Tag Archive for 'profiling'

Advertising on the Internet needs innovation

On the weekend, I caught up with Cameron Reilly of the Podcast network , and he was telling me about his views on monetising podcasts. It got me thinking again about those things I like to think about: how content can be monetised. Despite the growth in online advertising which is tipped to be $80 billion, I think we still have a lot more innovation to go with revenue models, especially ones that help content creators.

Advertising is a revenue stream that has traditionally enabled content-creators to monetise their products, in the absence of people paying a fee or subscription. With the Internet, content has undergone a radical changing of what it is – digital, abundant, easily copied – whilst the Internet has offered new opportunities for how advertising is done. However, the Internet has identified the fundamental weaknesses of advertising , as consumers can now control their content consumption, which allows them to ignore embedded advertising altogether. Content on the other hand, still remains in demand, but means of monetising it are slipping into a free economy which is not sustainable. I make that point to illustrate not that professional content creation is a sunset industry – but rather there’s a big market opportunity as this massive industry needs better options.

time mag

"Hey man, there’s this new thing called the Internet. Sounds pretty cool"

One of the biggest innovations in advertising (and enabled by the Internet) is of contextual search advertising. This has been popularised by Google, which now makes 98% of its $17 billion revenue from these units. This advertising dominates online advertising (40% of total) because of its pull nature, whereby key-words stated by a consumer in effect state their intention of what they are interested or would like to purchase. Whilst this is a highly efficient form of advertising, it also has its weaknesses – for example, it is not as effective outside of the search engine environment. Google makes 35% of its revenue from the adSense network , where these contextual ads are placed on peoples personal websites. Evidence from high traffic bloggers suggests they barely make enough money through this type of advertising. Another point to consider is that aspects of the Google network include significant partnership agreements like the one with AOL which accounts for 10% of Googles revenue (this is a 2005 figure which has likely changed, but Google does state in their 2007 report "Our agreements with a few of the largest Google Network members account for a significant portion of revenues derived from our AdSense program. If our relationship with one or more large Google Network members were terminated or renegotiated on terms less favorable to us, our business could be adversely affected.". AOL most recently reported for Q1 2008 half a billion dollars largely from search advertising ).

Other attempts at creating more efficient advertising which have existed for over a decade, have come in the form of profiling or behavioural tracking. However, these forms of advertising has also highlighted the growing awareness of consumer privacy being eroded, and is under heavy scrutiny by activist groups and government. Facebook is a company that is best posed to deliver new forms of advertising because of the rich profiling data it has, but it itself has faced massive backlash .

My view is that the majority of online advertising for successful individual publishers at least, has largely come from traditional approaches to advertising – a masthead blog with a sales team that uses display advertising. How effective this display advertising is is debateable with widespread banner blindness and consumer control over their content, but it would appear that this is more a case of advertisers seeing this as the least bad on the overall scale of opportunities. The fact it replicates the mass media approach of number of unique consumers viewing the content, and not the types of users, means this isn’t anything new other than being done in a digital environment.

Digital content is in need of a better monetisation system.
Targeted advertising is the most efficient form, yet consumer privacy is a growing force preventing this. What we need, is not a new advertising technology, but a new way of thinking about advertising – in a way that can help the content economy rather than riding on it without giving benefit. Contextual advertising sounds great in theory as it calculates key-word frequency of words on a website, to match it to a key word ad – but it’s proving in practice these ads are not very relevant. Yet trying to think of a smarter way to advertise, may be the wrong question – perhaps half the problem itself is advertising as a concept?

perspective

Are we running down a tunnel, only to find there is nothing there?

Content which comes in the form of news (historical and breaking), analysis, and entertainment can be monetised via a persons attention or through a transaction (ie, subscription, fee, etc). Both this approaches have different barriers.

– Attention: The key driver is increased dollars per unique person, over a period of time. The barriers to this approach is the challenge of identifying the individual in a way that gives advertising that is highly relevant and will result in a conversion. In other words, privacy privacy privacy.

– Alternative payment: Requiring consumers to pay for content is a barrier due to the paid wall. What is more problematic for digital content, is that the ability to replicate it freely makes it not just easy to do for the masses but has created a culture of if it’s not free, it’s not worth purchasing unless its really necessary. There needs to be a strong value proposition for a consumer to purchase content, and in the absense of a brand and marketing, the restriction of what value the content offers is a barrier for consumer demand as they don’t know what they are missing out on.

