By Larry Marsh, Kansas City Star Midwest Voices columnist 2009
The individualized newspaper (aka "Daily Me") that caters to each reader's personal preferences is coming soon. The Google News approach of allowing each reader to customize the display by selecting topics or phrases is not adequate for a newspaper's long term survival.
Until the 1940s economists thought that the only way to determine a person's precise preference map was to ask them their preferences. This proved to produce a very imprecise and inaccurate preference map. When his Harvard economics professor explained that this was unfortunately the only viable approach, graduate student Paul Samuelson claimed to have a better way. He called his new method "revealed preference." Samuelson went on to become an MIT professor and Nobel Prize laureate in economics.
Proving your professor wrong has become a time honored tradition, but proving Google News wrong may take a bit more explaining. The key to the success of revealed preference is that it focuses on what a person actually does and not on what they say they want or expect to do. If you ask me what I like to do, I would tell you that I like snow skiing in the winter and water skiing in the summer. If you observe my behavior, I hardly ever do either. Cake and ice cream sound great, but I'd be a lot heavier if I went that route.
Behavioral targeting is essential to giving readers what they really want. As an economist I don't care what you say, I just want to see what you actually purchase with your money. With online news time is money. You reveal your news preferences when you reveal what you spend your time reading.
It's not that Google News is actually totally wrong but that its approach up to now is just totally inadequate. A much better approach is Amazon's collaborative filter method. Following Amazon's approach to book recommendations, newspapers could suggest news and commentary by first observing what a particular reader rates highly. Then suggest other news and commentary based on what other readers with similar tastes have enjoyed.
Neflix has used this approach to offering its customers movie recommendations. In the fall of 2006 Netflix CEO Reed Hastings offered a million dollars to anyone who could improve Netflix's recommendation system by 10 percent. On Monday September 21, 2009 a group of 7 scientists and engineers won the prize in a competition with 51,000 contestants from 186 countries.
Of course Google's famous search technology uses some ideas along this line. However, Google has yet to apply these methods to create an individualized "Daily Me" display of news and commentary in Google News. Hopefully they are already planning to apply these methods in the future.
In the long run online newspapers will not be profitable if they don't understand the difference between what readers say they want and what they really want. Asking a reader's preferences may be a good first step, but it is not sufficient. A newspaper that is serious about surviving online must go further and observe where the readers really spend their time, and ultimately, their online money. Newspapers that ignore the need for online behavioral targeting will themselves ultimately be ignored.
There is a dark side to all this. Traditional newspapers expose a reader to a wide variety of news and commentary. Readers who focus on their own narrow interests may become uninformed voters and poor citizens. If readers concentrate their interests and only see and read what they really want, they may become like the professor becoming increasingly specialized in his or her field who learns more and more about less and less until they know everything about nothing.
After writing this I discovered that there is already a "Daily Me" located at dailyme.com. See comment from dailyme below.
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In the past few years, newspaper business has slowed, as almost everyone is craze on reading articles online. Newspapers ad revenue has been declining over the last few years thanks to online classifieds, and if news can be gotten online – why subscribe? Finding a sense of place online instead of trying to resuscitate a massive print subscription roster is crucial – making money online through ads or paid membership might help newspapers that have gone online, the same going for magazines that suffered the same fate. Magazines and newspapers that have gone online have to find a way so customers can justify giving them payday cash advances for their service.
The DailyMe already exists and does exactly as you propose
The analogy you make is right on point and much needed. For general news media to survive, publishers need to communicate with their audience at an individual level.
My company DailyMe has been developing news personalization and recommendation technology since 2006.
Our first experience with personalization was declarative: ask users what they want and get it for them. We found out there were three significant challenges: 1. Only a small portion of users will invest the time and energy; 2. Very few people know what they're actually looking for (the news experience as we know it is largely serendipitous); and 3. People interests change very frequently thus making the profiles decay very quickly.
Using the same principles as Netflix, Amazon and iTunes, DailyMe built the first dynamic news personalization engine. It's called Newstogram and you may see it at work in our portal: www.dailyme.com. Notice that, after clicking on 4 stories, the page will change and present news that are presumed interesting for you.
At all times you can view how the system interprets your pattern by clicking on the "My Newstogram" link. And you can also make explicit choices by clicking on the link "Add Content".
I invite you to review our application and we would welcome learning about your experience.
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