I have spent an inordinate amount of time helping clients understand the difference between “unique visitors” and “people” when it comes to measuring web site audiences. The “unique visitor” metric comes from web analytics and is defined in terms of browser cookies. The “people” metric comes from IP/panel data (like Quantcast) and is typically an estimate based on a representative audience sample. Neither metrics actually represent a person, like you or me or the people we interact with in real life (irl) every day.
The “unique visitor” metric is expected to be greater than the number of “irl people,” or customers that access your sites, and the “people” metric varies according to how representative the sample is of your audience.
If only there was a way to tell how many “irl people” are visiting sites.
Universal Analytics (UA) from Google moves us one step closer to being able to have the “irl people” metric and associated insights.
As the prevalence of multi-device browsing grows, brands are investing in mobile experiences in addition to web ones. But are they reaching the same customer twice – once on the web site and again on mobile? Or are they reaching a new audience on their mobile properties that they weren’t reaching before because they only had a website? Are customers converting at a higher rate thanks to being able to have a mobile touchpoint with the brand instead of just a web one?
Many web analytics tools let you capture the User-IDs for logged-in visits in a variable, but the reporting effort needed to answer questions about the impact of cross-device browsing is clunky since the measurement protocols are cookie based, rather than customer based. The measurement protocol for UA is designed around the User-ID, so once you start tracking that information, associated activity is attributed to one visitor in the reports – one “irl person.”
The seamlessness of the solution provided by the new measurement protocol in UA means clunky work-arounds – like having to adjust unique visitor numbers by the number of times a User-ID shows up in visits reports, are obsolete.
Battle scars gained from explaining the difference between “unique visitors” and “people” have made me shy away from reporting on those metrics and made me recommend that analysts focus on discrete sessions which are better captured in cookie-based web analytics tools. Now, with UA, I am excited to see analysts putting the “irl people,” the customers, back into their analyses.
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