 2.0 companies.      

Moving to the how.    This shift will pry open opportunity and monetization platforms across the web – and its likely we will have diversity in this system, it will likely be much more sustainable than web 1.0.    While this change is taking place its important to grow audience, manage costs and experiment with monetization approaches that follow the grain of your service.   And lastly, the consolidation the FT talks about — may not be the typical consoldation we see as busssiness go through changes — many of the web 2.0 companies have managed overhead/costs very aggresively, there might be opportunities to loosely couple parts instead of the organizational pain that mergers spawn.    More to come on this later when I have some time to write.    

Compacting connections

Interesting article by the founder of Meetro about what he learned from his startup experience.   Intrigued by the discussion about launch and member growth — he talks about how it first took off in Chicago and then it started spreading into small communities around Chicago.   A lesson I leant at Fotolog was the value of compacting social networks — its counter intuitive but it makes sense when you think about it.     Communities need to be compact or tightly connected at the outset in order to reach critical mass.    Duncan Watts has done a lot of great research on this — Adam Seifer taught me about it in practice.    Raw growth is not the right metric to focus on when you start a social network — you need to measure and track the density of those connections — tight, compacted social networks grow faster than thin broadly distributed one's.

Future of news

I saw the future of news unfold today.   We were on a conference call with Jay who was in Falls Church VA – he heard an explosion – Dave posted the question on twitter and in the space of two hours the tweet-o-sphere figured out it was a small earthquake.      There is still nothing on the subject on Google or Google news, let alone MSM.

You can see the tweet stream below via a search on Summize.  We  talk about this stuff ad-infinitum but its amazing to see it unfold before one’s eyes.   The first tweet is from 1.35pm right after the quake.   The last one on the screen shot was approx. 3.10pm — it links to the confirmation from the USG:

(USGS has confirmed a magnitude 1.8 “micro” earthquake occurred near Annandale, VA at 1:30pm.  There have been no reports of damage or injuries.)

note the screen shot below is a compilation of tweets, re-run the search on falls church at Summize.com

summize / earthquake

Dimensionalizing the web

What is a web page today? If you look at the average web page, it’s a compilation of a diverse set of data sources drawn into a construct that we think of as a concrete whole. It probably started with CGI — and the first commercial application was likely the ad banner — but today that simple web page is made up of a whole mix of things ranging from dynamic content, ad’s,  widgets, sidebar tools, gadgets — the frame that we think of as a web page is now constructed from data streams in from all these sources and more.   This componentization of the page was the first step in what is becoming a different architecture for information delivery. What we have today are the equivalent of early life forms – necessary building blocks that evolution will use as more sophisticated lateral services develop. The organization of data streams and how they are constructed relates to our understanding of the dimensions of the web.

Question?   What would the web look like if you picked it up and looked at the bottom? I imagine, what you would see would be a set of databases – with streams of data flowing between them, into these things we call web pages and between these things we call web sites. These metaphors we have applied to the web — pages and sites — are analog’s that helped us grasp and structure the web, yet like any proxy they also impose limits on our perspective. RDF/RSS started me thinking about a lot of these ideas but in the eight or so years since those standards were developed our understanding and approach to web sites as vertical businesses has barely evolved. The spacial assumption we imposed on the web — that a site is a discrete experience that a publisher can control — maps with both a human need to impose hard edges on a dynamic, complex system but also with how we have understood media for the past 100 years or so. I think those edges are been broken down and are offering a different view of the web, and therefore of media companies, one that is less structured around the hard edges of a web page or site, less vertical, less about data silos and more about dynamic, fluid use of data and connections between data points. Some examples.

Take a look at this picture of this post I found on tumblr last week. This person — Erin — is using tumblr to announce a meetup. In this case email and reblogging are the tools she is using to confirm attendants. Shouldn’t this person use meetup for this — clearly its their preference not to, but why?

tumb log

I would propose two theories: context and easy of use. First context — context is important, Erin has followers (an audience) on tumblr, she has an environment that is customized with a user experience she could control (nice background) — and so she wants her meetup to appear in that context. Ease of use — for a myriad of reasons it seems it was easier for her to roll her own meetup than use meetup.com or to quote Pip Coburn the perceived benefits outweigh the perceived pain of trying to learn something new. So here is an example of someone molding a use case (creating a meetup) into another web experience to fulfill a need.

