Monthly Archive for October, 2007

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.

Bloglines to support APML

Tucked away in a post by one of the leading RSS readers in the world, Bloglines had announced that they will be investigating on how they can implement APML into their service. The thing about standards is that as fantastic as they are, if no one uses them, they are not a standard. Over the last year, dozens of companies have implemented APML support and this latest annoucement by a revitalised Bloglines team that is set to take back what Google took from them, means we are going to be seeing a lot more innovation in an area that has largely gone unanswered.

The annoucement has been covered by Read/WriteWeb, APML founders Faraday Media,?Ç? and a thoughtful analysis has been done by Ross Dawson. Ben Melcalfe had also written a thought-provoking analysis, of the merits of APML.

What this means?

APML is about taking control of data that companies collect about you. For example, if you are reading lots of articles about dogs, RSS readers can make a good guess you like dogs – and will tick the “likes dogs” box on the profile they build of you which they use to determine advertising.?Ç? Your attention data is anything you give attention to – when you click on a link within facebook, that’s attention data that reveals things about you implicitly.

The big thing about APML is that is solves a massive problem when it comes to privacy. If you look at my definition of what constitutes privacy, the abillity to control what data is collected with APML, completely fits the bill. I was so impressed when I first heard about it, because its a problem I have been thinking about for years, that I immediately joined the APML workgroup.

Privacy is the inflation of the attention economy, and companies like Google are painfully learning about the natural tension between privacy and targetted advertising. (Targetted advertising being the thing that Google is counting on to fund its revenue.) The web has seen a lot of technological innovation, which has disrupted a lot of our culture and society. It’s time that the companies that are disrupting the world’s economies, started innovating to answer the concerns of the humans that are using their services. Understanding how to deal with privacy is a key competitive advantage for any company in the Internet sector. It’s good to see some finally realising that.

Service Seeking – new aussie eBay for services

I came across news that a new Aussie start-up, called Service Seeking, are launching today. Below is a summary:

The business is called Service Seeking (www.serviceseeking.com.au ). It’s an online market where people bid to do work for other people.

If you’ve got anything that needs to be done at home or around the office (eg a new website, some brochures or hire your next contractor), don’t waste time with the Yellow Pages. Post your project with Service Seeking.

It’ll cost you nothing, there’s no obligation to hire, providers chase you and bid against each other. Could be worth a try?

If you provide a service, then register. It will give you free access to new job leads. You only pay 5% for work which you win!

I’ve had a quick look of their site, and the interface seems pretty intuitive. They obviously haven’t got any activity yet, but their sample listings give an indication of the type of people they expect to use it: “I?¢‚Ǩ‚Ñ¢m moving: I need a cleaner“, “Business Cards & Stationary Print” (sic), “Furniture Removal“, “I want to get fit for Summer“, and “Legals for Property Sale“. The fact they are advertising on the domain.com.au network is a good indication that?Ç? they are targeting the housing market.
Similar to eBay’s reputation system there is also a mechanism to rate providors of services. Uniquely, it’s a score out of 100 and it is derived by people assessing them on quality of work, ability to keep to budget, ability to keep to schedule, communication style, and overall professionalism. This scoring system seems to be an important part of their business model, as they repeatedly make the case that its a way of getting business “without wasting time & money on marketing”.

The revenue model appears to be commission: service providers pay a 5% success fee on payments made.

It seems like a good idea. The Australian economy is 80% services, and the marketplace concept seemed to work for thousands of years as a way of commerce – I could certainly see myself using this service. However as a business model based on the network effect, they will thrive or flop depending on how they engage with the masses.

Making it free for the ‘demand side’ (the buyers) – you just place a request and someone approaches you for work – could be extended in a variety of ways and will be a key thing for it to take off. For example, partnership deals with major websites where people can post a request easily. Like any market, the demand side is is crucial – not enough people using it will make this a ghost town.

On the supply side, only charging when a payment is made means this is an outlet for free advertising, and should alone be a good incentive. However as I mention above, the key is engaging with the demand side – which they obvioualy are trying to do with their advertising campaign launching today.

The fact they are targetting the Australian market with a .au domain is both smart and stupid: smart because it plays on a competitive advantage that nationals of a country will use a business that is homegrown; stupid because it limits their business to the small Australian market. Nevertheless, for a small startup struggling for success, focusing on a niche market first is more important than playing for world domination. (And its not like service marketplaces is a totally new thing). But hey, with an Aussie economy worth?Ç? in exceed of?Ç? US$700 billion – if they can capture even only one percent of that, then that’s going to be happy days for them.