Apple has made their commitment to privacy very clear, and the company maintains a full microsite devoted to explaining its privacy policies. Now its data vs privacy as Apple is under pressure from the FBI to help unlock the iPhone of the San Bernardino terrorist, with the FBI director making a personal plea to the company for help.
The Apple question is surely fueling discussions this week at Mobile World Congress. Taking place in Barcelona, the show is the hot spot for mobile phone manufacturers and the technologies that support the industry. One of the show sessions, Putting Privacy at the Core of Digital, features leading experts from AVG Technologies, Facebook, Meeco, and Telfonica weighing in on the push-and-pull issues that are unique to the mobile industry. The use of customer data generated from devices, the balance of power between privacy controls offered by the provider and the true privacy of users, and the ever-present issue of third-party data. To keep services affordable for the consumer, manufacturers and developers are under great pressure to access more and more private data to sell to advertisers.
Data anonymization
Mobile phone manufacturers aren’t blind to the need for better privacy standards, so they will often implement data anonymization, a process that strips data of identifiable information so that, for instance, if the data is sold to a third-party for use in marketing, individual people could not be identified in the data set.
However, as reported by Wired in a story titled, Anonymized Phone Location Data Not So Anonymous, Researchers Find, researchers at MIT and the Universite Catholique de Louvain in Belgium who looked at 15 months’ worth of anonymized mobile phone data found that “it took very few pieces of data to uniquely identify 95 percent of the users” and trace activity to a specific individual.
As consumers gain more and more awareness of just how much of their personal data is available through their phone, pressure will mount for companies to show, as Apple does, that they have a strong commitment to protecting privacy.
Data and text classification: insights that respect privacy
There’s an easier way for many companies to get the answers they want about a certain population, and these answers can be attained without violating privacy.
If you have access to user generated content–for example, social posts, blogs, messages, or search queries–a comprehensive topic classifier can help you uncover and aggregate valuable information about what’s being said, while ignoring the details that betray the identity of the content’s author. What’s more valuable: learning that Danny in Spokane is thinking of getting a hoverboard, or that hoverboard enthusiasts show a distinctive interest in Samsung products and the website Mashable? As you look for the patterns of what a population or an audience is talking about, you can better understand what their passions are, and make informed decisions about how to market to them in the future – without having to scrape their profiles, track them with cookies, or follow their every move online.
eContext provides a complex and very useful framework for this kind of audience analysis. While some social listening tools can deliver similar insights, they are typically narrowly focused, rely heavily on one-by-one keyword contain searches, and barely scratch the surface with two or three tiers of classification offered for data. Consider Hillary Clinton’s media buying team. Right now, they’re trying to put together this summer’s ad budget, and mobile ads will be huge for them. They might want to find out what kind of sports Hillary Clinton’s followers are into so they can target ads at popular events during the summer. If the team uses a social listening tool to query a stream of social data, they will get some broad answers like “soccer” and “baseball”.
With eContext the team can pull that same data stream and combine it with any other available data they may have so that there is a larger corpus to query. We’re guessing Hillary’s team has a lot of data. eContext pulls all of their data, from any source, through its filter in real-time, and the result is deep classification of that data into a taxonomy that delves 21 tiers deep and delivers up to 450,000 categories. Now, Hillary’s team has some specific answers — They’ll get information on which football and baseball teams that Hillary Clinton supporters like best, so they can plan mobile campaigns more accurately, and share their findings with ground teams so that Hillary can show up at a few baseball games this summer where her supporters are. Knowing where your audience will be helps you know where the ads — and in this case, the candidate — should be.
And Hillary can do it without irking her audience by compromising their privacy. After all, nobody knows better than Hillary the sting you feel when perfect strangers go through your email for personal gain.