Example #2. What about Twitter. What is the web site Twitter.com?   The first answer — the one I would tell a stranger in conversation — is that its a destination to access and use the microblogging service provided by Twitter, “want to try one to many micropublishing? go to twitter.com”.   Sounds simple enough. Yet that conclusion isn’t supported by the data. I don’t have the exact number but I think its safe to say that more than half of the interactions with Twitter occur off Twitter.com — and the number is in all likelihood a lot higher than that. So is Twitter a protocol?, maybe.   Maybe Ted Stevens actually understood the web better than we thought — thinking about Twitter as a pipe makes more sense than as a  destination.   But its not a pipe in way that old media understood pipes — its different, im not sure i understand exactly what that difference is going to yeild but what is clear today is that each interaction that takes place on the network add’s value or context to further interactions.    As data chunks move around Twitter the get organized and collated into conversations and meme’s.  Similar to the Meetup example — each node on the twitter network is contextualized in form that makes sense for that particular interaction. But unlike Meetup, Twitter is powering all these interactions. The data becomes more valuable as it moves from interface to interface — not less.     There is something very powerful that is happening with the simplicity and openess of this network.   A network is the best metaphor I can think of for Twitter.

Another example.  Iminlikewithyou — the flash casual gaming site, started off as a destination (disclosure note, a betaworks company).    All of a sudden users started grabbing the code and syndicating their game on to their web sites.    But this isnt just the game — its not a widget model — its the entire underlying game net that is getting syndicated.     IILWY is closer to our understanding of old media but its contains some of the bizarre distributed breadth and possibilities that Twitter holds.

So where does all of this lead us?  I believe we need new metaphors to understand and place dimensions around what a web experience is. I don’t have an answer but I do have a few thoughts on how we can begin to frame and understand the shape of what is to come.

i) Think Centers vs wholes, think about networks vs. destinations

Pic by CALast week I was re-reading Christopher Alexander the Nature of Order . In the first book he has a section about wholes vs. centers. He makes the argument that composing visual structures as whole’s — thinking of buildings, things, windows — anything as a whole — fails to recognize the context in which the object lives. He builds the argument up starting with a dot on a piece of paper — he then analyzes how the dot divides and structures our spacial understanding of the piece of paper.  From this point he starts to frame up a way of looking at the world that is based on thinking about centers, zones of spatial activity vs. wholes.   An example he cites:

“On one occasion, I was discussing the concept of centers, as it applied to some bedroom curtains, with my wife Pamela.     She made the comment that the use of the word “centers” as I had explained it to her, was already changing her view of everything around her, even as we were talking: “When I look at the curtain in the room, and think of the curtain, the curtain rod, the window, the sky, the light on the ceiling, as centers, then I become so much more cognizant of the relatedness of all things — it is as though my awareness increases”

I think Alexander’s point and work here is profoundly applicable to the web. If you start thinking about centers — clusters of information — vs. destinations and vertical sites, for me at least, it gives me a frame of reference a metaphor that is far more expansive and networked than the one in which we operate today.   At Fotolog I learned that centers can form and cluster with remarkable speed within a community — now this is starting to happen with information moving laterally between domains.

ii) Think what can move laterally and encourage it to move

People, those things we often call users, want to take data and move it laterally across the web.   They want it to exist in context’s that make sense for a particular interaction. Whether its data portability standards, micro-content standards, people want to cross post and move data from one service to another. There is much that needs to be done here.   A year ago when F8 was launched it seemed that Facebook was driving headlong into this domain.   Yet a year later it now seems like Facebook might become known as the last portal, the last walled garden experience — data comes in but not out.   Openness of interface, api’s — letting data come in an go out of a domain is central to this thesis.    The Facebook newsfeed could be a web wide service — instead the way its articulated today is about retaining eye balls and attention — a movie we have seen before.  Last week we started talking publicly about SwitchAbit — SwitchAbit is a service that is designed to help drive this lateral movement of data across the web, while retaining context, its a small contribution we are hoping to make to this larger puzzle.

