Frequent thinker, occasional writer, constant smart-arse

Tag: Sydney (Page 1 of 2)

Bye Sydney, Hi San Francisco

My life is about to get a big shakeup. I’ve accepted an offer at San Francisco based Vast.com, after spending nearly four valuable years at the Sydney office of PricewaterhouseCoopers.

New job, new industry, new city, new country.
In the last few years, I’ve come out of nowhere (meaning no idea how!) to become a person driving a global industry movement (the DataPortability Project) and a recognised champion for my nation’s Internet industry (Silicon Beach). Ironically, I don’t have a computer software background (I’m a chartered accountant), and I don’t work directly in tech (I’ve worked in financial services) So this transition is a realignment in my life, that I hope will bring me closer to doing what I’ve recognised is my true passion: building Internet companies that add value to our world.

What will I be doing?
Reporting to the CEO, I’ll be managing the overall finance and accounting functions of the company. However with time and as the company grows, I’ll be taking on additional responsibilities that can extend my current skill-base and experience. I’m thankful that the CEO Kevin Laws (one of the smartest guys in any room – seriously!), the chairman Naval Ravikant (one of the most successful Valley entrepreneurs around – 15 companies and counting!), and Director of Product Steve Greenberg (wisest guy I’ve ever met – both in insight and wit) believe in me and want to help me reach my potential…whatever that may be. Vast.com has an exciting business model with a veteran executive team – I don’t know where my future is headed but I know it’s in good hands.

So are you giving up on Australia?
No way! In fact, I think my presence in Silicon Valley is going to allow me to extend the Silicon Beach effort. I will have a permanent couch reserved for all of Australia’s tech entrepreneurs (well if I can – housing and room-mate pending!) and I’ll be developing my expertise from the world’s best to share back with my compatriots. I do hope one day to return to Australia and I have plenty of reason to do so – my family is in Sydney as are my half-dozen best friends who quite literally are the best mates a guy could have. I’ll still be doing the Silicon Beach podcast’s and whatever else I can to keep me connected to Australia – socially, professionally, spiritually – but having said that though, it may be a while before I do come back. I’ve got a hell of a lot to learn first!

This is a move that I hope will position me for bigger and better things. Its been a very hard decision to give up my near perfect life in Sydney, but I’m also very excited about the opportunities possible in my new position. Living overseas is something everyone needs to do in their lifetime for their own personal growth, and working in Silicon Valley is something I had to do (or as my new boss Kevin has said repeatedly now, “you belong here”), otherwise I’d forever regret not doing it.

I’ve still got a month to wind up things here in Sydney but I plan to be in San Francisco by 1 August 2009 at the latest. For those in Australia, I hope I get to catch you all before I go. For the American’s: be warned – trouble’s coming. 🙂

Wish me luck!

Don’t get the Semantic Web? You will after this

Prior to 2006, I had sort of heard of the Semantic Web. To be honest, I didn’t know much – it was just another buzzword. I’ve been hearing about Microformats for years, and cool but useless initiatives like XFN. However to me it was simply just another web thing being thrown around.

Then in August 2006, I came across Adrian Holovaty’s article where he argues journalism needs to move from a story-centric world to a data-centric world. And that’s when it dawned on me: the Semantic web is some serious business.

I have since done a lot of reading, listening, and thinking. I don’t profess to be a Semantic Web expert – but I know more than the average person as I have (painfully) put myself through videos and audios of academic types who confuse the crap out of me. I’ve also read through a myriad of academic papers from the W3C, which are like the times when you read a novel and keep re-reading the same page and still can’t remember what you just read.

Hell – I still don’t get things. But I get the vision, so that’s what I am going to share with you now. Hopefully, my understanding will benefit the clueless and the skeptical alike, because it’s a powerful vision which is entirely possible

1) The current web is great for humans; useless for machines
When you search for ambiguous terms, at best, search engines can algorithmically predict some sort of answer that partially answers your query. Sometimes not. But the complexity of language, is not something engineers can engineer to deal with. After all, without ambiguity of natural languages, the existence of poetry is impossible.

Fine.

