I love data. Lots of data. Mountains of data. The more data, the happier I am as a marketer.
However, I’m sometimes perplexed when marketers use surface level data to try to make strategic marketing decisions. When metrics like Page Views become the centerpiece of a marketing discussion, it’s actually risky trying to identify insights without taking the analysis much, much further.
Page Views, Time-On-Site, Exits and other top-line metrics can be the start of the equation, but they require cross-data analysis to generate meaningful, actionable insights. Without a second or third layer of data, you run the risk of completely misinterpreting a hodgepodge of unsegmented data.
Instead of looking at Page Views, for example, you’ll gain far greater value by analyzing Page Views of new visitors vs. repeat visitors, or of those coming to your website through SEO vs. those through display ads, or of those who converted onsite vs. those who left without converting. It’s possible that your best site visitors are not those that look at the most pages. High Page View counts can sometimes reveal that something’s actually wrong with your site, such as complex navigation that drives extra, needless clicks. There are countless ways that surface level data can be misinterpreted.
By not going deep enough with their data analysis, companies draw the wrong conclusions quite often. One consumer software company was targeting Japan as its main market, yet they were analyzing all of their web analytics data on a global basis. They had not done any type of Japan-specific breakout of their data, rendering all of their analysis skewed and unreliable.
An online publisher focused on its SEO numbers, and thought that results were improving steadily. However, further analysis revealed that various sections of the site had actually experienced explosive growth in SEO traffic. Yet, this was in stark contrast to one particular section of the site that had experienced an 80% drop-off in SEO results. Without the deeper-dive analysis, they never would have realized how rockin’ most of their site was performing in SEO and never would have been able to identify and address the isolated weak area in their site.
Certain companies forget to segment their analytics data into groups associated with customers vs. new prospects. For example, if your goal is new customer acquisition yet you're combining your traffic data from email marketing together with traffic data from display ads, paid search, or sponsorships on third-party sites, you may be deriving the wrong conclusions to what’s working and what’s not.
So remember, when looking at your analytics data, go deeper than surface level. Start slicing and dicing your data against many different data points, and your analysis will become infinitely more valuable, and more actionable. Then you’ll REALLY love your data!!