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Yesterday, the New York Times Public Editor Margaret Sullivan wrote a refreshingly honest piece about the 17 Hopes and Dreams for the Times in the New Year, and touched upon their desire to find “A brilliant new revenue scheme to capitalize on the popularity of mobile devices.”

News organizations need to help advertisers deliver more effective online ads.

These ads need to have higher click through rates, they need to be more engaging, and most importantly, they need to provide a NEW type of ad targeting that utilizes news organizations’ greatest strength: knowledge.

Most online ad networks target by demographics (age/sex/location/interests/etc) or by navigation behavior (retargeting ads).

There are enterprise advertising platforms like BlueKai that help you match up thousands of demographic profiles to more effectively target ads. There are simple retargeting tools like Adroll or Perfect Audience that have made it easy to buy retargeting ads and drive people back to a website. And of course advertising networks like Facebook have made data-mining an art with the ability to create custom lists, and fine-tune and target people based on a wide range of spending behavior, demographics, interests, and pretty much everything in between.

To date, there is no advertising platform that takes advantage of people’s “knowledge” and helps advertisers reach people based on the news they are digesting and the information they have recently acquired. 

Knowledge-based advertising is NOT the same thing as advertising that targets based on page-views. If someone loads a webpage, it’s likely that cookies are being immediately dropped on their computer. These cookies are used for tracking, they are used for analytics platforms, and for advertising platforms. The vast majority of these cookies (if not all) are fired on “page-load”– this means that the cookie can’t tell whether someone actually digested the content, but instead just says, “X person viewed Y page.” That process to cookie every visitor creates larger universes for ads, but it will also be lower quality and therefore less likely to be an optimized universe.

Knowledge-based advertising would create a new “metric” to determine when people have actually read an article. This could be done with some simple scrolling-based actions. If someone gets to location X on a page, the cookie will fire and the person will be tagged as having read Y article that includes tags/categories A, B, C.

If an advertiser KNOWS exactly what content someone has read, and content they read regularly, then they will have a much better way to serve up a unique ad with a customized value proposition.

Here are some examples based on content currently on the New York Times website:

  • Every time you review a website or an app, like this recent post, “Just for Laughs: Fake Mustaches and Cat Translations,” you could create a unique universe of the people who read it — and then everyone who creates fun/silly apps that are also buying advertising, could tap into that universe and try to find people who have recently become aware of fun apps for phones. These people are ready to install a fun app.
  • Or what about people who read a “Progressive” article like “States’ Minimum Wages Rise, Helping Millions of Workers” — everyone who reads this would be a great target for ads from organizations looking to raise money off successful minimum wage campaigns, or for organizations that focus on blue-collar politics. The article is the best funnel that an advertiser could hope for — someone just digested several hundred words, and likely came away from it feeling good about how raising the minimum wage “lifts all boats.” People are ready to support this idea. Why can’t we tap into their new-found knowledge?
  • If someone managed to read your epicly-long interview, “Anderson Cooper and Kathy Griffin Are Naughty and Nice” then they should immediately be served ads about AC360 or Kathy Griffins new show — you’ve either identified someone who was already an existing super-fan of these people, or someone who has a new-found knowledge (and likely respect) for both of these people. The universe of people who read the entire article is likely VERY small, but it’s also a highly-informed audience on a very-specific topic. This type of knowledge-based targeting is the future of smart ad segmentation.
  • There is literally an article about the best face cleaners for winter, “Seeking a Gentle Cleanser for a Harsh Winter.” If you created a unique universe of people who read this article, you would basically have a ad universe of people who likely have dry skin, who worry about their skin in the winter, and who are willing to buy and look for products to improve their body… not to mention the fact that these people are potentially actively looking for solutions.
  • The Year of Taylor Swift is another long article that could help advertisers target ads to a profitable demographic. Imagine if after someone viewed this ad, they were immediately served a banner ad, or an ad in a Facebook newsfeed that said, “Want to fill that Blank Space in your closet with designer shoes without designer costs? Check out our back-logged inventory from 2014!”

The options for knowledge-based advertising are endless.

The only limitations will come from how you create these “knowledge-based universes,” whether you try to outsource the process to one of your 3rd party advertising partners (or whether you take ownership of this ad network), when/how you fire the cookies to track people (instead of page-load, they are scroll/view/time-based), how you curate and grow these universes, how open and flexible your systemn is, and how easily that data can be used on existing 3rd party advertising platforms (Getting this network/knowledge-targeting on Facebook should be your priority).

It’s long overdue for news organizations to stop ignoring their greatest assets: information and content. 

News organizations need to flip the advertising model on its head — they shouldn’t be solely focused on how to get better ads on their own website and on their apps, they should be focused on how to more effectively monetize readers and viewers onto 3rd party platforms across the internet.

News organizations need to be dragged into the 21st century and decide whether they are players in the big-data game, or whether they are just spectators who use a bunch of 3rd party data apps.

If I were the CFO of the New York Times, i’d want to know how much money every month is being spent on the dozens of advertising platforms and trackers currently on the site — and how much revenue each of these trackers/platforms is taking on from their other clients. Big data is big business, and it’s time news organizations stepped up to the plate to become players in it.