The headline says it all: “It’s 2015 – You’d Think We’d Have Figured Out How to Measure Web Traffic By Now.”
ComScore was one of the first businesses to take the approach Nielsen uses for TV and apply it to the Web. Nielsen comes up with TV ratings by tracking the viewing habits of its panel — those Nielsen families — and taking them as stand-ins for the population at large. Sometimes they track people with boxes that report what people watch; sometimes they mail them TV-watching diaries to fill out. ComScore gets people to install the comScore tracker onto their computers and then does the same thing.
Nielsen gets by with a panel of about 50,000 people as stand-ins for the entire American TV market. ComScore uses a panel of about 225,000 people4 to create their monthly Media Metrix numbers, Chasin said — the numbers have to be much higher because Internet usage is so much more particular to each user. The results are just estimates, but at least comScore knows basic demographic data about the people on its panel, and, crucial in the cookie economy, knows that they are actually people.5
As Chasin noted, though, the game has changed. Mobile users are more difficult to wrangle into statistically significant panels for a basic technical reason: Mobile apps don’t continue running at full capacity in the background when not in use, so comScore can’t collect the constant usage data that it relies on for its PC panel. So when more and more users started going mobile, comScore decided to mix things up…
Each measurement company comes up with different numbers each month, because they all have different proprietary models, and the data gets more tenuous when they start to break it out into age brackets or household income or spending habits, almost all of which is user-reported. (And I can’t be the only person who intentionally lies, extravagantly, on every online survey that I come across.)…
And that’s assuming that real people are even visiting your site in the first place. A study published this year by a Web security company found that bots make up 56 percent of all traffic for larger websites, and up to 80 percent of all traffic for the mom-and-pop blogs out there. More than half of those bots are “good” bots, like the crawlers that Google uses to generate its search rankings, and are discounted from traffic number reports. But the rest are “bad” bots, many of which are designed to register as human users — that same report found that 22 percent of Web traffic was made up of these “impersonator” bots.
This is an interesting data problem to solve with multiple interested parties from measurement firms, website owners, people who create search engines, and perhaps, most important of all, advertisers who want to quantify exactly which advertisements are seen and by whom. And the goalposts keep moving: new technologies like mobile devices change how visits are tracked and measured.
How long until we get an official number from the reputable organization? Could some of these measurement groups and techniques merge – consolidation to cut costs seems to be popular in the business world these days. In the end, it might not be good measurement that wins out but rather which companies can throw their weight around most effectively to eliminate their competition.