So as you see above, content creators are in a difficult position. Charging people reduces their opportunity unless they are really established, but even then, due to the digital environment they don’t have any control over subsequent distribution (with rampant piracy). Yet advertising is fraught with being irrelevant and hence not effective (so advertisers go to other forms) and any attempts to make it more relevant, gets held back by the concerns of privacy advocates (and rightly so). Whilst the Internet parades itself as an advertising growth machine, it’s growing in new areas but not the old areas that have traditionally been the medium for advertisers.

This advertising growth is largely being driven through utility computing products that aim to make information retrieval more efficient (ie, search). However, the growth for the content creators, is not happening. As Cam was telling me, in a market like Australia – small content organisations like TPN and Bronwen Clune ‘s Norgs , don’t have access to the big end of town for a sales team. And he didn’t have to tell me, those Google ads for the smaller guys, are not enough to pay the bills. That small to middle end is not being really catered for.

But before you jump on the phone and create some mid-tier advertising network that caters for a niche, think about the real problem: content creators need a better solution to monetise their content. But advertisers also need a better way of selling, other than some slick-talking sales person who can sell ads on pageviews (a broken model with weak alternatives ) They need advertising that is suited for their product, but the market now includes other products media outlets never had to compete with like marketplaces now happening online and utility computing products. Whilst the technology community obsesses about search , let’s also remember we have yet to see a new way to monetise content that is superior to the old world. Contextual advertising of text is the latest new thing area, but that technique is nearly a decade old. As I prove above, outside of the search environment, it is showing to not be that effective.

Where is the innovation going to come from? Not through technology but with a new paradigm shift like how content creators operate . New ways of thinking about the way we ‘sell’ like what the VRM Project is challenging. But perhaps more fundamentally, is an understanding that the holy grail of targeted advertising has got a speed hump called privacy – and that may actually be a sign of not going faster towards better targeting, but changing the vehicle all together.

How Google reader can finally start making money

Today, you would have heard that Newsgator, Bloglines, Me.dium, Peepel, Talis and Ma.gnolia have joined the APML workgroup and are in discussions with workgroup members on how they can implement APML into their product lines. Bloglines created some news the other week on their intention to adopt it, and the announcement today about Newsgator means APML is now fast becoming an industry standard.

Google however, is still sitting on the side lines. I really like using Google reader, but if they don?¢‚Ǩ‚Ñ¢t announce support for APML soon, I will have to switch back to my old favourite Bloglines which is doing some serious innovating. Seeing as Google reader came out of beta recently, I thought I?¢‚Ǩ‚Ñ¢d help them out to finally add a new feature (APML) that will see it generate some real revenue.

What a Google reader APML file would look like
Read my previous post on what exactly APML is. If the Google reader team was to support APML, what they could add to my APML file is a ranking of blogs, authors, and key-words. First an explanation, and then I will explain the consequences.

In terms of blogs I read, the percentage frequency of posting I read from a particular blog will determine the relevancy score in my APML file. So if I was to read 89% of Techcrunch posts ?¢‚Ǩ‚Äú which is information already provided to users ?¢‚Ǩ‚Äú it would convert this into a relevancy score for Techcrunch of 89% or 0.89.

ranking

APML: pulling rank

In terms of authors I read, it can extract who posted the entry from the individual blog postings I read, and like the blog ranking above, perform a similar procedure. I don?¢‚Ǩ‚Ñ¢t imagine it would too hard to do this, however given it?¢‚Ǩ‚Ñ¢s a small team running the product, I would put this on a lower priority to support.

In terms of key-words, Google could employ its contextual analysis technology from each of the postings I read and extract key words. By performing this on each post I read, the frequency of extracted key words determines the relevance score for those concepts.

So that would be the how. The APML file generated from Google Reader would simply rank these blogs, authors, and key-words – and the relevance scores would update over time. Over time, the data is indexed and re-calculated from scratch so as concepts stop being viewed, they start to diminish in value until they drop off.

What Google reader can do with that APML file
1. Ranking of content
One of the biggest issues facing consumers of RSS is the amount of information overload. I am quite confident to think that people would pay a premium, for any attempt to help rank the what can be the hundreds of items per day, that need to be read by a user. By having an APML file, over time Google Reader can match postings to what a users ranked interests are. So rather than presenting the content by reverse chronology (most recent to oldest); it can instead organise content by relevancy (items of most interest to least).

