When I heard about the FCC fining Snapchat for essentially lying to users about how they deleted images, when in fact they hadn’t, I could hear the sucking sound of all the trust going out the window. Being in the business of data analytics means we have to take data ethics seriously. As more and more companies use data to analyze and predict customer behavior for marketing and relationship building, we need to provide open and clear communication about how data is being used and how it is being secured.
As a marketer, I understand that it’s not a coincidence that I see ads for Birkenstocks show up in my Facebook newstream after a quick browse at Zappos. It’s my data shadow following me around the Internet. I’m being targeted and re-targeted based on my history, my likes, and my associations. God only knows what my cookies are doing.
I’ve pondered my data shadow, my meta-me floating around out there, and what it looks like. My hobbies and fashion sense. My political leanings. My finances. My health concerns (oh yes, I am a hypochondriac who regularly consults Dr. Google). My musical tastes…Everything. My data shadow is a pretty good composite pixilation of my persona. It probably contains more about me than my husband even knows! But who is “It”? It is not one entity.
I know some people (you know who you are) who use Google and browse the web anonymously so they leave no shadow, but most of us just browse, search, and click away with only a mild wariness of what is happening on the other side of the screen. Of course, this is a hotbed of controversy now that more people are getting to know more about data brokers and privacy rights.
We are becoming more accustomed to our data, for sure, and the rise of Personal Analytics shows that data can be downright addictive. I fell on the floor laughing over this recent article in the New Yorker by David Sedaris, one of my favorite writers. Confessing to his FitBit obsession, Sedaris perfectly demonstrates why performance management works on a very personal level. This trend will continue to grow as more wearable tech and machine sensors enter the fray. We will want to analyze everything, which is what makes big data analytics a huge market and opportunity for innovation, disruption, and change.
We’d like to believe that our data would not be used against us – in discriminatory or other nefarious ways. As consumers, we must be cautious and vigilant, but not paranoid. As custodians of our customers’ and citizens’ trust, we must show value from the data we collect in concrete ways, for example:
- More relevant communications. (Don’t send me a 15-pound pile of catalogs on kid’s furniture and outdoor gardening when I live in an apartment and have no children. This. Just. Happened.)
- Better engineered and higher quality products. (Do institute feedback loops from social media analytics straight back to quality control and customer service.)
- Safer streets. (Do perform predictive analytics with data blended from internal police sources plus third-party and social data streams to pinpoint likely eruptions of crime.)
- Better understanding of ourselves and better predictions for our future. (Don’t hog my data for your own purposes – let me see it so I can have another view of my finances, health, and behavior.)
- More convenience. (Do remember what I like and don’t make me repeat it over and over when I want to do business with you.)
- Less fraud. (Do use advanced analytics to pinpoint fraudulent activity to help keep criminals at bay and reduce waste.)
We have a real opportunity to do good and even amazing things with data, and we have a responsibility to keep the trust of our customers and the public. This requires respect of privacy, and 100% transparency about how we collect, store, and use data.
If you’re responsible for looking after data in your department or organization, download this white paper for a nice overview of data management strategy: Data Stewardship in Complex and Big Data Environments.