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c h a p t e r6 :SOCIAL ANALYTICS, METRICS, AND MEASUREMENT■insights and that show you how to tie actions and results to your business objectives.
Again, the key insight in measurement is taking the time to understand how relatively
simple measurements can be combined, trended, and reinterpreted to provide useful
information. This means that it is important, especially in the early stages of any social
business program, to measure aggressively. Measure everything you can. Sure, you may
end up discontinuing the collection of some items, but you will surely discover others
that are surrogates or even direct indicators that provide the data you need to make
sense of newer Social Web-based consumer behaviors.
Consider a metric like bounce rate, the relative measure of visitors who land on
your site and then leave immediately, without looking at anything else. Dig into bounce
rate, slice it by source, slice it by date, trend it over time, and run correlation analysis
against it. What’s driving it? Do adjacent trends in blog activity or conversations on
Twitter correlate strongly with the trends in bounce rate that you observe? These are the
questions you really want to answer, because when you know what is driving your bounce
rate rather than knowing only the number itself, you can actually develop a plan to reduce
it—or to understand why further reduction has a diminishing economic payback.Avinash Kaushik: Web Analytics
Author of Web Analytics: An Hour a Day (Sybex, 2007) and Web Analytics 2.0 (Sybex, 2009),
Avinash Kaushik publishes the blog Occam’s Razor. You can follow Avinash on Twitter (@avi-
nashkaushik) and read his blog here:
http://www.kaushik.net/Connect the Dots
Moving beyond the basics of data collection is the difference between “12 people vis-
ited last week, up from 8 the week before” and “qualifi ed visitors to our site increased
following the release of the latest podcast program.” Counting visitors is important,
no doubt about it. Studying the ways in which people traverse your site, for example,
before they choose to make an actual purchase gives you a way to spot “qualifi ed” visi-
tors earlier in the process and thereby the ability to implement specifi c practices that
drive these conversions further. Connecting the next step—connecting the changes
in qualifi ed traffi c to specifi c Social Web-based programs—enables another level of
understanding. This is, of course, the path to understanding ROI, and in the larger
sense being able to make the case across your organization for meaningful spending on
social business efforts.
It’s all about connecting the dots. Like the silos that exist inside organizations,
data that is collected in isolation is less useful than data that is connected and thereby
refl ects holistically across processes. This leads to the larger question of “How are webAvinash Kaushik: Web Analytics
Author of Web Analytics: An Hour a DayWeb Analytics: An Hour a DayWeb Analytics: An Hour a Day (Sybex, 2007) and (Sybex, 2007) and Web Analytics 2.0 (Sybex, 2009),
Avinash Kaushik publishes the blog Occam’s Razor. You can follow Avinash on Twitter (@avi-
nashkaushik) and read his blog here:
http://www.kaushik.net/