This won?¢‚Ǩ‚Ñ¢t reduce the amount of RSS consumption by a user, but it will enable them to know how to allocate their attention to content. There are a lot of innovative ways you can rank the content, down to the way you extract key works and rank concepts, so there is scope for competing vendors to have their own methods. However the point is, a feature to ?¢‚ǨÀúSort by Personal Relevance?¢‚Ǩ‚Ñ¢ would be highly sort after, and I am sure quite a few people will be willing to pay the price for this God send.

I know Google seems to think contextual ads are everything, but maybe the Google Reader team can break from the mould and generate a different revenue stream through a value add feature like that. Google should apply its contextual advertising technology to determine key words for filtering, not advertising. It can use this pre-existing technology to generate a different revenue stream.

2. Enhancing its AdSense programme

blatant ads

Targeted advertising is still bloody annoying

One of the great benefits of APML is that it creates an open database about a user. Contextual advertising, in my opinion is actually a pretty sucky technology and its success to date is only because all the other types of targeted advertising models are flawed. As I explain above, the technology instead should be done to better analyse what content a user consumes, through keyword analysis. Over time, a ranking of these concepts can occur ?¢‚Ǩ‚Äú as well as being shared from other web services that are doing the same thing.

An APML file that ranks concepts is exactly what Google needs to enhance its adwords technology. Don?¢‚Ǩ‚Ñ¢t use it to analyse a post to show ads; use it to analyse a post to rank concepts. Then, in aggregate, the contextual advertising will work because it can be based off this APML file with great precision. And even better, a user can tweak it ?¢‚Ǩ‚Äú which will be the equivalent to tweaking what advertising a user wants to get. The transparency of a user being able to see what ‘concept ranking’ you generate for them, is powerful, because a user is likely to monitor it to be accurate.

APML is contextual advertising biggest friend, because it profiles a user in a sensible way, that can be shared across applications and monitored by the user. Allowing a user to tweak their APML file for the motivation of more targeted content, aligns their self-interest to ensure the targeted ads thrown at them based on those ranked concepts, are in fact, relevant.

3. Privacy credibility
Privacy is the inflation of the attention economy. You can?¢‚Ǩ‚Ñ¢t proceed to innovate with targeted advertising technology, whilst ignoring privacy. Google has clearly realised this the hard way by being labeled one of the worst privacy offenders in the world. By adopting APML, Google will go a long way to gain credibility in privacy rights. It will be creating open transparency with the information it collects to profile users, and it will allow a user to control that profiling of themselves.

APML is a very clever approach to dealing with privacy. It?¢‚Ǩ‚Ñ¢s not the only approach, but it a one of the most promising. Even if Google never uses an APML file as I describe above, the pure brand-enhancing value of giving some control to its users over their rightful attention data, is something alone that would benefit the Google Reader product (and Google?¢‚Ǩ‚Ñ¢s reputation itself) if they were to adopt it.

privacy

Privacy. Stop looking.

Conclusion
Hey Google – can you hear me? Let’s hope so, because you might be the market leader now, but so was Bloglines once upon a time.

Explaining APML: what it is & why you want it

Lately there has been a lot of chatter about APML. As a member of the workgroup advocating this standard, I thought I might help answer some of the questions on people’s minds. Primarily – “what is an APML file”, and “why do I want one”. I suggest you read the excellent article by Marjolein Hoekstra on attention profiling that she recently wrote, if you haven’t already done so, as an introduction to attention profiling. This article will focus on explaining what the technical side of an APML file is and what can be done with it. Hopefully by understanding what APML actually is, you’ll understand how it can benefit you as a user.

APML – the specification
APML stands for Attention Profile Markup Language. It’s an attention economy concept, based on the XML technical standard. I am going to assume you don’t know what attention means, nor what XML is, so here is a quick explanation to get you on board.

Attention
There is this concept floating around on the web about the attention economy. It means as a consumer, you consume web services – e-mail, rss readers, social networking sites – and you generate value through your attention. For example, if I am on a Myspace band page for Sneaky Sound System, I am giving attention to that band. Newscorp (the company that owns MySpace) is capturing that implicit data about me (ie, it knows I like Electro/Pop/House music). By giving my attention, Newscorp has collected information about me. Implicit data are things you give away about yourself without saying it, like how people can determine what type of person you are purely off the clothes you wear. It’s like explicit data – information you give up about yourself (like your gender when you signed up to MySpace).

