To really get the most from web measurements, online business owners need a clear understanding of exactly what they want to accomplish and how they will measure those accomplishments.
No matter how objective the reporting of analytics software, the meaning divined from its numbers and graphs is somewhat subjective, including our semantics—something that several recent articles have pointed out.
A debate is taking place in the analytics world over how certain commonly used terms are defined. I learned about the debate from Neil Mason’s recent column on ClickZ. This discussion of terms, described in more detail below, set me thinking about what analytics are supposed to accomplish, namely helping us improve web traffic, the customer experience, and—ultimately—conversion or action goals.
In this “eCommerce Know-How” column, I will (1) describe the analytics/semantics discussion in brief and (2) explain the system I use to set SMART goals for my ecommerce businesses.
IAB Proposed Definitions
According to its website, the Interactive Advertising Bureau (IAB)’s goal is “to achieve transparency in audience counts and to revise out-of-date methodologies.” This goal, and how it has manifested itself in slippery definitions like “unique visitors,” seems to have caused more problems than solutions.
As Mason puts it in his article:
The IAB’s definition of unique visitors differs from the web analytics industry’s commonly used definition — which is cookie based.
Web analytics systems define a “unique visitor” based on the presence of a cookie. If I visit a site using three different devices in a week [say a PC, a laptop, and a mobile phone], I’ll be recorded as three different “unique visitors.” If I also regularly delete the cookie, then I can appear to be a new visitor to the site and am therefore not counted as being “unique.”
Audience measurement panels define a unique visitor based on the activity of an individual member of the panel. Web analytics tools measure all activity on a website [a so-called census-based approach], whereas a panel measures a proportion of the activity on a site [a sampling approach] and then uses that to estimate the total.
So with two different definitions and two different data collection methodologies, it’s hardly surprising that people can get confused and debates rage about which numbers are right and wrong. It would certainly be helpful if web analytics tools came up with another name for unique visitors. That’s a massive issue for the industry to address. Hopefully, it can be done collaboratively.
What Matters Is How You Define Your Goals
While is very interesting to read about the ongoing semantics discussion (see Eric T. Peterson’s recent blog post for more), what really matters for online store owners is how analytics in general can improve business. So, although it is important to understand exactly what definition is being used for a particular analytics term in a particular context, it is far more important to understand the goals you want to accomplish.
Establishing SMART Goals
I was introduced to the concept of SMART goals while working at a large Fortune 500 company. Establishing SMART goals for your business can help you achieve success. Simply put SMART goals are:
A Real World Example of SMART Goals
Let’s explore how SMART goals can be applied in the real world and how they relate to analytics. Imagine that you are about to embark on a new pay-per-click (PPC) campaign to promote a particular widget sold in your online store. Before you post an ad on Google, try making a SMART goal.
Let’s say you set out to sell 1,000 of the widgets — a very specific (S) and measurable (M) goal. If you only sell 800 widgets you will miss the mark, but if you sell 1,200 widgets the campaign will be more than a success.
Next, test your goal to see if it is achievable. Is selling 1,000 of the widgets realistic? Use your experience to tell. If it will represent only an incremental improvement in sales your goal is likely achievable, but if you only plan to invest $10 in the new campaign that is not very realistic. Rather your proposed actions (advertising investment) must be able to realistically (R) drive your achievement (A).
Finally, let’s say that you want to sell the widgets over the next month. With a time (T) constraint in place your SMART goal is complete.
Using Analytics to Monitor Our Goals
Now we bring things full circle. We can use web analytics, like unique visitors (however we define them), to monitor our campaign and determine if we are on target to reach our site goals. Suddenly analytics have real meaning.
For example, if our imagined PPC campaign increases traffic to our online store, but doesn’t seem to increase conversions, we can examine our campaign landing pages, our site navigation, or other factors, and adjust them accordingly. With SMART goals in place, web analytics become much more than just a turnstile counting potential shoppers as they arrive.