This week ReadWriteWeb is running a series of posts analyzing the 5 biggest Web trends of 2009. Our first post was about Structured Data, our second about The Real-Time Web. The third part of our series is on Personalization.

Personalization has long been a buzzword on the Internet. With the glut of information on the Web circa 2009, personalization in this era means providing effective filters and recommendations. Ultimately personalization is about web sites and services giving you what you want, when you want it. That's the long-standing dream anyway. Let's see if the products of 2009 are fulfilling it.

All of the trends that we're profiling overlap. This is particularly so with personalization, as we'll see.

Filtering the Real-Time Firehose

Personalization is often used to provide an organization layer for users on top of real-time data. As Ken Fromm put it in his primer on the Real-Time Web:

"The Internet is shifting from discrete units of websites and Web pages to discrete units of information [...] organized in ways that are relevant and personal to each individual, using data gleaned from social graphs as well as recommendation and personalization services that allow users to set their preferences."

If you use a dashboard product like TweetDeck, Seesmic or Peoplebrowsr to use Twitter, then you're able to group people, keywords and topics. This is effectively personalization at work.

Open Web: More Data About You, Better Personalization

Another aspect of personalization is the increasing prevalence of open data on the Web. A lot of companies make their data available on the Web via APIs, web services, and open data standards. And as we discussed in the first post in this series, much of that data is structured - allowing it to be inter-connected and re-used by third parties.

How does open data lead to personalization? Simply put, the more data about you and your social graph that is available to be used by applications, the better targeted the content and/or service will be to you. There are non-trivial privacy issues about this, however the personalization benefits can be significant.

There are a whole host of open data standards on the Web now. They include:

  • Data portability - taking your data and friends from one site to another.
  • OpenID - portable identity; single sign-on.
  • OpenSocial - Google initiative for social networks, enabling developers to create widgets with one set of code; MySpace a member, Facebook isn't.
  • APML - growing 'Attention' standard; Your Attention Data is all the information online about what you read, write, share and consume.

Recommendation Engines

Many consumer products on the Web aim to recommend you things that you may like. A couple of years ago, Alex Iskold outlined what he saw as the 4 main approaches to recommendations:

  • Personalized recommendation - recommend things based on the individual's past behavior
  • Social recommendation - recommend things based on the past behavior of similar users
  • Item recommendation - recommend things based on the item itself
  • A combination of the three approaches above

Amazon is probably still the best example of recommendations on the Web, but an example of something new from 2009 was Netflix launching better personalization features in March. They included new taste preferences, allowing users to (for example) choose between movies that are romantic, suspenseful, or dark. Other additions included a personalized homepage and a feature enabling users to mix and match genres.

Conclusion

Personalization has shown slow but steady progress in 2009. It hasn't been as wild a ride as Structured Data or Real-Time Web, but we consider personalization to be a key facet of the evolving Web.

ReadWriteWeb's Top 5 Web Trends of 2009:

  1. Structured Data
  2. The Real-Time Web
  3. Personalization
  4. Mobile Web & Augmented Reality
  5. Internet of Things

Image credit: davepatten