Building block for behavioral advertising: address the privacy concerns!

On Off Switch

How much user tracking is okay? This is a question marketers and advertisers face everyday.

Earlier this year, FTC revised its Online Behavioral Targeting Principles. The FTC report discusses the benefits of behavioral advertising to consumers, including the free online content that advertising generally supports, personalization that many consumers value and an enhanced user experience. It also discusses the privacy concerns that the practice raises, including the invisibility of the data collection to consumers and the risk that the information collected – including sensitive information regarding health, finances, or children – could fall into the wrong hands or be used for unanticipated purposes.

In the coming year, staff also will evaluate self-regulatory programs and will conduct investigations, where appropriate, to determine whether practices in this industry violate Section 5 of the FTC Act.

With increasing pressure from the FTC and the privacy advocates, advertisers will have no choice but to make tracking and storing of information more transparent to the users. Advertisers have to make it easier for consumers to opt out and select when and where they want their browsing habits to be stored.

Google made some advances in this area when they introduced the cookie opt-out plugin that permanently opts you out of the Doubleclick cookie.

Google Cookie Opt Out Plugin

There are 2 additional things that could be done to protect the user and also make the experience more relevant and personalized. My thoughts below:

  • User profile: In the browser, create a user profile with information on age, gender, location and interest categories. The interest categories can be a list of areas like travel, automobiles, dining, sports, entertainment etc that you are interested in. All this information is stored on the browser. Based on the demographic, geographical and interest category information, the advertisers can serve targeted ads for that particular cluster. This way, individual user information is never shared with the advertiser.
  • The Opt in/Opt out switch: Instead of putting the “clear cookies and browsing history” tabs somewhere in the tools section of the browser or on the Ad Preferences page page as done by Google, put it in front of the user. The “switch” can be included in the HTTP header or as a widget on the bottom right hand corner of the browser screen.
    The switch should be color coded to show you whether your browsing information is being stores or not. Green means information is being stored and the consumer will see relevant ads & personalized experience and Amber means that information is not getting stored and the consumer will not have a personalized experience.
    The feature is similar to the “Private Browsing” tab in either Safari or Firefox if you are a Mac user. As you open a new webpage in the same browsing session or open a new tab, the default setting is GREEN. If the consumer chooses AMBER, a message is displayed that your browsing history will no longer be saved and you may not see personalized content. If the consumer revisits the page, the previously chosen setting is maintained. The widget could show Green or Amber for different tabs within the same browser session based on preferences.

For behavioral advertising to have a future, it is important that privacy concerns are addressed.

What are your thoughts? How will the opt in/opt out widget affect behavioral advertising? What will be the reaction of behavioral ad targeting systems?

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Monetizing Social Networks- will attribution be the answer?

Continuing on the topic of monetizing social networks, one of the problems in the industry is last touch attribution.


If you think about the purchase funnel, it starts from brand awareness to favorability to intent to action. Display advertising, the main form of advertising on social networks, is very powerful in creating brand awareness and moving the consumer to a favorable stage.

Click or Search advertising plays a big role in converting those leads into intent and action.

If we only follow the last touch attribution model, then all the work done by social networks to create brand awareness and purchase intent is lost. An interesting read on this topic is the keynote address delivered by Gian Fulgoni, chairman and co-founder of comScore, at the MediaPost OMMA Metrics & Measurement conference.

A potential answer for CMOs to measure their display advertising ROI on social networks and see what is being fed into the sales channel is marketing mix modeling (MMM). MMM uses multivariate regression techniques to analyze the sales and marketing time series data: it looks at how the different ad sources (display, search, video etc) contribute towards making a sale.

I don’t think clicks are going away as a metric for ROI online. However, we will be shooting ourselves in the foot if we don’t look at cross channel synergies and impacts.

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