I want to start off 2015 with a miniseries of articles on data analytics. The reason is because as the Caesar Rodney Institute’s Communications Director I have spent a lot of time going through data analytics for our websites and social media pages (social media analytics will come in a future blogpost). Seeing the data is one thing; knowing how it can benefit your company or personal website is another. All you aspiring authors and personal profile builders out there, you might want to take a few notes. Knowing ways to build your Search Engine Optimization (SEO) can mean the difference between being discovered and going “viral” and being stuck in the bog of roughly 644 million websites worldwide.
For this post I’ll focus on Google Analytics (GA) and the book “Advanced Web Metrics with Google Analytics, 3rd edition” by Brian Clifton (John Wiley & Sons, Inc., 2012). Brian is the former head of web analytics for Google Europe, Middle East, and Africa, and I combine his lessons with my own experiences. Most of the newer editors are just slightly updated versions of previous editions, but if you have the chance to pick up a copy I’d recommend it. (author note: I do not benefit in any way from endorsing this book)
The first step in learning to use data analytics is to know why it’s so important for your website profile. Unfortunately many people just see a bunch of numbers and some pie charts and then don’t compare data from past months or try to dig into the data to spot useful trends. GA has over 100 different reports available for downloading and this is a daunting number for the new user.
Not all data points in GA are as useful as others; for example I discovered that, for CRI, measuring the average page visit was not very valuable. Part of this reason is because there is no perfect way to measure exactly how long someone really stays on your page- ever opened a new website in your browser, then gone off to do something else? At some point the website has to cut off your site visit time. Some sites cut it off after 30 minutes of inactivity, some 10.
Some useful data points which can be tracked:
- Your daily visitor total
- average conversion rate (if you sell things on your site)
- top-visited pages
- where people are searching from (location)
- where people are searching from (web browser)
- Your “page stickiness” (how many pages are viewed before a visitor leaves)
- keywords being used in search engines to find you.
All of this data, and more, help you identify your Key Performance Indicators (KPI). For example, a review of CRI data shows about 1/3 of people who find us via search engine are doing so by looking for us by keywords like “prevailing wage Delaware” or “Delaware government accountability” rather than by our name, which is an indication that there is interest in our policy issues but a lot of those people didn’t know we existed prior to entering those keywords.
Having this information available allows you or your team to figure out what is working and what isn’t working with your pages and make adjustments. So for us, for example, we discovered that we had an increase in total visits in November but a lot of those views were from November 1-20. By being able to break down the month into thirds to view our total page views, we could see that November 21-30 accounted for only 26% of our visits, which we attributed to the Thanksgiving holiday. Knowing the specific cause of the late November drop into early December prevented us from being overly concerned about the drop and then making an irrational decision regarding our online presence.
In the next post I’ll talk about some of the inaccuracies in GA and some ways you can prevent these inaccuracies from adversely affecting your data points. Please feel free to comment below on ways you use data analytics for yourself or your company.