Archive | February, 2010

Finding Meaning in Engagement Metrics

Posted by: Matt Shanahan I am never surprised when someone says they measure subscriber loyalty only to learn they are really measuring engagement.  How and why a subscriber engages can be a loyalty driver, and understanding these drivers can help paid-content providers create loyalty programs. When it comes to measuring engagement, it’s hard to argue with the approach of measuring everything.  The incremental cost of collecting three or three-dozen quantitative measures is negligible. Why not have duration and frequency of visit, click-through rate, bookmark data, RSS subscriptions, downloads and blog comments metrics available at your fingertips? My view gets a bit more controversial when we start talking about how to derive meaning from all the engagement data points that are collected. The […]

Demand Ratings™ Done Right Part 2 — Device, Biometric and Network Signatures

Posted by: Pete Horadan So I’ve laid the foundation for the idea of unique signatures, now let’s look at them in more detail. On the access side, we start by creating a Device Signature for each machine that accesses an application. We track over 80 unique attributes of the machine, and utilize a proprietary statistical method for understanding the patterns and the evolution of change to the patter for a given machine. Using this approach, we can tell with great accuracy, which machines accessing a system are unique and create associations between devices and visitors. Another of our algorithms—keystroke dynamics—can actually get to the individual level if required.  Keystroke dynamics works in conjunction with our Device Signature, analyzing visitor-specific typing […]

Demand Ratings™ Done Right Part 1 — Signature Algorithms

Posted by: Pete Horadan I talked earlier about the insufficiencies of current tracking approaches and their impact on behavioral analytics.  Let’s now talk about how it should be done—how we do it here at Scout Analytics.  Basically, our technology is centered around a unique signature concept.  We analyze dozens of unique attributes and utilize patent-pending algorithms to derive a unique signature for the device, network, even the individual user (biometric).  You can think of signatures sort of like a genome—while there are overlapping characteristics—each carries a unique and identifiable pattern and sequence. Of course, this isn’t easy or everyone would be doing it.  As you can imagine, machines, networks and even people change in different environments and over time—you install […]

Online Metrics Done Wrong Part 2 — Tracking IP Addresses

Posted by: Pete Horadan Last week, we looked at the serious acurracy issues associated with using cookies to track visitor behavior and engagement.  This week we’ll explore the accuracy of another often-used factor, IP address. In short, IP address provides even less information about users than a cookie.  The accuracy issue starts with the fact that one user may have many IP addresses.   For an example, let’s look at me. I access different sites (e.g., TechCrunch) from home through my personal broadband, while at my coffeehouse through their broadband, or through the network at my corporate office. When I’m on the road, I broaden my access points to include hotels and airports. When using IP address to count visitors, the […]