iii) Think about how to atomize context so that it can travel with the data

Dirty DataAtomizing content is one piece of the puzzle, the other is doing the same for context so it can travel with the data as it moves around the web from center to center.    Outside.in — Steven Johnson’s creation — trawls through blog posts and attaches geo context to individual posts. I sometimes refer to Outside.in as a washing machine — dirty data comes in one end — Outside.in scrubs the data set and ships out geo-pressed results the other end.   The geo scrubbed post is now more useful for end users, publishers and advertisers.   A bit of structure goes a long way when the data can then move into other structures.   The breadth of what geo scrubbing can do is staggering — think about pivoting or organizing any piece of information around a map — the spatial dimension that is most familiar to our species.  A bit of context goes a long way.   (disclosure note, Outside.in / an investment of betaworks)

iv) Think Layers

There is a layering dimension that is worth consideration — there are services starting to emerge that offer functionality that is framed around exposing some separation between different layers of the web.   Photoshop is the software that first introduced me to the layer metaphor,  i still cant use photoshop, but I think I get the layer idea.   Google earth has applied a layering concept to mapping.   Similarly services like PMOG are experimenting with layers.   Back at betaworks Billy Chasen started working with layers about eight months ago.   He developed a simple navigational tool called Fichey that lets you navigate web pages independent of their domain – using a common navigational tool.    Want to flip thru the top digg stories? — fichey makes it fairly easy and fast.   This was just a beginning.    Billy has developed a service called firefly — it’s in testing now and over the coming weeks we will begin to preview it — but its all about creating a layer of interactivity that is contextualized with the web site you are on but its exists independent of that web site.

v) Accept uncertainty, keep it rough on the edges

What did Rummy say about the known unknown’s?    As we experiment and design these new forms of interactions its vital that we remain open to roughness and incompleteness on the edges of the web.   The more we try to place these services into the convenient, existing models, that we have used to structure our thinking thus far the more we will limit our ability to look ahead and think about these things differently.

This is just a beginning.   I hope these five areas have helped define and frame how to think about alternative data dimensions on the web.  Time to wrap this post up — enough for now.

Fotolog + Hi Media

With mixed emotions – a combination of great excitement and a slight tug at the heartstrings – we announced today the sale of Fotolog to Hi-Media, one of Europe's largest advertising and micro-payment networks. This transaction forms one of Europe’s best positioned Internet companies, with huge audience reach and great monetization tools. Our release lays out key elements of the rationale for this transaction, but here are the high points:

· The opportunity to bring together Fotolog’s rapidly growing audience of more than 10 million members, 15 million visitors – and its top 20 ranking among the world’s most trafficked websites – with Hi-Media’s huge ad-network and great optimization capabilities

· The tools for Fotolog to extend its platform and community services with one of Europe's largest micro-payment networks · The jump-start Fotolog brings to Hi-Media’s Publishing Group

· The strong geographic fit, combining Fotolog's growing strength in European markets like Spain and Italy with the reach Hi-Media will give Fotolog in rich and valuable Internet markets such as France,Germany and Sweden. · The outstanding opportunity the Fotolog team and investors will have to participate in the growth of the combined company.

· And equally important, the matching of two teams of people who know how to run Internet businesses. Cyril Zimmerman and the Hi-Media team have been building one of Europe's foremost online ad networks for more than a decade.

With Adam Seifer, Warren Habib and Scott Heiferman, we have a pedigree that goes back to the earliest days of social networking. The result will be one of the largest publicly traded Internet pure plays in Europe. Without the tangle of cable, DSL or old media properties that so often come with and encumber European online companies, our combined company will be able to focus on the hottest and fastest-growing media segment on the continent, and in some areas, around the world.

Seen from that perspective, it becomes clear why Hi-Media considered Fotolog so valuable and why we considered them the ideal partner, strategically, geographically and philosophically, to accelerate our growth and fully leverage our team and our audience. So those are the deal highlights. Now to some background on both companies, and why they are such a great strategic and geographic fit.

Hi-who?

Hi-Media, based in Paris, is a leading European advertising network and micro-payment aggregation platform listed under HIMD-PA . Hi-Media’s current management team is the same one that started the business ten years ago as an ad network. Over time they added micro-payments to the business and, more recently, a publishing group. The first two businesses are large and growing rapidly – the third is younger but with the acquisition of Fotolog now reaches scale.

We’re encouraged by Hi-Media’s demonstrated ability to grow through successful acquisitions and integration. The micro-payments business (today one of the largest in Europe), the local ad-sales business (today one of the largest in Scandinavia) and their current content business (a leading French gaming site) were all acquisitions. Hi-Media’s geographic center of gravity also gives reason for doing this deal. Hi-Media's roots are European, but they have a growing presence in South America, based out of Brazil.

