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The Backlash of the Crowds: An Orbitz Analytics Case Study

Resource Logo Resource , Building Open Brands Jul. 6, 2012

It’s been fascinating to watch the brouhaha over Orbitz’s recent admission that Mac users are presented with a different—and pricier—set of hotel options than PC users who visit their site. The lead in the article from the WSJ that broke the story was accurate:

Orbitz Worldwide Inc. has found that people who use Apple Inc.’s Mac computers spend as much as 30% more a night on hotels, so the online travel agency is starting to show them different, and sometimes       costlier, travel options than Windows visitors see.

The article went on to explain what Orbitz is doing and why. The explanation of the process from the article is an analyst’s dream: The company had an “intuition” about Mac users, and they used the data to confirm that intuition. In analytics-speak, they had a hypothesis, they failed to disprove it, and that led to action—they altered the content displayed to users based on their operating system! This seemed like a pretty clear win-win situation:

  • Consumers win: When they visit the site, they are presented with content that is likely to be more relevant to them based on the past behavior of other visitors with whom they shared a characteristic that was correlated to hotel preference.
  • Orbitz wins: Consumers get a better experience on their site based on the content targeting, so they convert at an incrementally higher rate than visitors who are not targeted based on their OS.

Within hours, Forbes.com posted their take on the news with a hefty dose of inflammatory drama in the headline: “Mac Users Have Money to Spare, Says Orbitz.”

By the time CNN covered the news the following day, “many people [had taken] to Twitter in a fury, saying that just because they shelled out money for a MacBook doesn’t mean they don’t want a good deal on a hotel.”

A few more days of social media flame-fanning, and we got to blog posts that made statements like, “And Orbitz, you just lost a lot of customers with that move.  I’m guessing every Mac user that reads about this will switch to another service, as they should.”

This incident is just the latest in a series of cautionary anecdotes for marketers. When it comes to combining social data with long-standing CRM strategies to achieve 1-to-1 marketing nirvana, we focus on the harried consumer’s desire to be presented with content and offers in which she might actually be interested:

But, consumers are leery of brands knowing them too well. Without consciously thinking of it as such, consumers sense a gray area between “targeting the anonymous me with relevant content and offers” and “knowing enough about me that you can nefariously manipulate my behavior:” As Andrew Pole, the data scientist at the center of the story earlier this year that recounted how Target knew a teenager was pregnant before her father did (and targeted their direct mail to her using that information), noted: “Even if you’re following the law, you can do things where people get queasy.”

In the Orbitz case, Orbitz was aiming for a win-win (at least for Orbitz and their customers). They intuited something along the lines of the following:

  1. The operating system (in general) tells us the computer platform of a visitor.
  2. Apple users pay a premium for their computers.
  3. Apple users (in general) have discretionary income and choose to spend it on things that satisfy them experientially or as a status symbol.
  4. People who have discretionary income and spend it on experiential or status-related purchases (in general) are likely to do the same when choosing a hotel.

They then tested the theory with data and found an easily detectable visitor characteristic (operating system) that correlated with a buying preference (higher-end hotel rooms). They put that finding into action.

But the social media/journalism/consumer feedback loop quickly morphed this rational behavior to be, instead, an attempt by Orbitz to gouge Mac users. Even though Orbitz both admitted what they were doing (transparency is good!) and assured the media that they were not changing prices, but, rather, targeting content, the company still wound up with something of a black eye. It’s a risky area—even if brands are being big sisters with the best of intentions, it is easy for their intentions to be morphed into a conviction in the Court of Social Media Opinion.

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