Personalization is hot these days, widely seen ([1] [2] [3] [4]) as a key battleground in the battle between Microsoft, Yahoo, and Google. But what is personalization?
I'd define web personalization as delivering different and unique content to each individual customer based on the customer's interests. It's your own version of the web site, a site just for you.
To distinguish personalization and customization, I would argue that personalization uses implicit interests and customization uses explicit interests. Personalization learns what you like from your actions; you are what you click on and what you buy. Customization requires you to explicitly specify what you want; you are what you say you are. My Yahoo is an example of customization. You tell the site what you want. Amazon.com is an example of personalization. The site learns your interests and adapts.
In a world with a glut of information, personalization offers a way to find focus. It doesn't waste your time showing you what everyone else sees. It learns what you like, shows you what you want to see, and filters out the rest. That's personalization.
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I think the key challenge is to provide a service that is an optimal mix of personalization and customization. We want the user to be able, but not have to, modify preferences to suit his current tastes. Since sometimes the underlying personalization model might be too simplistic.
Great point, Seun. A mix of customization and personalization can work well. Customization can allow users to correct mistaken guesses and assumptions by the personalization engine. It also gives power users the ability to tinker with the system. But it's important to realize that most people won't bother dealing with customization features, so they'll always only be applicable to a small percentage of your customers.
You make an interesting point, but let's be careful with our terms. From the examples you gave, asking a sales person for directions and a well organized room, I'd think the closest parallels would be search and categorized directories. Clearly, when someone knows what they want, it's important to get out of there way and let them find it.
But customization is not search and browse. Customization is manually specifying your individual interests to modify the way information is displayed on the site.
Given my definition, I don't agree that customization is merely an interface issue. The basic problem with customization is that it requires effort from the user. Users will not devote time to doing something that where the reward isn't obvious to them. Most will simply use the default.
Better interfaces may reduce the effort required and may be able to make the gain more obvious. But there will always be a large group of users, often the vast majority, who will not be willing to put in the effort.
We're certainly in agreement on the end goal. The holy grail would be an automated expert system that could converse on various topics in natural language. But a system capable of this, capable of the kind of dialogue you describe, is incredibly challenging and many years away.
You did mention that inference techniques aren't the way toward this goal and that the user should be able to explicitly state desires and get answers. I think it's important to realize how ambiguous natural language dialogues are.
For example, in the conversation example you gave, the automated sales person has to make a lot of guesses about what the customer wants. Does "looking" mean that they want to buy a camera? Or that they lost a camera? Seems obvious to you, perhaps, but the only reason it's obvious is that you're applying knowledge to determine the meaning of the word from the context. Does "model" refer back to camera? What does "model" mean in this context? Does "help" refer back to "looking for a digital camera"? What would be most helpful? What information is necessary for this decision? What are the customer's goals? How can I match my information about various cameras to best satisfy (my wild guess at) the customer's goals?
Everyday conversation is ambiguous. Nothing is explicit or fully specified. Meaning isn't clear, information is incomplete and noisy, goals are unknown, models of the world differ. Inference and assumptions are how we through our day.
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