6 Pillars of the Right Time Web

In our haste to reach the Real-Time Web we forgot that it isn’t about how fast we receive information, it’s about receiving the right information at the right time. The next wave of the web will be centered around this premise.

The infant stages of the Right Time Web are here. Look at FourSquare, Gowalla, and Facebook. They are all building and leveraging the Right Time Web by customizing experiences based on our interests. For your web application to leverage the Right Time Web you need to be aware of the 6 pillars that encompass it. They are:

Personal Information

How old are you? What gender and race are you? Who your friends are?

Location / Time

Where are you now? What time of day is it?

Interests

What are your hobbies? What do you like to do?

Schedule

Where are you going? How much free time do you have?

Status

What are you doing right now? What do you need right now?

Wish Lists

What do you wish you owned? What do you want to learn or do?

What Makes a Web Application “Right Time”?

Right Time Web applications need to integrate 2 or more of these pillars. One is not enough.

For example, your interests can be combined with upcoming events and your schedule to notify you that on your upcoming vacation there’s a concert that you would enjoy attending.

Or, your wish list could be combined with your location to let you know the camera your want is on sale at the store you’re in.

There are hundreds of examples. What’s important is the accuracy of the information. Right Time web apps don’t spam. The noise is filtered out leaving you with just the information that you need at that point in time.

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  • Lateefivy

    One aspect worth considering is which of these pillars should be done by apps and which should be done by people. Computers are notoriously bad at pattern-matching unstructured and fluid data like “interests” and “what do you need right now”, but people are actually pretty good at that. We seek tools that leverage people's ability to pattern-match unstructured data with a computer's ability to manage messaging.

    @golateef

  • Lateefivy

    One aspect worth considering is which of these pillars should be done by apps and which should be done by people. Computers are notoriously bad at pattern-matching unstructured and fluid data like “interests” and “what do you need right now”, but people are actually pretty good at that. We seek tools that leverage people's ability to pattern-match unstructured data with a computer's ability to manage messaging.

    @golateef

  • http://www.marketingformavens.com Chris

    Agreed. We have to find ways to loosely structure the fluid data or build algorithms that can get us close to what humans can do. In many cases there isn't enough time for human intervention.

  • http://www.marketingformavens.com Chris

    Agreed. We have to find ways to loosely structure the fluid data or build algorithms that can get us close to what humans can do. In many cases there isn't enough time for human intervention.

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