Ad blocking metrics are not monolithic, nor are publishers' ad targeting strategies. Looking at top-line ad blocking numbers obscures the underlying dynamics of who's blocking what.
Mezzobit offers publishers the ability to detect ad blocking on their websites and route this data to their in-house analytics systems, such as Google Analytics, Piwik, and Adobe SiteCatalyst.
These platforms already have existing data and reports pertaining to a wide range of user behavior and audience segments. Coupled with your analytics teams's deep proficiency with these tools, this permits publishers to quickly examine how blocking correlates with a variety of audience characteristics, such as geography, referrer, content consumed, and platform. Having this data in a centralized location also empowers publishers to federate it with other systems, such as ad serving, data management and supply-side platforms.
The end game of these analytics is for publishers to develop response strategies to begin recovering some of the revenue lost to ad blocking. Mezzobit offers the industry's widest array of choices, including serving alternate ads, changing editorial content presentation, hard and soft intercepts, and A/B testing.
This article discusses how Mezzobit structures the ad-blocking data and particular reports that can provide insight into blocking behaviors. As part of a free ad-blocking analytics trial, Mezzobit will perform much of the analysis described in this article, but many publishers may wish to take a deeper dive themselves. As the most widely used metrics package among publishers, Google Analytics is used to demonstrate examples, but the concepts are very similar to Adobe SiteCatalyst and Piwik. Before discussing the specifics of ad-blocking reporting, an overview is provided regarding event analytics.
Events describe how users and their technology interact with the web page, such as navigating content and clicking on controls. Most analytics platforms have a long list of standard events that they track and most also support the inclusion of custom-defined events.
Events typically have a hierarchical structure. For instance, there may be a broad class of events that involve a user's interaction with video content, with subcategories being editorial content and advertising. Beneath that could be specific actions that the user takes, such as hitting the play button, adjusting the volume, pausing the video and so on.
Below is the generic events structure from Google Analytics, with categories forming the top level and labels forming the bottom. More advanced analytics platforms often have deeper levels of parent-child relationships.
The hierarchical structure not only permits analytics users to drill deeper into events, but also enables fine-grained cross-comparisons with non-event data. You may want to understand how newsletter sign-ups vary by platform (desktop vs. smartphone vs. tablet) or ad interaction differs by referrer type (social vs. search vs. organic).
For ad blocking, Mezzobit has two category trees: page-level ad blocking (which is currently available) and ad-unit blocking (which will be added soon).
Page-level ad blocking detection looks at the entire page without regard to the individual elements. Coming soon will be label-level options that break down the type of blocker detected, when possible. These stats would provide an overall view of ad blocking across the site with an eye towards user technology.
The ad-unit blocking category tree starts at one level beneath by examining all of the ad units on the site in question, as named in their slot definition (for Google Publisher Tags). On the label level will be what percentage of the units detected were subject to blocking and which rendered. For premium Mezzobit customers, there also would be the option of a DFP interface to report upon other ad metadata.
Basic event reporting
Google Analytics event reporting can be found under the Behavior menu. There are four dedicated reports available:
- Overview lets you browse event categories, actions and labels for the specified time period.
- Top Events lets the user sort by the categories, actions and labels with higher frequency.
- Pages provides a page or page title view of the same data.
- Events Flow provides a sequential graphic of how one event leads to another.
Also, events can be viewed from the Events submenu under the Real-Time dashboard. This permits a rolling 30-minute window of user activity with respect to events.
Events also show up throughout Google Analytics as a secondary dimension on many reports. By adding an event category, action or label, users can insert a column with that label and show values superimposed upon other metrics such as pageviews, user attributes, and traffic acquisition.
Understanding that X% of all users have ad-blocking enabled or Y% of all ads are blocked only provides the highest level of intelligence about the problem.
Publishers need to correlate the value of users, as well as their acquisition cost, with ad-blocking to understanding the true impact. It may be that ad blocking is concentrated among hard-to-monetize users (such as those outside geographic ad target areas) or among users with already low sessions stats. Furthermore, if publishers hope to recover lost ad impressions, they need to develop strategies that are keyed to visitor segments and not monolithic audiences.
Here are some event-based GA reports that publishers may find insightful regarding formulating an ad-blocking strategy. The suggested menu path to each report is shown in parentheses however you can add the event for "Detected" to various reports in different ways so this is just one way of accessing the info. Just look in the secondary dimensions tab for Event Action.
- Country (Behavior -> Event Overview -> Event Action -> Detected -> Add Secondary Dimension "Country"): This will let you determine if a high percentage of traffic is blocking ads in valuable Geos you sell into.
- Browser (Behavior -> Event Overview -> Event Action -> Detected -> Add Secondary Dimension "Browser"): This will help you determine if a specific browser has a disproportionate amount of ad blocking.
- Device Category (Behavior -> Event Overview -> Event Action -> Detected -> Add Secondary Dimension "Device Category"): This will let you see the percentage of ad block detected traffic which was mobile.
- Days Since Last Session (Behavior -> Event Overview -> Event Action -> Detected -> Add Secondary Dimension "Days Since Last Session") This is a great way to see if the ad blocking traffic you are receiving is from loyal users or from single page view incoming referrals.
- Mobile Device Name/Model (Audience -> Mobile -> Devices -> Add Secondary Dimension for Event Action): This will let you determine if there is a disproportionate amount of ad blocking happening on a specific device which could hurt a targeted campaigns performance.
- Session Duration (Audience -> Behavior -> Engagement -> Add Secondary Dimension for Event Action): This will allow you to determine the value of users who ad block based on their engagement.
- Source (Acquisition -> All Traffic -> Source/Medium -> Add Secondary Dimension for Event Action): This will show you the sources which drive higher amounts of ad blocking traffic.
- Social Network (Acquisition -> Social -> Overview -> Add Secondary Dimension for Event Action): This will let you determine which social networks tend to send you higher amounts of ad blocking traffic.