How can we solve the conflict between advertisers' need for more targeting and users' need for more privacy?
People probably realize that if they're online or use a mobile device, they're being tracked. But what most people probably don't realize is just how much data is being collected about them for the purpose of targeting ads at them. At some point users will rise up and defend themselves. At that point, what will advertisers do, when they no longer have the data for targeting or are no longer allowed to use the data they already have in such loose and unrestricted ways? Let's investigate.
Creepy Amounts of Data Are Being Collected
In the past, data about users were mainly collected by the sites they visited. The advent of browser toolbars and plug-ins allowed companies to collect data across any site that users visited. Then data sold by ISPs gave away user location and every site or web page they viewed even in "incognito" mode in their browsers. With social sharing buttons installed on millions of sites, every action of every user on every web page can be tracked, plus information about users' computers (OS, browser version, screen resolution and color depth, geo-location, etc.). And now, with public application programming interfaces (APIs), companies like Facebook reveal to advertisers users' social graphs (who they are connected with) and interest graphs (what they like or have shared). And if you read the fine print in smartphone app user agreements, you may see apps using user locations, accessing address books, and parsing call logs and text messages.
All of these data are in many ways more personal than "personally identifiable information" or PII - like name, mailing address, social security number, etc. - that advertisers swear they don't collect and use. But with the proliferation of user data and ways to collect it, advertisers have more data than ever before - we are firmly into the era of "big data."
Advertisers' Need for More Targeting Is at Odds With Users' Need for More Privacy
This data has given rise to sundry new forms of targeting that simply weren't even possible just a few years ago. For example, 1) behavioral targeting - targeting based on the series of sites a user visits; 2) search targeting - targeting based on the search terms the user types; 3) social targeting - targeting based on who your friends are and what they like, share, or talk about; and 4) reputation targeting - targeting based on your Klout or Kred scores in social media. The long list goes on. In fact, for years Google and Yahoo have been reading the contents of emails for the purpose of showing "relevant" ads to people. And Google's Chrome browser lets them track even the untrackable; and when users are logged in via Gmail, Chrome, or their Android device, every search, every web page, every bookmark, every preference, every social share, every GPS location, every conversation, every phone call (Google Voice), etc. is stored, ostensibly for the user's convenience.
Unfortunately, everyone knows that this additional data is being used in some way to target more ads at them. But is more and more targeting all what it's cracked up to be? Obviously some targeting is better than no targeting - ads for men's shaving products shouldn't be shown to women and ads for feminine hygiene products don't need to be shown to men. But is knowing a user's list of friends on Facebook or their tweets about having just gone to the bathroom really going to help advertisers better target ads at them? Probably not. That's the problem with targeting - it's a rudimentary guess at what people may want based on observations of other things like what sites they visited in the past. And while this used to work nicely - targeting a few parameters like gender, age range, geography, etc. - layering in hundreds of additional parameters is likely to be just an exercise in futility. And yes, a 1,000 percent lift in click-through rates of 0.001 percent is nothing to write home about.
What Should Advertisers Do When Users Fight Back?
What's more important, if we step back for a moment, is the question, "Where is 'the line'?" When will users finally say enough is enough and that they want greater control over their own information and how it's being used? Already we have seen a dramatic increase in the use of pop-up blockers, browser plug-ins that block ads, browser features that prevent third-party (ad server) cookies from being placed, etc. The Do Not Track initiative is analogous to offline measures such as the Do Not Call List. What happens if advertisers were no longer permitted to use this data for targeting or permitted to collect the various levels and kinds of data on more and more individuals?
Advertisers should start to reduce their dependence on this kind of "big data" that confers the mirage of doing more to better target ad messages at people. How should advertisers do this? This will come from changing the mindset of "targeting" from finding who to target with a message to "targeting" to ensure they can find the information they need, at the moment they need it, using whatever search term they choose to use, and on whatever device they happen to be using at that time. This shifts the thinking from a "push" mentality that advertisers have been used to for years to a "pull" mentality where the message and the content are designed to serve the information needs of the users - and are useful to them when they go out and look for it.
With this new mindset about targeting, big data and the collection of it will be seen in the proper light and the reliance on more and more data will be reduced - solving the conflict between advertisers' need for more targeting and users' need for more privacy.
Join the Industry's Leading eCommerce & Direct Marketing Experts in Chicago
ClickZ Live Chicago (Nov 3-6) will deliver over 50 sessions across 4 days and 10 individual tracks, including Data-Driven Marketing, Social, Mobile, Display, Search and Email. Check out the full agenda and register by Friday, Oct 3 to take advantage of Early Bird Rates!
Dr. Augustine Fou is the senior digital strategy advisor to CMOs, marketing executives, and global brands. Dr. Fou has over 15 years of Internet strategy consulting experience and is an expert in social media marketing strategy, data/analytics, and consumer insights, with specific knowledge in the consumer packaged goods, financial services/credit cards, food/beverage, retail/apparel, and pharmaceutical/healthcare sectors.
He is a frequent panelist, moderator, and keynote speaker at industry conferences. Dr. Fou is also an Adjunct Professor at NYU in the School for Continuing and Professional Studies and at Rutgers University at the Center for Management Development, where he teaches executive courses on digital strategy and integrated marketing.
Dr. Fou completed his PhD at MIT at the age of 23. He started his career with McKinsey & Company and previously served as SVP, digital strategy lead, McCann/MRM Worldwide and group chief digital officer of Omnicom's Healthcare Consultancy Group (HCG). He writes a blog "Rants, Raves about Digital Marketing" and can be found on Twitter at @acfou.
IBM Social Analytics: The Science Behind Social Media Marketing
80% of internet users say they prefer to connect with brands via Facebook. 65% of social media users say they use it to learn more about brands, products and services. Learn about how to find more about customers' attitudes, preferences and buying habits from what they say on social media channels.
An Introduction to Marketing Attribution: Selecting the Right Model for Search, Display & Social Advertising
If you're considering implementing a marketing attribution model to measure and optimize your programs, this paper is a great introduction. It also includes real-life tips from marketers who have successfully implemented attribution in their organizations.
October 23, 2014
1:00pm ET/10:00am PT