5 Data Fails in 2014

When it comes to data breaches, leaks and blunders, 2014 had more than its fair share. Many major brands took data-related hits that became PR nightmares, scrambling marketing departments into damage control mode as they tried to repair tarnished images.

In the spirit of learning from past mistakes so as not to repeat them, heres a look at some of last years standout data fails and what advertisers/marketers can do to avoid them.

1. Bank of Americas Whats in a name? Blunder

As reported last February in a Time.com article, Lisa McIntire, a feminist writer living in San Francisco received a credit card offer from Bank of America addressed to: Lisa is a Slut McIntire. In response to the mislabeled mail, McIntire told The Daily Intelligencer that the letter initially made me nervous because Im a feminist writer on the Internet. But I dont think its personal. Bank of America has yet to comment on the cause of the junk mail mistake.

The lesson for marketers who buy mailing list data from third parties for Big Data advertising purposes is to make sure that the data is clean and problem-free before launching campaigns.

2. Facebooks User Manipulation Scandal

Back in June of 2014, the journal Proceedings of the National Academy of Sciences of the United States of America published an article entitled, Experimental Evidence of Massive-Scale Emotional Contagion Through Social Networks. That same month, a Forbes expose revealed some disturbing details about the study, which, as it turns out was conducted by Facebook data scientists.

In the study, which took place back in 2012, Facebook researchers measured the psychological effects of positive and negative posts on over 700,000 users. According to Forbes, The short version is, Facebook has the ability to make you feel good or bad, just by tweaking what shows up in your news feed.

The takeaway for marketers is to never make your current and potential customers feel like lab rats.

3. Titans Phone Booth Beacon Bust

New York City has long been known as a hub for cutting edge advertising. No doubt the clever folks at Titan, an outdoor ad firm, counted on the Big Apples ad-friendly culture when they installed beacons—digital devices capable of broadcasting ad messages and offers to mobile devices—in 500 New York City phone booths. When the news of the clever ad scheme reached the office of Bill de Blasio, New York Citys Mayor, Titan was told in no uncertain terms to remove the beacons post haste.

For marketers familiar with the adage that Its better to ask for forgiveness than permission, Titans blunder suggests that the opposite approach may be the better way to go.

4. CNNs 110% Math Mistake

Scotlands independence referendum made big news last year, and CNN was there to report on the referendum as events unfolded. Using Big Data analytics to generate interactives and graphics during the live coverage, CNN suffered a data flub as one onscreen graphic showed that 58% of Scots had voted Yes to the referendum and 52% had said No. Adding up those two numbers, it seems that 110% of Scotlands population had voted, an impressive but impossible turnout. Faster than CNN news execs could say viral, the faulty graphic spread on social networks like wildfire. CNN quickly updated the graphic to show the correct numbers—52% No and 48% Yes—but by then it was too little too late.

What the erroneous CNN graphic correctly pointed out for marketers is that its critical to double check all data for accuracy before using it.

5. Sonys Data Breach

The Big Data fail in 2014 that made the biggest headlines was of course the hack executed on Sony Pictures. Resulting in massive leaks of personal employee data, embarrassing emails, celebrity contact information and the digital files of films yet to be released, the hack is a wake-up call to all organizations that operate under the false assumption that their sensitive data and information is safe and secure. For marketers, Sonys attempts to re-establish credibility demonstrate that strategies and scenarios designed to regain trust should be worked out before they are needed.

While the above is only a partial list of the many data fails that occurred in 2014, these examples should help advertisers/marketers avoid costly mistakes, many of which are preventable.