What did you think when you read that? As in: “I’ve had it – fine!” which is like another way of saying ok or agreeing with something. Perhaps you thought about that parking ticket I just got – illegal parking gets you fined. Maybe you thought I am applauding myself by saying that was one fine piece of wordcraftship I just wrote, or said in another context, like a fine wine.

Language is ambiguous, and depending on the context with other words, we can determine what the meaning of the word is. Search start-up company Powerset, which is hoping to kill Google and rule the world, is employing exactly this technique to improve search: intelligent processing of words depending on context. So by me putting in “it’s a fine”, it understands the context that it’s a parking ticket, because you wouldn’t say “it’s a” in front of ‘fine’ when you use it to agree with something (the ‘ok’ meaning above).

But let’s use another example: “Hilton Paris” in Google – the worlds most ‘advanced’ search engine. Obviously, as a human reading that sentence, you understand because of the context of those words I would like to find information about the Hilton in Paris. Well maybe.

Let’s see what Google comes up with: Of the ten search results (as of when I wrote this blog posting), one was a news item on the celebrity; six were on the celebrity describing her in some shape or form, and three results were on the actual Hotel. Google, at 30/70 – is a little unsure.

Why is Paris Hilton, that blonde haired thingy of a celebrity, coming up in the search results?

Technologies like Powerset apparently produce a better result because it understands the order of the words and context of the search query. But the problem with these searches, isn’t the interpretation of what the searcher wants – but also the ability to understand the actual search results. Powerset can only interpret so much of the gazilions of words out there. There is the whole problem of the source data, no just the query. Don’t get what I mean? Keep reading. But for now, learn this lesson

Computers have no idea about the data they are reading. In fact, Google pumping out those search results is based on people linking. Google is a machine, and reads 1s and 0s – machine language. It doesn’t get human language

2) The Semantic web is about making what human’s read, machine readable
Tim Berner’s Lee, the guy that invented the World Wide Web and the visionary behind the Semantic Web, prefers to call it the ‘data web’. The current web is a web of documents – by adding this extra data to content – machines will be able to understand it. Metadata, is data about data.

A practical outcome of having a semantic web, is that Google would know that when it pulls up a web page regardless of the context of the words – it will understand what the content is. Think of every word on the web, being linked to a master dictionary.

The benefit of the semantic web is not for humans – at least immediately. The Semantic Web is actually pretty boring with what it does – what is exciting, is what it will enable. Keep reading.

3) The Semantic web is for machines to interpret, not people
A lot of the skeptics of the semantic web, usually don’t see the value of it. Who cares about adding all this extra meta data? I mean heck – Google still was able to get the website I needed – the Hilton in Paris. Sure, the other 60% of the results on that page were irrelevant, but I’m happy.

I once came across a Google employee and he asked “what’s the point of a semantic web; don’t we already enough metadata?” To some extent, he’s right – there are some websites out there that have metadata. But the point of the semantic web is so that machines once they read the information, can start thinking like how a human would and connecting it to other information. There needs to be across the board metadata.

For example, my friend Michael was recently looking to buy a car. A painful process, because there are so many variables. So many different models, different makes, different dealers, different packages. We have websites, with cars for sale neatly categorised into profile pages saying what model it is, what colour it is, and how much. (Which may I add, are hosted on multiple car sites with different types of profiles). A human painfully reads through these profiles, and computes as fast as a human can. But a machine can’t read these profiles.

Instead of wasting his (and my) weekends driving around Sydney to find his car, a machine could find it for him. So, Mike would enter his profile in – what he requires in a car, what his credit limit is, what his prior history with cars are – everything that would affect his judgement of a car. And then, the computer can query every online website with cars to match the criteria. Because the computer can interpret these websites across the board, it can evaluate and it can go back to Michael and say “this is the car for you, at this dealer – click yes to buy”.

The semantic web is about giving computers the information to be able to interpret data, so that it can do what they do really well – compute.

4) A worldwide database
What essentially Berner’s Lee envisions, is turning the entire world wide web into a database that can be queried. Currently, the web looks like Microsoft Word – one swab of text. However, if that swab of text was neatly categorised in an Excel spreadsheet, you could manipulate that data and do what you please – create reports, reorder them, filter, and do whatever until your heart is content.

