Accurately measuring ad blocking rates

Ad blocking, and content blocking in general, is a major topic of discussion in the industry right now, and many are struggling to formulate a response tailored to their particular websites and their users. Although worldwide users' interest has been growing for years (see Google Trends), it is not yet clear what a compromise that caters to the needs of users, website publishers, and advertisers would look like.

ublock Origin blocking report in Firefox

Regardless of the wider industry debate (more on that below), ad and content blocking are here to stay, and you need to define a response suitable for your website and your users. To start, you need to measure the percentage of your users who use content blockers.

Although there are many demographic- or industry-wide reports on ad blocking rates, not many robust ways to measure accurately the percentage of users on a given website who block ads have been documented.

Many of the published methods rely on using existing analytics trackers, like Google Analytics or Omniture. However, some popular blockers, like Ghostery and uBlock Origin, block popular analytics packages as well as ads by default, and others can be configured to do so too. This means you are likely not measuring what you think you are measuring if you use existing analytics to measure ad blocking.

The solution

The solution is to spin up your own analytics infrastructure. (In another blog post we will talk about why this should be a strategic investment for all sites and apps in 2016). For just measuring ad blocking, you only need something very lightweight. In this post, we will sketch out a simplified version of a technique we've been developing, which we've tested with uBlock, uBlock Origin, Ghostery, Disconnect, and Firefox private browsing mode with the new Tracking Protection.

The core of the technique requires two analytics URLs:

To test your configuration, enable one ad blocking extension at a time and visit the test page (ideally using a fresh incognito mode browser window every time). The control URL should be pinged but the creative ping URL would not.

This configuration generates raw data, and allows you to get a rough estimate of the ad blocking rate. However, this number is likely to be misleading without further enhancements. Here are general tips and thoughts for production use:

We can help if you are stuck.

Why you need a strategy for handling ad blocking

Let's take a step back and survey the industry debate. As noted, these ad and content blockers have been around for years. The discussion took a new urgency earlier this year when Apple announced that Safari on iOS 9 would support content blocking. With content blocking pushed into the mainstream, the industry reacted:

Unsurprisingly, variations of the word "ethical" come up often (e.g. BBC in 2013, Washington Post, Marco Arment).

But before you decide what is the best response for your site and users, you need to measure the current, baseline, blocking rate, and continue to measure it going forward. You also need user and business research to find the right response. If you need help with any of these topics specific to your website, please get in touch.