Why Should You Care about the Visitor and the Visit?

Guest blog post by John Butler, Sr. Consultant, Analytics and Optimization, Numeric Analytics —

Garbage In, Garbage Out
Why care about the visitor and the visit? What about why visitors abandoned or why they repeated a process? Why did they give negative feedback via the Voice of Customer survey? Simply put, if you don't care about the visitors, their visits and their feedback when analyzing your web site, you are taking a GIGO approach to analytics. What is the GIGO principle of analytics, you ask? Garbage In, Garbage Out. This may seem a little extreme, but in the early days of analytics, this wasn't too far from the truth.

Let's face it; there is no shortage of data in the analytics world, at least not anymore. Once upon a time, before the days of clickstream analytic tools, the data available for analytics was limited to log files collected by the web server. You were able to get only a limited amount of data, and were left on your own to figure out better and more creative ways to extract something meaningful. Regardless of the number of ways we tried to slice up this data, we were forced to analyze our web traffic at a high level and make some big assumptions about what was good and/or bad for our site.

From those early days of web analytics, we developed some bad habits, which can cloud the way we look at the massive amounts of data we have available to us today. We grew accustomed to looking at high-level data and making assumptions about that data, without understanding 'why' the visitor came to our site in the first place. Which brings me back to the question "Why should you care about the visitor and the visit?" Understanding “why” the visitor is on your site starts to remove some of the uncertainty around the decisions you are trying to make and adds clarity to your analysis, enabling you to drive business-critical action.

The massive amount of web data we collect provide us with “what” the visitor did while on our site. We can slice and dice this data a million different ways, but until we understand “why” visitors behaved as they did, we are left with something slightly more meaningful than GIGO. Understanding “why” the visitor was on our site or why they left provides us with the treasure we have long been searching for... actionable insights! So, the better we understand our visitors, the more confidence we have in our data and our analysis. As confidence grows and more trends start to emerge from a deep understanding of the visitors on your site, you can start to drive real change within your organization through true actionable insights and business-critical action.

Understanding the “Why” of Site Behavior
Now that we are clear on the importance of understanding ”why,” we need to determine the best way to dig useful information out of our data store. In other words, how do we filter out all the noise to determine the “why?”

The first step is to break that data down into smaller, more manageable chunks or segments. Segmentation will add clarity and focus to your analysis, helping you to understand the true reasons behind visitor behavior on your site. All sites are different but a good place to start is with broad segment definitions, such as geographical region or country if your site is international. Once you've defined some broad segments, start creating more focused segments to break these broad segments into smaller pieces of data. Segmented data is the cornerstone to analytics success and, ultimately, actionable insights.

Segmentation goes back to the GIGO principal. Segmentation allows you to maximize your investment in analytics and lets you treat each visit/visitor as the individuals they are. I think we can all agree that not all visitors and visits to our web sites are the same. The visitor that came to my site to purchase 100 of my most expensive specialty widgets is more valuable than the visitor that came to my site to view the list of job openings available.

A Segmentation Example
Take, for example, two hypothetical companies that sell the exact same products on their web sites. Company A gets 1,000 visitors a day and Company B gets 2,000 visitors a day. Company A converts 50% of their visitors (500 sales), and Company B converts 25% of their visitors (500 sales). Without segmentation, the logical conclusion is that Company A is doing a much better job of converting their visitors, by a factor of 2X. Without segmentation, the best we can do is make assumptions about what this data is telling us. Now, what if I told you Company A's web site had 20 total pages, focused on only the products they sell, while Company B had 100 pages with a lot of additional information about their products, customer reviews, FAQs, help, and a forum? Again, without segmentation, this additional information allows us to make more accurate assumptions but still doesn't tell us what is actually happening and “why” on the visitors are on those sites.

With segmentation, we can start to filter out some of the noise, and determine the real reason(s) visitors came to our web site. In the example above, if Company B had a segment of visitors identified as non-buying customers, we might find over 1,200 of these visitors are there to view their great content, research products, read reviews, perform company research, participate on the forum or to look for a job. Now, not only does their data look a lot better, in terms of how they are competing with Company A, but it makes a lot more sense as we begin to understand the “why” component of our analysis. To take this a step further, we might want to break our buying and non-buying segments down further to provide even deeper insights into more specific areas of our web site.

We will continue our discussion of segmentation and how to obtain insights that you can take action on in our next post on this topic. Stay tuned!

Numeric Analytics is the leading organization in North America focused on marketing analytics, optimization and automation.