This represents a great fit given Fotolog's recent growth in Europe, and with the acquisition of Fotolog, the Hi Media South American business should become an even more significant area of growth. Most importantly, Hi-Media is one of a small handful of companies positioned at the epicenter of European internet growth. I have blogged about this before, but broadband penetration today stands at approximately 60MM HH in Europe – and is poised to double in the next 3 years. Overall, Internet penetration in Europe in '07 will surpass 30% — an important number that has in other geographies represented a step function in growth, usage and monetization. Net based advertising, spending and direct micro-payment services are set to grow proportionally even faster, with analysts estimating CAGR's of over 20%.

Finally, macro trends aside – Hi- Media is well positioned to benefit from the growing needs of long-tail publishers to optimize and monetize their customers. The Ad- Network provides a CPM based platform for publishers to advertise through. The micro-payments platform is an aggregation service, one that offers customers the choice of more than 40 payment providers and access to more than 160,000 premium content sites.

Photo-blogging?

Fotolog was created five years ago by Scott Heiferman. Adam Seifer joined him shortly after and, working out of their apartments, the two of them birthed photoblogging … and created a global phenomenon. It’s strange, but here in the US, the rapid growth of the Internet often reduces business to a set of categories, at which point companies tend to retrofit services to fit those categories. Blogging in the US was initially defined as a text-based experience. Moreover, today daily people post photos to Facebook and Myspace – but those sites are defined as social networks – no one would seriously refer to them as a photoblogging platforms. But look at actual usage data.

The primary media types on Facebook are, first text (messages between members of the community) and second, photos. And that’s exactly what we see on Fotolog — where we host close to 300M photos and billions of conversations … all woven together in a complex social network. Myspace is substantially similar. Today, Fotolog is one of the 20 most-trafficked sites in the world, and the simple magic of Scott’s and Adam’s creation is still seducing our members. I first came to the company as an angel investor, and then Scott and Adam asked me to join as CEO late last year. In the space of seven months we have doubled the membership, inked partnerships with AOL, Google and Sun and brought the company close to breakeven. Our audience has grown in Europe such that today we almost 30% of our traffic is coming from Europe — 2.2 of our 15M unique visitors are coming from Spain. In terms of membership growth — last month — Italy, Germany, and France were right behind.

So why do a deal?

While Fotolog has grown at an incredible pace, it’s only now becoming a business. We have expanded our ad revenue base significantly in '07, yet we have done this with a tiny sales team, based in NY. There are limits to what you can do with 25 people based in NY, serving an audience mostly in South America and Europe. We have a worked with the Google team to use their AFC and AFS networks with significant successes – yet for media companies to build large, sustainable businesses, across both established and emerging markets, we have learnt you need to complement the ad networks with direct sales capabilities.

Fotolog needs room to grow … and with access to Hi-Media's ad-network, we will have an instant ad-sales capability in our largest and fastest growing markets. Longer term, I am big believer in the promise of peer-to-peer advertising among our members. Ads are often blunt instruments that fail to offer value to a membership engaged in a dynamic conversation – targeting and metadata only get you so far. Offering our membership the ability to buy and sell real and virtual items is something we are keen to offer at Fotolog, and a necessary capability to that end is access to micro-payment services across our footprint. Allopass, Hi-Media's micro-payment service, could fill that bill. Finally the agreement we struck with Hi-Media is a great return for our investors – many of whom (including me) are opting to hold stock in the combined company.

To close, a personal note …

As I said in the first paragraph, it was with mixed emotions that I recommended to our board that we do this deal. Fotolog is on a tear. Our international audience is coming of age, there is so much promise ahead, and it’s been a lot of fun running and building the company. The company has a group of very dedicated people. Adam's heart and soul is in the community. And since I came on board, we have weathered some fun operational challenges including user strikes, drowned servers, vendors trashing core databases … not to mention and some pretty hairy and exciting product launches.

Adam, Andrew, Warren, Olu, Frank, Elke, Yossi, Rodrigo, Andrew and many others have all pulled together through many a long night to make the company what it is today. I’m well aware that mergers and acquisitions don't always work out the way you hope. But Fotolog is truly poised to take off – and with the right mix from Hi-Media, there is a lot of potential in this merger that I hope we can make real for our membership, our team and our investors.