Attention camera

I know what you did last Summer

XML
XML is one of the core standards on the web. The web pages you access, are probably using a form of XML to provide the content to you (xHTML). If you use an RSS reader, it pulls a version of XML to deliver that content to you. I am not going to get into a discussion about XML because there are plenty of other places that can do that. However I just want to make sure you understand, that XML is a very flexible way of structuring data. Think of it like a street directory. It’s useless if you have a map with no street names if you are trying to find a house. But by having a map with the street names, it suddenly becomes a lot more useful because you can make sense of the houses (the content). It’s a way of describing a piece of content.

APML – the specification
So all APML is, is a way of converting your attention into a structured format. The way APML does this, is that it stores your implicit and explicit data – and scores it. Lost? Keep reading.

Continuing with my example about Sneaky Sound System. If MySpace supported APML, they would identify that I like pop music. But just because someone gives attention to something, that doesn’t mean they really like it; the thing about implicit data is that companies are guessing because you haven’t actually said it. So MySpace might say I like pop music but with a score of 0.2 or 20% positive – meaning they’re not too confident. Now lets say directly after that, I go onto the Britney Spears music space. Okay, there’s no doubting now: I definitely do like pop music. So my score against “pop” is now 0.5 (50%). And if I visited the Christina Aguilera page: forget about it – my APML rank just blew to 1.0! (Note that the scoring system is a percentage, with a range from -1.0 to +1.0 or -100% to +100%).

APML ranks things, but the concepts are not just things: it will also rank authors. In the case of Marjolein Hoekstra, who wrote that post I mention in my intro, because I read other things from her it means I have a high regard for her writing. Therefore, my APML file gives her a high score. On the other hand, I have an allergic reaction whenever I read something from Valleywag because they have cooties. So Marjolein’s rank would be 1.0 but Valleywag’s -1.0.

Aside from the ranking of concepts (which is the core of what APML is), there are other things in an APML file that might confuse you when reviewing the spec. “From” means ‘from the place you gave your attention’. So with the Sneaky Sound System concept, it would be ‘from: MySpace’. It’s simply describing the name of the application that added the implicit node. Another thing you may notice in an APML file is that you can create “profiles”. For example, the concepts about me in my “work” profile is not something I want to mix with my “personal” profile. This allows you to segment the ranked concepts in your APML into different groups, allowing applications access to only a particilar profile.

Another thing to take note of is ‘implicit’ and ‘explicit’ which I touched on above – implicit being things you give attention to (ie, the clothes you wear – people guess because of what you wear, you are a certain personality type); explicit being things you gave away (the words you said – when you say “I’m a moron” it’s quite obvious, you are). APML categorises concepts based on whether you explicitly said it, or it was implicitly determined by an application.

Okay, big whoop – why can an APML do for me?
In my eyes, there are five main benefits of APML: filtering, accountability, privacy, shared data, and you being boss.

1) Filtering
If a company supports APML, they are using a smart standard that other companies use to profile you. By ranking concepts and authors for example, they can use your APML file in the future to filter things that might interest you. As I have such a high ranking for Marjolein, when Bloglines implements APML, they will be able to use this information to start prioritising content in my RSS reader. Meaning, of the 1000 items in my bloglines reader, all the blog postings from her will have more emphasis for me to read whilst all the ones about Valleywag will sit at the bottom (with last nights trash).

2) Accountability
If a company is collecting implicit data about me and trying to profile me, I would like to see that infomation thank you very much. It’s a bit like me wearing a pink shirt at a party. You meet me at a party, and think “Pink – the dude must be gay”. Now I am actually as straight as a doornail, and wearing that pink shirt is me trying to be trendy. However what you have done is that by observation, you have profiled me. Now imagine if that was a web application, where this happens all the time. By letting them access your data – your APML file – you can change that. I’ve actually done this with Particls before, which supports APML. It had ranked a concept as high based on things I had read, which was wrong. So what I did, was changed the score to -1.0 for one of them, because that way, Particls would never show me content on things it thought I would like.