At university, I was forced to do an Information Systems subject which was essentially about the theory of databases. Damn painful. I learned only two things from that course. The first thing was that my lecturer, tutor, and classmates spoke less intelligible English than a caterpillar. But the second thing was that I learned what information is and how it differs from data. I am now going to share with you that lesson, and save you three months of your life.

You see, data is meaningless. For example, 23 degrees is data. On its own, it’s useless. Another piece of data in Sydney. Again, Рuseless. I mean, you can think all sorts of things when you think of Sydney, but it doesn’t have any meaning.

Now put together 23 degrees and Sydney, and you have just created information. Information is about creating relationships between data. By creating a relationship, an association, between these two different pieces of data – you can determine it’s going to be a warm day in Sydney. And that is what information is: Relationship building; connecting the dots; linking the islands of data together to generate something meaningful.

The semantic web is about allowing computers to be able to query the sum of human knowledge like one big database to generate information

Concluding thoughts
You are probably now starting to freak out and think “Terminator” images with computers suddenly erupting form under your computer desk, and smashing you against the wall as a battle between humans and computers begins. But I don’t see it like that.

I think about the thousands of hours humans spend trying to compute things. I think of the cancer research, whereby all this experimentation occurring in labs, is trying to connect new pieces of data with old data to create new information. I think about computers being about to query the entire taxation legislation to make sure I don’t pay any tax, because it knows how it all fits together (having studied tax, I can assure you – it takes a lifetime to only understand a portion of tax law). In short, I understand the vision of the Semantic web as a way of linking things together, to enable computers to compute – so that I can sit on my hammock drinking my beer, as I can delegate the duties of my life to the machines.

All the semantic web is trying to do, is making sure everything is structured in a consistent manner, with a consistent dictionary behind the content, so that a machine can draw connections. As Berner’s Lee said on one of the videos I saw: “it’s all about creating links”.

The process to a Semantic Web is boring. But once we have those links, we can then start talking about those hammocks. And that’s when the power of the internet – the global network – will really take off.

On the future of search

Robert Scoble has put together a video presentation on how Techmeme, Facebook and Mahalo will kill Google in four years time. His basic premise is that SEO’s who game Google’s algorithm are as bad as spam (and there are some pissed SEO experts waking up today!). People like the ideas he introduces about social filtering, but on the whole – people are a bit more skeptical on his world domination theory.

There are a few good posts like Muhammad‘s on why the combo won’t prevail, but on the whole, I think everyone is missing the real issue: the whole concept of relevant results.

Relevance is personal

When I search, I am looking for answers. Scoble uses the example of searching for HDTV and makes note of the top manufacturers as something he would expect at the top of the results. For him – that’s probably what he wants to see – but for me, I want to be reading about the technology behind it. What I am trying to illustrate here is that relevance is personal.

The argument for social filtering, is that it makes it more relevant. For example, by having a bunch of my friends associated with me on my Facebook account, an inference engine can determine that if my friend called A is also friends with person B, who is friends with person C – than something I like must also be something that person C likes. When it comes to search results, that sort of social/collaborative filtering doesn’t work because relevance is complicated. The only value a social network can provide is if the content is spam or not – a yes or no type of answer – which is assuming if someone in my network has come across this content. Just because my social network can (potentially) help filter out spam, doesn’t make the search results higher quality. It just means less spam results. There is plenty of content that may be on-topic but may as well be classed as spam.

Google’s algorithm essentially works on the popularity of links, which is how it determines relevance. People can game this algorithm, because someone can make a website popular to manipulate rankings through linking from fake sites and other optimisations. But Google’s pagerank algorithm is assuming that relevant results are, at their core, purely about popularity. The innovation the Google guys brought to the world of search is something to be applauded for, but the extreme lack of innovation in this area since just shows how hard it is to come up with new ways of making something relevant. Popularity is a smart way of determining relevance (because most people would like it) – but since that can be gamed, it no longer is.

The semantic web

I still don’t quite understand why people don’t realise the potential for the semantic web, something I go on about over and over again (maybe not on this blog – maybe it’s time I did). But if it is something that is going to change search, it will be that – because the semantic web will structure data – moving away from the document approach that webpages represent and more towards the data approach that resembles a database table. It may not be able to make results more relevant to your personal interests, but it will better understand the sources of data that make up the search results, and can match it up to whatever constructs you present it.

