He lists five reasons why personalized search is doomed:
People are not static; they have many fleeting and seasonal interests.The criticisms might be summarized as a claim that clickstream data is too dynamic, noisy, and sparse to support personalization.
The surfing data used for personalizing search is weak [compared to purchase data].
The user's decision to visit the page is based on the title
and brief excerpt (snippet) that are shown in the search results, not the whole page.
Home computers are often shared among family members.
Queries tend to be short.
There are two problems with this argument. First, Amazon.com's personalization works just fine from similar clickstream data. Sure, it's true that the data is dynamic, noisy, and sparse, but Amazon deals with that by using algorithms that adapt rapidly, are tolerant to errors, and work from very little data.
Second, personalization doesn't have to be perfect. It just has to be better than the alternative. In Amazon's case, the alternative to a personalized front page is a generic front page with a top sellers list or a bunch of marketing goo. It's easy to be more useful to shoppers than that. Mistakes are just fine. The guesses just need to be right more often than the alternative.
Personalized search is no different. The algorithms need to adapt rapidly, be tolerant to noise, and work from little data. Mistakes are fine. Personalized search just needs to be more useful than unpersonalized search.
See also my earlier posts, "Perfect Search and the clickstream" and "Personalized search vs. clustering".
[Valdes-Perez paper via John Battelle]