“Do Not Track List” Implications for Web Analytics
The U.S. Federal Trade Commission’s recently released report about consumer privacy at first glance makes web analysts like me shudder. It says, not surprisingly, that some companies appear to treat consumer information “in an irresponsible or even reckless manner” and “do not adequately address consumer privacy interests”. The gist is that unless government steps in to corral the unfettered encroachment on individual privacy, consumers may become the hapless victims of “physical security, economic injury, and unwanted intrusions into their daily lives.” Talk of a creating a “do not track” list to protect consumers is underway both in the U.S. and now in Canada.
Assessing the performance of a website without some quantitative gauge of what people are doing (or not doing) makes it nearly impossible to know if the web channel is meeting the needs of users and the goals of the organization. I worried that the FTC’s proposed framework for protecting consumers would greatly impact any analyst’s ability to use quantitative tools to measure web performance.
But the FTC does put some common sense into their framework by allowing data collection for what they term “commonly accepted practices.” These include the obvious, such as collecting the address for shipment of a purchased product, fraud prevention, first-party marketing (the site you’re visiting offers you free shipping) and happily, collection about visits and click-throughs to improve customer service.
Mind you, quantitative or clickstream tools are only part of the analyst’s arsenal. Real insight comes with a myriad of inputs about user behaviours, be they on-page surveys (“did you find what you were looking for today?”), testing of different calls to action, or other methods that marry the what with the why with respect to how users interact with a Web site.
I agree with the FTC’s assertion that organizations should be more transparent about their data practices, which at a minimum includes publishing plain language policies explaining how individual data is used. The same policy considerations are needed in Canada, allowing both for privacy of Canadians’ personal information as well as recognition that Web performance data helps government, non-profits and for-profit organizations reach their audiences more effectively and efficiently.
Denise Eisner is a senior consultant within the Government Service Excellence practice.