Marketers never stop in developing new ways to match people to products that might interest them based on the things their peers like. For instance, market intelligence company Umbria
is developing "tribe analysis" software that finds patterns between buying behaviors across seemingly unrelated product categories.
The software will identify if people who own flat screen TVs also like hybrid cars. The probably with this thinking is that people's tastes are as unique as snowflakes, and that even if you can get a majority of folks to agree on two things, you will still be paying a premium for all of the people who disagree.
How many of your closest friends can you find with three things in common -- such as the car they drive, the place they like to visit most, and the type of ethnic food they like to eat? I bet it's not so easy, even if you went to the same school and are at similar age and income level.
Netflix has been running a contest offering $1 million to anyone who can develop a recommendation engine that does a better job than what Netflix currently does at predicting the movies that you would like. The Technology Evangelist
has interesting suggestion -- allow friends to recommend movies.
This would be a good PR move for Netflix and would encourage more renting of movies, but probably won't be an improvement over their current system for the reasons stated above. Spouses can't agree on movies that they like and even the best of friends diverge on interest in genres and affinity for individual films.
The answer is that marketers need to address the audience of one and personalize the ads based on the individual. An ad network such as Google or ValueClick should embed a thumbs up or down button into all of their ads, like TiVo offers. If you don't like the category of an ad (like dating services or SUVs), then you don't see those ads anymore. They could provide an incentive (say a $10 coupon at the merchant of your choice) in return tracking your data, which is protected.
It would be more effective to ask me what I like than trying to guess based on my age or a single purchase.