It’s that time of the year to review 2009: “Top 5 Google Analytics Posts in 2009”! We want to thank our blog readers for their time, input and comments and we look forward to offering you more useful tips in 2010 and additional methods and strategies to leverage Google Analytics and take your marketing optimization efforts to the max. This post lists the top viewed Google Analytics blog posts, as well as a couple of bonus points related to measuring blogs.
Let’s get started!
- Content Grouping in Google Analytics: this is our top viewed post in 2009. Marketers loved it and techies loved it too :), it showed you the what and the how. This very handy method allows you to categorize pages into groups of related content and collect these pages together and treat them as a single entity (for further analysis as a group). For example, if you have an online store with women and men clothing categories, you can use this technique to group the women pages as one “content group” and the men pages as another “content group” and then, as Avinash mentioned in his comment on this post, “content grouping can really help make a complex site much easier to understand from a macro perspective”. You can also, apply the same content grouping concept to brand pages, or to a groups of landing pages.
- Monetize your SEO effort by Leveraging Google Analytics: this was one of my posts and it had to be marketing & analysis focused, since I am not the javascript guy :). If you are running a Search Engine Optimization (SEO) program, you’d want to take a few minutes and read this post, if you haven’t already. The post uses a case study and real numbers to help you answer questions on how ranking, or lack thereof, impact the bottom line, and help you get decision makers to act and get the most out of your SEO program.
- Tracking Press Releases in Google Analytics: again, another method to enhance your measurement system and get a better sense of how your marketing initiatives are performing. Granted Press Releases fall under the “branding/awareness” marketing category, and we don’t just measure branding/awareness by immediate visits/outcomes, it’s still nice to have performance data for each press release. Check out this method, some coding is involved, but the implementation is detailed for you.
- The Cost of Misinformation: a popular post addressing the mis-information (by some fee-based web analytics vendors) about Google Analytics. In additional to the advanced capabilities and enterprise-level features that Google Analytics has been introducing, this post highlighted Google’s innovative, open and global eco-system for support, training and consulting, available around the globe by some of the brightest in the industry.
- Problems with Bounce Rates: this post was an answer to a lot of questions we get on how to correctly read and analyze one of the most useful metrics, the bounce rate. Hint: look at your top landing pages report.
And some from 2008!
And since we are talking about top posts, here are three posts that were published in 2008 but continue to be very popular, check them out and put them to use!
- Tracking Mobile Devices in Google Analytics
- Optimize Form Length with Input Analysis
- Detailed Pay-Per-Click (PPC) Keyword data in Google Analytics
And another bonus – E-Nor’s Guest Posts on the official Google Analytics Blog
In addition to the top posts on the E-Nor site, here are few posts that were well received (based on the limited qualitative data we have) on the GA blog:
- Structure Your Google Analytics Implementation – Account Roll-Up & Reporting
- How to Set Up Goals in Google Analytics
- Advanced Segmentation & e-Commerce
- Marketing & Campaign Optimization with Google Analytics
A couple of notes on measuring blogs and posts
Note #1- Normalize your data
If you really want to measure the most popular post in a year, the aggregate data might not tell the entire story. A post that was published in January will have a whole lot more time to get traffic/visits/comments/feed subscriptions/retweets than a blog that is published in December. This reminds me of what Malcolm Gladwell describes in his book “Outliers – The Story of Success” and how Canadian hockey players born early in the year all have a huge advantage and how this advantage compounded over time (he showed the stats and the numbers to back up his findings). So if you truly want to compare how each post did, you might want to normalize the data, add a weighing factor to compensate for the sequence of the month in the year, or simply measure stats for each post in X weeks after it has been posted.
Additionally, and for the visually inclined, you can use a Google Analytics’ Motion Chart to “play” the graph over time and watch how each post did and compare the various metrics concurrently over the span of the year.
For example, the chart above represents a number of blog posts (from the GA Top Content report) along with few metrics. The x-axis represents pageviews; y-axis: average time on site; size of the bubble represents $index, and each color represents a specific post.
You see how the blog post represented in dark blue behaved differently than the post represented in lighter blue. For example, you see a “big bubble” on the right hand side of the graph, ~550 unique pageviews with a relatively larger $index value, both are positive outcomes compared to other posts. One can then do a bit more digging and find out what led to this positive result and repeat it!
Note #2: Blog Engagement Metrics
When it comes to blogs, you don’t just want to measure visits & pageviews (that is so 2009! 🙂 ), you want to have more meaningful metrics. Who cares if you are pumping out posts like there is no tomorrow and no one is engaged. I’d look for things like feed subscriber rates, comments per post, words per comment, posts per blogger, among other things.
Here are a couple of snapshots from two bloggers that are active authors on the E-Nor blog, you’ll notice completely different patterns and user interaction.
A couple of observations
- Blogger A is more active in blogging 1.2 posts per month compared with 0.6 per month for Blogger B
- Blogger A gets fewer comments, 0.8 per post while Blogger B gets 8.4 per post
- One conclusion is that while Blogger A can write, his posts are not as engaging (ouch!) but Blogger B has a knack for getting people’s attention and input. Both bloggers can learn from this quick analysis and improve their posts in 2010 (Blogger A do something to get your audience attention, and Blogger B, charm us with more posts).
I hope you have found our 2009 posts useful! We’d love to hear from you for ideas, issues, questions and areas you like us to address in 2010. Leave us a comment below or email us directly at info @ e-nor.com
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