Like Google’s page rank, the semantic web will require human’s to structure data, which a machine will then make inferences – similar to how Pagerank makes inferences based on what links people make. However Scoble’s claim that humans can overtake a machine is silly – yes humans have a much higher intellect and are better at filtering, but they in no way can match the speed and power of a machine. Once the semantic web gets into full gear a few years from now, humans will have trained the machine to think – and it can then do the filtering for us.

Human intelligence will be crucial for the future of search – but not in the way Mahalo does it which is like manually categorising pieces of paper into a file cabinet – which is not sustainable. A bit like how when the painters of the Sydney harbour bridge finish painting it, they have to start all over again because the other side is already starting to rust again. Once we can train a machine that for example, a dog is an animal, that has four legs and makes a sound like “woof” – the machine can then act on our behalf, like a trained animal, and go fetch what we want; how those paper documents are stored will now be irrelevant and the machine can do the sorting for us.

The Google killer of the future will be the people that can convert the knowledge on the world wide web into information readeable by computers, to create this (weak) form of artificial intelligence. Now that’s where it gets interesting.

BarCampSydney2

Things I learned at this BarCamp

  • It was a very different crowd from the first one.
  • It’s so easy to network – it was as difficult as breathing in, breathing out! I gave a presentation, and as a consequence, I had people throughout the day approach me and introduce themselves.
  • In the morning, collaboration was a bit of a hot theme. John Rotenstein from Atlassian asked the question of how do people define collaboration: “when two or more people work together on a business purpose”, was my answer. We agreed. Everyone else, kind of didn’t.
  • How to raise money – was the afternoon’s theme. Great points were brought up by Marty Wells, Mike Canon-Brookes and Dean McEvoy who led the discussion.
  • Some things mentioned:
  1. Aussie VC’s lead you on. “Nice idea- let’s keep in touch” is their way of not burning bridges
  2. VC’s work in a cycle that are in five or so year cycles – raise money at the beginning of the cycle
  3. Rule of thumb: give 30% away on the first round, 30% on the second round
  4. Advisor’s that give out Comet grants work on a 2% commission of future venture capital that you raise.
  5. No one understands the advertising market – everyone in the room wanted something they could read to learn more (check back here soon – I promise!). For example, Google’s adwords programme is largely supported by the property market – the mortgage lending market that is affected by the current credit crisis, is going to affect start-ups relying on adsense as the money drops out of these ads.
  • I met Jan Devos, who randomly approached me and blew me away with what he has done in his life. Basically (and from the age of 17), he created an implementation of the MPEG4 compression technology (for non-tech readers – MP4 as opposed to the older MP3) and he licenses out the technology to major consumer appliance companies like Samsung, who incorporate the technology into their products.
  • I met Dave O’Flynn – self-described as a “tall Irish red-head” developer; Matt June – a former Major in the Australian military, and now pursuing a project based around social innovation; I discovered Rai of Tangler is a commitmentphobe; Mick thinks he can skip most of BarCamp because he thinks organising a wedding is so hard; Mike Canon-Brookes over beer revealed he is a Mark Zuckerberg wannabe; and Christy Dena one of the lead (un)organisers of the conference looks completely different from the person I thought she was!

I got a positive reaction to my half hour session on five lessons I have learned on successful intrapreneurship due to a large internal project I started at my employer, with people throughout the day getting into a chat with me about it. Richard Pendergast, who is starting a online parenting site, said he was going to write a blog on one the points with his own personal battle of creating credibility. Glad I helped! I said to him I was going to blog what I talked about it so we could turn it into a discussion, but I have decided, this exam I have to sit in 12 8 days might need to start getting my attention. Anyway, here were the five points I made, however given the discussion during the session by everyone, is a very rough framework as people brought up some great points when talking:

1) It is a lot easier to seek forgiveness, than permission when doing something in an organisation. Or in other words, just do it.

2) Be proactive, never reactive. By pushing the agenda, you are framing the agenda for something that works for your project. Once you start reacting to others, your idea will die.