3) Privacy
I joined the APML workgroup for this reason: it was to me a smart away to deal with the growing privacy issue on the web. It fits my requirements about being privacy compliant:

  • who can see information about you
  • when can people see information about you:
  • what information they can see about you

The way APML does that is by allowing me to create ‘profiles’ within my APML file; allowing me to export my APML file from a company; and by allowing me to access my APML file so I can see what profile I have.

drivers

Here is my APML, now let me in. Biatch.

4) Shared data
An APML file can, with your permission, share information between your web-services. My concepts ranking books on Amazon.com, can sit alongside my RSS feed rankings. What’s powerful about that, is the unintended consequences of sharing that data. For example, if Amazon ranked what my favourite genres were about books – this could be useful information to help me filter my RSS feeds about blog topics. The data generated in Amazon’s ecosystem, can benefit me and enjoy a product in another ecosystem, in a mutually beneficial way.

5) You’re the boss!
By being able to generate APML for the things you give attention to, you are recognising the value your attention has – something companies already place a lot of value on. Your browsing habits can reveal useful information about your personality, and the ability to control your profile is a very powerful concept. It’s like controlling the image people have of you: you don’t want the wrong things being said about you. 🙂

Want to know more?
Check the APML FAQ. Othersise, post a comment if you still have no idea what APML is. Myself or one of the other APML workgroup members would be more than happy to answer your queries.

Privacy – just like inflation

Privacy is a massive business issue. I’ve commented on the lack of interest in privacy from entrepreneurs in the web space; I’ve tried to define privacy; and I joined the APML workgroup for this reason

Need to know why I think it matters? Well here are three facts:

1) Targeted advertising is the future of advertising. Why? Because it’s most effective type of advertising.

2) Web services, and arguably the entire attention economy, rely on advertising as a revenue model.

3) There is a natural friction between targeted advertising and privacy. You can’t target without knowing who you are targeting – which implies some type of implicit collection of data.

Google, on the strength of its brand, has been able to manage the privacy issue. But no longer. Privacy International has ranked Google at the worst privacy offended on the internet. As 99% of Google’s revenue relies on advertising, with open acknowledgment that they are trying to find ways of better targeting advertising, we can expect to hear more and more how Google’s evil is in the data they collect and the way they control it.

Economic growth is one of the key concepts to how our world works – it’s what companies and countries for example, constantly aim for. But as we have seen repeatedly, if an economy grows too quickly, problems can appear – inflation, infrastructure issues, and fatigue. Greed has a price. In the context of an economy, inflation is the speed-hump – the faster you drive over it, the bigger the hit.

So would it be too far to extend the metaphor, to say that privacy is the advertising equivalent to inflation? If you are relying on advertising as a revenue model, remember that privacy will matter more and more with an interconnected world.

The Wizards of Oz

The Internet has enabled a new world-order, causing people from the CEO down in almost every industry, an amazing amount of grief. The music industry, the newspaper industry, the telecommunications industry – heck, even tangible non-digital products like books – have been challenged at the core. However what these CEO’s have begun to realise, is that the Digital Age is no longer a threat, but a vehicle for growth.

Innovation is a key source of competitive advantage. And if you are an established company, innovation is hard. What takes six months of trying to convince the right people, jumping through hoops to keep internal stakeholders happy, and then finally releasing a half-baked product that is dramatically cut down from your vision – could be done by a bunch of college students in a garage over a weekend. Economies of scale is no longer an advantage in the Information Age – small, agile teams are.

In America – Google, Yahoo, Microsoft, News Corp, IAC and the rest – rely on acquisitions to fuel their innovation. An amazing amount of innovation is occurring on the web at the moment – not just new products but new business models. And the above mentioned companies have realised that acquiring a start-up early on, is a cheap way to innovate – as well as a great way to recruit.
But what about Australia?

Like America, we have a strong Internet industry with some clever entrepreneurs. But unlike America – no one is acquiring them. Could it be executives of this country’s leading companies just don’t know how much talent is available onshore? Well working in a professional services company that advises these companies, I am sure of it. Even a tech-savvy person like me is still discovering the amazing amount of talent and potential in my city, let alone country.

So here is to educating – both you and me – as I begin to start profiling innovation in Australia To make a suggestion for me to review on my blog, post it here

How to become the next Google

During the industrial age, information was a scarce commodity. The flow of information was controlled by the mass media – books, newspapers, television – were the sole distributors of information. The media during this age had a huge influence on society because the mass media was effectively the "gatekeeper" of information in society. Supply, or rather the distribution-capacity to supply information, was limited.

