Jul30

Numbers Don’t Lie—But They Could Be Trying to Tell You More

data tabletAn advantage of analytics that is often extolled or capitalized on is the sleek, easily consumed result at the end of miles and miles of data. It is an alluring power, to be sure, and the ability to see past the noise to extract core performance metrics is certainly foundational. Practically, however, these extractions may lull one into seemingly natural simplifications of data in order to provide neat, packaged numbers.

Analytics is not merely a mass of raw data; it is the underlying story being told by the data and it is the story that is meaningful. In essence, context imbues the easy and commonplace metrics we use and rely on with impact and meaning. Merely looking at just one aspect of performance can even be detrimental, as it blinds us from other motivating factors.

In fact, in an increasingly digital HCP world where 98% of physicians use the Internet for professional purposes [1], the task of understanding and connecting with this audience has grown more and more complex.

Specifically, with regard to digital web analytics, some of the primary and day-to-day concerns revolve around site performance and content engagement. What many of these issues generally boil down to are fairly straightforward answers—number of site visits and interest in specific site content.

Volume of site traffic is, independently, a rather inert number that can be incredibly misleading. High numbers one month followed by a much lower volume the next would assert that website performance has declined in terms of site traffic—but placing these numbers in context of another metric could change the view entirely. Looking at visits in light of bounce rates could inform us that a far smaller percentage of visits bounced in the latter month. Time on site might stay the same from month to month, but if page views per visit decrease, then more time is being spent consuming content on each individual page (on average), delivering an entirely different message once a corollary metric is introduced. The goal, after all, is to deliver the right message to the right audience, at the right time. A larger audience might not necessarily be the right audience, and so the quality of a site visit or a digital imprint is affected by and affects a multitude of other elements.

The benefits of exploring the connection between metrics are the models that emerge from the analysis, which in turn allow us to make more surprising and valuable insights. A top-line glance may miss or overlook these connections in its urgency to survey surface-level movements or trends; breaking down site referrals by traffic drivers might display which sources of site visits are the most prominent, but aligning these sources with other factors could reveal that certain segments are more likely to convert (download materials, sign up for accounts, order samples, etc.) and thus lead to immediately effective and actionable conversations.

At any point in a venture where data is generated, or can be generated, analytics can explain, evaluate, and optimize. No one part of it should be taken in isolation from the others, and this is no less relevant to the practice of analytics itself.

It is imperative that analytics never be stripped down to mere metrics, but live and thrive in a much larger framework.

CONTINUE THE CONVERSATION:
Questions? Comments? You can contact the author directly at
blog@ochww.com.
Please allow 24 hours for response.

Also posted in Analytics, Content Strategy, Data, Digital, Healthcare Communications, positioning, Statistics, Strategy | Comments closed