3) The more you let go – the bigger your idea will get. Use other people to achieve your vision. Give other people a sense of ownership in it. Let them take credit.

4) It’s all about perception. It’s amazing how much credibility you can build by simply associating your idea to other things – and which in the process, builds your own personal brand to push through with more later on.

5) Hype build hype. Get people excited, and they will carry your idea forward. People get excited when you communicate the potential, and have them realise it.

Thank you to all those involved – both the organisers and the contributors – and I look forward to the next one.

Thoughts on attention, advertising, and a metric to measure both: keep it simple

Advertising on the Internet is exploding. Assuming you accept my premise that the Internet will be the backbone of the world’s attention economy – then, I am sure you can see the urgency of developing an effective metric for measuring audiences that consume content online. Advertisers are expecting more accountability online and there is increasing demand for an independent third-party to verify results. But you can’t have accountability and there is no value in audits, if one place measures in apples and the other in bananas.

The Attention Economy is seriously lacking an effective measurement system

Ajax broke the pageview model of impressions, the one billion-dollar practice of click-fraud is the dirty big secret of pay-for-performance advertising, and the other major metric of using unique visitors (through cookies) is proving inaccurate.

It sounds crazy, doesn’t it? The Internet has the best potential for targeted advertising, and advertisers are moving onto it in stampedes – and yet, we still can’t work out how to measure audiences effectively. Measurement is broken on the Net.

(Although I am focusing on advertising, this can be applied in other contexts. An advertising metric is simply putting a monetary value on what is really an attention metric.)

Yet when we look at the traditional media, are we being a little harsh on this new media? Is the problem with the web’s measurement systems just that it is more accountable for its errors? After all – radio, television, and print determine their audience through inference which are based on sampling methods and not actually directly measuring an audience. Sampling is about making educated guesses – but a guess is still a guess.

Maybe another way of looking at it is that the old way of doing advertising is no longer effective. Although we can say pageviews are broken due to AJAX, the truth is it was always an ineffective measurement system, as it was based on the traditional media’s premise of how many viewers/subscribers theoretically and potentially could see that ad. As an example of why this is not how it should be: when people visit my blog via Google Images, they hang around for 30 seconds. People that search for business issues on the web that I write about, like stuff you are reading right now – spend 5+ minutes. If both are equal in terms of page views, but the later actually reads the pages and the former only scans the content for an image – why are we treating them equally? My blog is half about travel, and half about the business of the internet, which is why I have two very different audiences. Just because I get high page views from my travel content, doesn’t mean I can justify higher CPM’s for people that want to advertise on internet issues. Not all pageviews are the same – especially when I know the people giving me high pageviews, arn’t really consuming my content

Another issue is that advertisers are so caught up on who can create the most entertaining 30 second ad, that the creativity to get people entertained has ovetaken the reason why advertising happens in the first place: to make sales. The way you do that, is by communicating your product to the people that would want to buy it. If I placed advertising on this blog, from people who want to do web-business related stuff, they should only pay for the peope that read my blog postings for 5+ minutes on the Attention economy, not for the Google images searchers who are looking for porn (my top keywords, and how people find my blog, makes me laugh out loud sometimes!).

When we create a metric that measures attention, lets be sure of one thing: the old way is broken, and the new ways will continue to be broken if we simply copy and paste the old ways. New ways like click-through ads that appear on search results, and account for 40% of internet advertising is not how advertising should be measured. The reason is because it is putting the burden of an effective advertising campaign, on a publisher. Why should a publisher not get paid, with the opportunity cost of not using another ad that would have paid, because of the ineffectiveness of the advertisers campaign strategy at targeting?

When measuring audience attention, lets not overcomplicate it. It should be purely measuring if someone saw it. As an advertiser, I should be able to determine which people from which demograph can see it my ad – and yes, I will pay the premium for that targeting. If it turns into a sale, or if they enjoyed the content – is where your complex web analytic packages come in. But for a simple global measurement system, lets keep it simple.

Concluding thought

If I stood at the toll booths of the Sydney Harbour bridge naked, some people will honk at me and others won’t. If I can guarantee that they can see me naked, that’s all as a publisher I need to do. It’s the advertisers problem if people honk at me or not. (Not enough honks means as a model I should still get my wage. They just need to hire a better looking model next time!)