Criticism of these gatekeepers occurred for their power on what information they distributed, a thing the internet changed. We now live in the Information Age, which has come on the back of the internet. This has opened up the distribution points of information ?¢‚Ǩ‚Äú access to information is no longer dependent on the mass media – and availability is no longer confined by physical constraints (the internet has potentially an infinite storage). No longer do the traditional gatekeepers control the flow of and access to information.

The consequence of losing the old gatekeepers is that information is now plenty and consumers face information overload. Due to an environment of limited distribution in the Industrial Age, the mass media by consequence filtered information for consumers. Now with infinite information available, consumers are finding it difficult to filter information: identifying quality information was a role that wasn’t totally appreciated before. The cost of consuming quality information is being bourne by the consumer, as they are forced to identify it themselves.

The attention economy has risen as an important factor, as consumers only have limited attention to view the now unlimited amount of information. The new scarce commodity is no longer information, but the attention of consumers. Demand for information is now limited – people only have so much time to sift through the abundance of information.

Why search and aggregation services are valuable to consumers
The 1990s saw the development of search engines as a solution to this problem. Search engines have now become the new gatekeepers of information, as they provide consumers a means of filtering information and returning only what is relevant. Search works as a filtering system because consumers identify what they want, and a search engine simply needs to associate pre-indexed information that best matches that request. Innovation in search is about increasing the relevance of information to that request.

Other technologies have also been developed, which allow for the filtering of information. "Aggregation" services similar in role to what newspapers for example traditionally did – help pull together information from disparate sources. The value of these aggregation services, is in the value of relevant information to the consumer – a similar scenario to search. Search engines help consumers pull information; aggregation services push information, with what they think a consumer would want.

With both these "pull" and "push" technologies, consumers are reverting back to an industrial age concept of trust in brands. Google’s search for example, has impressive technology. But so do its rivals. User experience aside, the biggest advantage Google has is that users trust its brand more for the quality of information provided. Users trust Google to provide more relevant information – relevance is quality. The same reason why consumers used to trust a broadsheet newspaper over a student newspaper, is in the credibility of that brand to provide quality. The brand was and still is a way for consumers to filter information – or rather, trust others to provide information they can rely on.

The future

If you are looking to start a new search engine that will beat Google: don’t. If you think you have a brand new of way identifying quality information: spend your efforts there. Remember the reason why search, RSS, and profiling aggregators are important to consumers, is because they help them find the best quality information, in the shortest period of time.

You can’t beat Google at search. And if you do, by the time you do, it will be a waste of time because the industry will have evolved. Innovation on the internet and the Information Age, is about understanding why the traditional gate keepers were so effective in what they did. The last decade has seen some clever innovation – but we still have a long way to go.

I’m on the APML workgroup

As Chris announced, I’m now a member of the APML work-group. So the question, is why have I joined it? Because profiling is huge. People are only starting to get to grips with the loss of privacy on the web – I suppose an externality of an electronic world. I remember reading about some guy who posted on a marijuana bulletin board in 2000, and that it still comes up in Google searches. Prospective employers, prospective girlfriends, prospective anything – he now cannot control the information that he was once a pot head. It’s like someone watching you get changed, and you don’t have the option of pulling the curtain. Privacy, is about giving you the choice to use that curtain – whether you’re an exhibitionist or not!

Something a lot of people arn’t aware of, is the amount of data other companies are collecting – and you can’t control it. You reading this blog posting – I can find out what browser you have, what city you are viewing this from, who your Internet service providor is – heck I even know what version of windows you use. And I’m not even trying to profile you – think about Google or DoubleClick that know of every website you visit by placing a cookie on your computer.

Why do people want to collect information about you, known as your “attention data”? Because they can profile you – and when you can profile someone, you can personalise the experience for them…and target their advertising better.

The APML standard does a very simple thing: it allows you to control your “attention”. It’s still early days, and although there are some smart people discussing some deep issues on it, everyone on the work-group is still feeling their way of where this standard is going to go.

If you have thought about targeted advertising – and if you don’t you should – I would watch this standard. Or better still, start discussing it – this is a huge opportunity to set things right, before the Internet dominates our lives.