Posts tagged as recommendations

What’s next for RSS?

Wednesday September 13th, 2006 in , , , , ,

There’s no doubt that RSS has had a significant impact on how people access and discover information on the web. But to most people the experience has been bittersweet. Sweet because we no longer have to visit sites that haven’t been updated with new content since our last visit. It helps us save time, and for a while it seemed a small yet noticeable step in the right direction for fighting the information overload most of us face every day.

As time passed, more and more websites proclaimed “we have a feed, add it!”, and so we did, thinking that this feed might be the one we couldn’t live without. There was something alluring about the promise of always staying informed and ahead of the game - we couldn’t help it and just had to click the shiny RSS button. Soon, the list of feeds had outgrown the height of the screen, spanning numerous categories. The once so comforting “3 unread items” had been replaced by numbers in the three digit range. RSS suddenly made it all too clear that we will never be able to read and comprehend all the content out there.

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Attention Brings Service Online

Scientists from the RAND Corporation have created this model to illustrate what a “home computer” could look like in the year 2004. However the needed technology will not be economically feasible for the average home. Also the scientists readily admit that the computer will require not yet invented technology to actually work, but 50 years from now scientific progress is expected to solve these problems. With the teletype interface and the Fortran language, the computer will be easy to use. — Popular Mechanics, 1954

June 2006, Internet World Stats reports that more than one billion people use the Internet. That’s one billion people looking to connect, be entertained, discover something new, even learn something. As a result, the Internet has fundamentally changed how some of the most basic human needs are met. The problem is that the principles on which our society is built no longer apply, including the laws of physics and many of the established economic models. It’s an entirely different animal and it’s called The Attention Economy. 

One important aspect of how this attention driven economy works is known as The Long Tail. Simply put, the long tail means that in terms of business, small is the new big since storage, shelf-space and distribution no longer factor into the equation. When the product range is broadened the sales generated from small names, for example in books and music, starts to add up and the volume of low popularity items exceeds the volume of high popularity items. One thing remains constant though, it’s still all about giving people what they want, and herein lies the challenge.

The challenge can be outlined as follows:

  1. Assume an almost infinitely broad selection of products
  2. Attention is the most precious resource that the user has - for this reason consider it extremely limited
  3. Present the user with the most relevant products in the shortest possible time, and a minimal amount of work required on their end.

I’ve been focusing on how we spend money on music and books, but variations of this challenge exist anywhere we spend attention. We chose the search engine that provides us with the best results, subscribe to the feeds that have the best chance of keeping using up to speed. Or at least we like to think that’s what we’re doing. We can never really know what’s out there, if we missed that one important thing that would have made all the difference.

Hi, I’ll have the Usual / What’s Good?

We’ve established that we all spend attention. The challenge ahead is to maximize the “return of attention”. Ideally, I want relevant products and information at my fingertips. Products that are a perfect match for me, information I can use and enjoy. How can we achieve this? Logic dictates that in order to do this better, the source of these products and information needs to know more about me - my likes and dislikes, what I’ve done previously. This is where attention data comes into play.

As a consumer you can think of attention data as the relationship you’ve established with the seller of the product in question. A premise for this kind of relationship is trust, but once established the experience becomes more enjoyable for you and more profitable for the seller. A few real-life examples of this includes:

  • The staff at your favorite restaurant - they come to know how you like to be seated, the kind of food and drink you like. As a result they will be able to recommend new dishes you’re likely to enjoy.
  • The bartender at the place you usually hang with your friends - lift a finger and she’ll respond with an ice-cold beer of your favorite brand. Tell her what flavors you like and she’ll suggest new drinks for you to try.
  • The same thing goes for the staff at movie theatres, record stores, bookstores, you name it. Basically anywhere they get to know you through your returned visits.

Amazon understands this, and has been hugely successful as a result. Their technology essentially serves the same purpose as the bookstore clerks do in the real world. The big difference is that their servers know about all books and all other customers. They’ve taken some of the service that people enjoy in the real world, and made it work on a large scale online.

The bottom line is that we are all uniquely special, and we enjoy being treated as such, online or not. The use of attention data will play an important role and shows great promise, but in order to succeed we need to strike a perfect balance between too little or too much data in terms of privacy. One thing is for sure:

The fight for attention has begun…

What is Attention Data?

Saturday August 19th, 2006 in , , ,

To answer this question let’s start with attention. Simply put, attention is time spent interacting with someone or something. Sounds pretty abstract, I know, but that’s kind of the idea. Let me give you a few examples of attention:

  • Talking to someone
  • Reading a book, listening to music or watching a movie
  • Taking a picture

Not that many years ago we did these activities by sitting or standing across each other, holding a piece of dead tree and finally by means of analog film that we would have to get developed.

Today, we can pretty much do the same things using video conferencing, webcams, e-books, ipods and digital cameras to name but a few. The big difference is that when you go digital it’s much easier and very valuable to keep track of what you pay attention to - this is in essence what attention data is all about:

Attention data is a digital record that describes the
time spent interacting with someone or something.

This means that attention data can pretty much cover anything we do that has some kind of digital footprint, including:

  • books - that I bought, read, recommended or wished for
  • movies and videos - that I saw at the cinema, own on DVD, streamed online etc.
  • music - CDs that I’ve bought and listened to, my playlists, radio etc.
  • games - that I own and play online
  • photos - that I took and how I browse my photo collection
  • websites and blogs - that I read, my bookmarks, blogrolls, rss and opml
  • events and places - calendar entries for concerts, meetups, vacations etc.
  • people in my social network - communities that I participate in, my contacts and friends lists, my subscriptions etc.

As you probably noticed, keeping records with this kind of data has major implications for consuming and discovering products, our social interactions online and last but not least identity and privacy.  

Using Attention to Create Value

How is value created using attention data? As I see it, there are at least six different flavors:

  • Personal value - improved user experience and productivity
  • Network value - use your network to learn and discover, build relationships and strengthen friendships
  • Enterprise value - optimize the use of available resources within the enterprise including people and their competencies
  • Community value - expand your social network and discover outside the limits of your existing social network
  • Consumer value - better customer service through personalization and recommendations
  • Global value - smarter search and better relevance in online search

As mentioned earlier in this post, attention data has a lot of implications that I will continue to write about - including a detailed look at the different kinds of value that attention data creates. In the mean time, your comments and thoughts are very much welcome. I’ll leave you with this to consider:

How are you creating value from your attention data?