Australia as Silicon Beach

In January, David Bolliger coined the term “Sillicon Beach” to refer to a bunch of Sydney based start-ups – continuing an international trend of regionalising hotspots of tech innovation that aspire to be like Sillicon Valley (my other favourite is New York as Sillicon Alley). Although it’s not the first time the term has been used, everyone from Perth, Melbourne, Newscastle, Brisbane, and the rest are claiming they are the real silicon beach.

So seeing as our population is only 20 million, and we are one big island continent anyway – I think I am going to settle with calling Australia’s tech industry as a whole as “Silicon Beach”.

Tangler

This is the second post in a series – wizards of oz – which is to highlight the innovation we have down under, and how the business community needs to wake up and realise the opportunities. I review Tangler, a Sydney-based start-up that has recently released their application to the world as a public beta.

Tangler is a web-service that enables discussions over a network. Think of discussions with the immediacy of Instant Messaging (it’s easy), but with the persistency of a forum (messages are permanently stored). Discussions are arranged into communities of interest (groups), which are further broken down into topic areas. Click here to see a video overview.

Value

1) It’s a network application. Although it’s got a great design, and looks like a funky website, the real power of this web service is what it’s working towards: discussions over a network. Imagine a little widget with the topic “What do you think of Elias Bizannes?” placed on my (external) personal blog, my internal work blog, my myspace/facebook/social networking page, as well as it’s own dedicated forum on the Tangler site. A centralised discussion, in a decentralised manner. That’s big.

2) It’s community has great DNA. Communities are not easy things to build – my own experience on a getting-bigger-by-the-day internal project has shown that it is a complex science, touching everything from understand motivational theory to encouraging the right kind of behaviours (policing without policing). My usage on the site has shown to me that the active community building currently occuring, is on the right track. Anyone can hire a code monkey, wack on some flashy front-end, and say they have a great product. But not anyone can build a strong community – even Google struggles on this (the acquisition of YouTube happened largely because of community, because the YouTube community beat Google’s own service). Tangler’s community is already turning into a powerful asset – the DNA is there – now it just needs exposure, and the law of cumulative advantage will kick in.

3) The founder and staff are responsive to its community. I posted a question on the feedback forum, to prove this point: I got a response in an hour, on a Saturday. The staff at Tangler are super responsive – which in part, is due to the real-time discussion ability of the software – but also because of their commitment. As I state above – the value of Tangler is the community of users it builds – this type of responsiveness is crucial to keep its users satisfied to come back, because it makes them feel valued. Additionally, the community is driving the evolution of the application, and that’s the most powerful way to create something (adapting to where there is a need by the people that use it)

4) It’s a platform. What makes Tangler powerful, is that it encourages discussions around niche content areas. Make that niche content, being created for free. Low cost to produce + highly targeted content = an advertisers dream. Link it with a distributed network across the entire Internet (see 1 above), and you’ve got something special.

Conclusion

Social networks, which is what Tangler is, are characterised by:
1) the existence of a repository of user-generated content and
2) the need of members to communicate.

Tangler’s user-generated content and communications web make them an interesting fit for both media conglomerates and telecommunication companies (but for different reasons). I see a Tangler acquisition as a no-brainer for the big Telco’s. Integrating a social network like Tangler into Telstra, builds on the synergy between the communication needs of social network users and the communications expertise and service infrastructure of the communication companies. Unlike voice calls that are a commodity now, the Telco’s need to take advantage of their network infrastructure and accommodate for text-based discussions, which can be monetised for as long as the content exists (with advertising).

The challenge for Tangler however – as with any other Internet property – is that the scale of the audience of social networks determines the nature of the relationship with a communications company. Micro-sized social networks are not interesting to communication companies. Massive social networks are, but history has shown they would rather be partners than be acquired. To be attractive to the big end of town, Tangler needs to show to have a scale large enough to grow as a business but not too large to dictate the terms of the business.

My observations conclude me to think that they will be a hit once they open up their application to external developers, which will relieve the development bottleneck faced by their resource and time constrained team. However they shouldn’t rush this, as I still think their performance issues are not completely ironed out yet. An open API would be taken up by its enthusiastic community who are technologically orientated. Not too mention the strong relationships the CEO and CMO have forged with the local web entrepreneurial and development community in Australia.

