Filed under: Gary Angel
By Gary Angel (@garyangel)
We’ve been involved in measuring Paywall issues for several different media/publishing sites lately. It’s an interesting set of problems and highlights some common weaknesses in Web analytics solutions as well as a few interesting workarounds that are applicable to a surprising range of problems extending beyond Paywall analysis.
Paywalls on media sites have gotten much more sophisticated these days. In most cases, sites choose to expose their entire content to the public but limit the amount consumed in a given time-period; this strategy is designed to protect Search Engine traffic and create a rich pre-Paywall experience.
So if you’re thinking about, planning or rolling out a Paywall on a site, one of the fundamental questions you have to answer is where to put the wall. The location of a Paywall is a business decision not an analytics decision, of course, but to decide the location of a wall there are a few things decision-makers typically want to know.
First, and most importantly, they need to understand the actual distribution of walled content consumption by visitor in a given period of time. If a Paywall is going to limit visitors to X pages in a week, how many visitors will it actually impact? What’s the potential loss in advertising revenue if those pages don’t get served? And how many visitors will actually have a strong incentive to go through the wall?