Archive | Behavioral Analytics

State of Behavioral Targeting in B2B Media

In my most recent benchmarking project, I asked a series of B2B digital media brands if they had a behavioral database that the editorial, audience development and sales could use. All of them responded “no,” which means they are not able to operationalize behavioral targeting. This was surprising, as behavioral databases are required to answer such questions as: Which audience members read the latest news on a particular topic? What news is the most popular for which audience members? Which audience members read a vendor guide or some other directory? Which audience members are researching information on a specific type of product? Answering these questions allows media companies to behaviorally target editorial that drives audience engagement, to behaviorally target metering […]

How Many Audiences Can You Measure?

Building on our original findings in 2010 about audience loyalty, scout® research has been looking into what creates loyalty. Understanding the nature of loyalty, would obviously allow a publisher to nurture and grow the audience. For instance, is a fan a fan because she reads all the homepage articles? Or is she a fan because of a certain section of content? So what did we find out? Site-wide fans typically make up 20-30% of the visitors. Site-wide fans are the ones with a broad reading habit. Think of them as the cover-to-cover reader. In contrast when you analyze most fans’ behavior to figure out what they are a “fans of”, it is typical to find an individual fan has an […]

How Visit Data Provenance Impacts Publisher Revenue

Posted by: Matt Shanahan In my previous post, the lack of provenance for visit data was described as a big hole in web analytics tools such as Google Analytics and Yahoo! Web Analytics. Provenance allows a publisher to enrich visit data with information from circulation, CRM, or other databases. Provenance also enables visitor analysis to identify patterns in behavior. These two capabilities help publishers maximize the lifetime value of visitors with improved targeting and prediction. Improved targeting comes from visit data enrichment. The easiest way to increase the potential pool of advertisers, is to create more targeted segments. Visit data enrichment allows publishers to slice and dice their impression inventory in smaller chunks. The smaller and more targeted the chunks, the more […]

Provenance Missing from Web Analytics

Posted by: Matt Shanahan Provenance is one of the big holes in web analytics today. Reporting and manipulating visit data based on the source that generated the visit data isn’t exposed. Some vendors offer expensive data mart add-ons to patch the hole, but this creates more headaches. Consequently, the ability to understand individual visitor behavior isn’t possible with web analytics such as Omniture SiteCatalyst, Google Analytics, Webtrends Analytics, and others. Surprisingly, very few publishers are aware of this limitation and its impact on the revenue model. For publishers, the lack of provenance puts real operational limits on monetizing subscribers or audience members. I’ll cover these limitation in my next post. This post looks mainly at the technical side. So what is provenance? […]