My boss is currently doing a secondment as acting Finance Director at Sensis, Telstra’s media arm. Maybe I need to organise a catch-up with him, before these guys get snatched up by some US conglomerate!

New measurement systems need a purpose

Chris recently proposed a new measurement system for attention, after yet another call to arms for a new way of measuring metrics. This is a hard issue to gnaw at, because it’s attempting to graple at the emerging business models of a new economy, which we are still at the cross roads at. Chris asked us on the APML workgroup on what we thought of his proposal, which is interesting, but I thought it might be better to take a step back on this one and look at the bigger picture. Issues this big need to be conceptually clear, before you can break into the details.

Television, radio, and newspapers are the corner stone of what we regard as the mainstream media. For decades, they have ruled the media business – with their 30 second advertising spots, and “pageviews” (circulation). Before the information age, they were what the ‘attention economy’ was. None of those flamin’ blogs stealing our attention: content and advertising flowed through to us from one place.

The internet is enabling literally an entire new Age of humanity. A lot of the age-old business models have been replicated, because we don’t know any better, but people are abandoning them because they are realising they can now do so much more. So the key here is not to get too excited on what you can do – rather, we need to think why what we need to do.

Let me explain – advertisers sold their product on a TV/radio commercial, and a newspaper page, because it guaranteed them that a certain amount of people would see it. Advertisers advertise because they want to do one thing: to make money. It’s just how capitalism works – profit is god – so do what you can to make higher profit.

But back then, the traditional mainstream media was the only way they could reach audiences on an effective scale. However advertising on the Sunday night movie is the equivalant to dropping a million pamphlets out of a plane, hoping that the five customers you know that would buy your product, end up catching it. Back then, no one complained – it was the best we could do. It sucked, but we didn’t know any better.

The internet changed that.

Advertisers can now target their advertising to a specific individual. They don’t care anymore about advertising on a mass scale; what they would rather is advertising on a micro scale. Spending $20,000 on 10,000 people you know that want to buy your product, has a much better Return on Investment than $2,000,000 on 1,000,000 people – of which 10% don’t speak the language of your ad, 20% aren’t the target group for your ad; and 30% are probably offended by your ad and will ruin it for the 40% they you were targeting in the first place.

Sound crazy? Well Google making $10 billion dollars doing just that is crazy.

So now that we have cleared that up – let’s get back to the issue. We now know one of the reasons why we need measurement: advertisers want to target their advertising better. Are there any other reasons? Sure- sometimes people want to measure what their audience reads for non-monetary reasons – they could just trying to find out what their readers are interested in, so they can focus on that content. Statistics like that is not narcissism – it’s just being responsive to an audience. Or then again, it could be pure ego.

So when it comes to measuring content, there are two reasons why anyone cares: to make money, or to see how people react to your content. However it’s the first type that is causing us problems in this issue. And that’s because how long someone spends on your content, or how many people view your content, is no longer relevant as it was in the mass media days. What is relevant is WHO is reading your content.

I don’t think you can have a discussion about new ways of measuring the way content is consumed, without separating those two different motives for measurement. I like Chris’s proposal – knowing how long someone spends reading my blog posting is something I would find interesting as a blogger. But that’s pure ego – I just want to know if I have a readership of deep thinkers or random Google visitors that were looking for a picture about shorts skirts. (As an aside – one of my pictures is the number one Google image result for “women in short skirts” – thank God it goes to my Flickr account now, the bandwidth that used to eat up was crazy!)

So before we come up with new measurement systems, lets spend more time determining why we are measuring. Simply saying we are better measuring what consumers are giving their attention to, is only part of the problem. We need to first determine what value we obtain from measuring that attention in the first place.

My media consumption

I’ve only recently started blogging again, and I need to get into the habit. Even though I have a gazillion things I want to write about, I literally don’t have the time! So here’s a quick post, to keep me – ahem – regular. It’s actually something I think about a lot, given my interest in the internet started from my interest/background in media. Meme was started by Jeremiah, and I saw it on a posting by Marty.

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