Again, I would recommend reading the whole thing, but I here will focus on the parts on personalization.
In particular, there are a few tidbits on personalized advertising in this round of interviews. Some excerpts:
Chris Sherman: ... As they get to know you and your preferences, you know... "I never click on that video ad," they’ll gradually stop showing you [those] ads ... and maybe increase the ads ... that you do click on.The impression I got from this is that personalized advertising is now seen as inevitable. Privacy concerns may make it appear incrementally, but most seem to agree that it will happen.
Larry Cornett: ... The more they understand about what a specific user is looking for in their context, the more intelligent they can be about what they're actually offering ... By being more targeted it will add more value for the users and hopefully, be a better experience for them as well .... Do [users] really want to spend time in the context where they're seeing a lot of stuff that’s not targeted and not appropriate and might even be annoying or would they rather ... [see ads that] could be beneficial for them.
[Gord Hotchkiss:] Personalization of advertising will happen incrementally and the ability to target accurately will improve over time. For many users, it will be a mixed environment, with some very well targeted, relevant ads in some locations that don’t even look like advertising and the more typical forms of untargeted advertising we're more familiar with.
On a different topic, usability guru Jakob Nielsen used his time to promote NLP over personalization and pick on Amazon.com's recommendations yet again. Gord asked me to respond.
On the one hand, I agree with Jakob about the long-term promise of natural language techniques (though I think he may be underestimating the challenges and overestimating the likelihood of rapid progress there) and his criticism of inaccuracies in personalization and recommendations (and they are inaccurate, no doubt).
On the other hand, I think Jakob is using an absolute measure of the effectiveness of personalization where a relative measure is more appropriate. Specifically, the metric should not be how often does personalized content accurately reflect your interests; it should be how much better does personalized content predict your interests than whatever unpersonalized content you otherwise would have to put in the space.
That is a much lower bar. Bestsellers and other unpersonalized content tend to be very poor predictors of individual interest. By knowing even a little bit about you, it is easy to do better.
Is personalization ever going to be perfect? No, but it does not have to be. It just has to be more useful than the alternative. Personalized content only has to be marginally more interesting than unpersonalized content to be helpful.
See also Gord's first post in this series, "Search In The Year 2010", which has some more on personalized search, and my comments on that post.
For more on personalized advertising, please see also my posts "What to advertise when there is no commercial intent?" and "Is personalized advertising evil?"
1 comment:
I still don't see why the two (NLP and Personalization) are mutually exclusive.
Suppose I use NLP to differentiate between "books by children" and "books for children". Well, then personalization can still give me a better list of books by children, right?
So NLP and personalization can actually work together, it seems.
I think where the confusion may lie is in the fact that all the examples that industry gives for why personalization is so great center around word sense disambiguation. The financial analyst typing "bank" means something different than the river kayaker typing "bank".
That kinda misses the mark, IMHO. Word sense disambiguation is not using the power of personalization in the right way. So I can see how, if someone is using it for word sense disambiguation, you might prefer the NLP solution instead.
But personalization is more than that. It's the idea that, once you have disambiguated between money bank and river bank (even using NLP), you can give someone the best list of river banks... maybe something like river banks that allow for easy portage through particularly rough spots of water.. because you've notice, through search personalization, that a particular person prefers class 5 rivers.
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