Are you obsessed with analytics? Do you find yourself checking your website’s stats several times every day?
The answer could well be yes – we are all guilty on occasion of spending a little too much time obsessing over how many people are visiting our beloved blogs.
Here is a more difficult question that I want you to consider carefully – what value do you get out of your habit? How does your constant and consistent analysis of your analytics actually benefit your blog and/or business?
It is all too easy to get little to no value out of analytics. It is also remarkably easy to draw completely invalid conclusions from the data available to you.
With that in mind, let’s take a look at 5 reasons why you may have your approach to analytics all wrong.
1. You’re Obsessed With Bounce Rate
For the avoidance of doubt, let’s quickly check out Google’s definition of bounce rate:
Bounce rate is the percentage of single-page visits or visits in which the person left your site from the entrance (landing) page.
It seems like a simple enough definition, but you can get yourself in a whole heap of trouble by misinterpreting bounce rate.
Firstly, forget about quality (related to your design and content), and consider relevance. You could have the most engaging site in the world – for its target audience – but still attract a high bounce rate. So many people assume that the problem is on their site, when it may in fact be the type of referral traffic that is creating the issue. A prime example of this would be traffic from Stumbleupon, which is notorious for sending your bounce rate through the roof.
Secondly, consider the fact that bounce rate might not be a bad thing at all. Say you have a subscriber – an ardent fan of your content – and they receive an email notification of a new post on your blog. They click the link, read the article in full, then get on with their day. That counts as a bounce – and yet the visitor was thoroughly engaged.
Even if you weed out returning visitors from your analysis and consider only new visitors, bounce rate can be misleading. For instance, when I was looking at Google’s web page linked to above, I briefly hit the back button on my browser to check if the listing in Google had a date stamp. Although the web page told me exactly what I wanted to know and I subsequently linked to it, my two visits are both bounces.
You might be ready to jump in and tell me that although I clicked the back button, I was still on Google’s domain, so it doesn’t count as a bounce. But the definition page was on a subdomain of Google’s main domain, and clicks between domains and subdomains count as bounces. Just another reason why bounce rate can be misleading.
For more information on bounce rate, check out this infographic from Kissmetrics.
Oh, and if this was the first post you read on ManageWP in this session and you clicked on that link, then came back to this article when you were finished, guess what – you counted as a bounce.
2. You’re Obsessed With Time On Site
I haven’t seen a better explanation of how flawed a metric time on site is than this by Avinash Kaushik:
It turns out that every visitor doesn’t rub their head against their monitor before starting their session on my website (and of course another head rub when they decide they have had enough and exit).
Okay – so it’s not an explanation as such, but it is a heavy implication as to how limited analytics bots are in measuring true time on site. It would be folly of me to go into the fine details, as Avinash has already done so brilliantly in the above article, but I will summarize an example he uses:
- Visitors hit home page.
- One minute later, the visitor clicks to another page.
- Visitor sees an attractive offer and clicks through to a third page.
- Visitor notices fine print and leaves.
There are two things to take from this:
- The above example could result in an above average time on site, but it wasn’t a positive user experience.
- The time spent on the final page was not measured (and therefore omitted). The time spent on the final page could have doubled the total time on site, but you would never know that.
There are plenty of other question you can ask yourself when considering the relevance of time on site. What if a user opens a link on your site in a new tab, and your site remains open in the background? How useful a metric can time on site be when bouncing visitors don’t even get counted?
And most importantly – what is a “good” time on site? What represents success, and why? What does extended time on site bring you in terms of results? If you are simply engaged in a constant battle to increase time on site just because, you will be left bitterly disappointed – as your blog grows and your referral sources become more and more diverse, your time on site is likely to go down, rather than up.
3. You’re Obsessed With Page Views
And now we move onto the last of the three main “important” analytics metrics.
Here’s the story in a nutshell – for the most part, only those who actually benefit from multiple page views (such as sites with $ per impression ads) should be paying attention to page views.
What does a high number of page views mean? Does it mean that your visitors are wandering hungrily through your blog, voraciously devouring every morsel of content that you have on offer? Or does it mean that your navigation elements are hopelessly misleading, and your visitors are clicking from page to page in frustration before finally leaving?
As is the case with bounce rate, there is absolutely nothing wrong with one of your subscribers landing on a new post, reading it in full, then leaving your site. That will count as one page view (the horror!), but in reality you have just seen one happy and engaged reader pass through your blog – someone who will be returning in the future.
Just like time on site above, you have to ask yourself why higher page views represents “success”. What benefits does a visitor reading multiple pages bring you?
4. You Don’t Consider The Human Element
At the end of the day, the numbers you find in your analytics service are just that – numbers. They can be flawed and they can be misleading. That is not to say that they are without value – far from it – but to view them as objective evidence of the quality of your site is folly.
Let me reiterate my point in a different way – analytics data is not cast iron evidence of human behavior. Depending upon your site, each of the three metrics covered above could be viewed in completely different lights.
Take Yahoo! Answers as an example. I would love to see their bounce rate, time on site and page views – I’m guessing that they would look pretty awful to the average blog owner. But it doesn’t mean that the site is a failure in achieving its goals.
And that leads us smoothly onto our final reason today as to why you may have your approach to analytics all wrong.
5. You Don’t Know What You Want
If your aim is to get people to hit your site, hang around, and click on lots of pages, then feel free to stop reading this article. Just keep doing what you’re doing.
If on the other hand you want to promote engagement and perhaps even establish or increase revenue (gasp!), you need to take a long hard look at what you are actually getting out of your analytics analysis.
Because make no mistake – understanding what you want from your blog is the key to effectively using analytics. Until you have figured out what the point of your blog is, you are floating without a paddle. It may sound like a silly statement, but do you really have a perfectly-formed idea of the reason for your blog’s existence? Consider that question carefully.
Analytics Are Not Redundant
I’ve been hard on some popular metrics in today’s article, but I want to make something clear – I do not consider analytics to be an obsolete tool. Far from it. Nor do I consider metrics such as bounce rate, time on site and page views as useless when gauging engagement on your site. When used in the right context (and under the right understanding), they can be valuable.
However, I do think that analytics are utilized ineffectively by a huge proportion of blog owners, and this is my humble effort (in part) to redress that situation. Consider today’s article a primer on what not to do. In part two of this series, we are going to be looking at 5 ways you can effectively use analytics to your advantage.
What About You?
Has this article changed your perspective on analytics? Or do you consider my arguments to be flawed? Feel free to share your opinion in the comments section!
Creative Commons images courtesy of Enderst07, gualtiero, striatic, Lauren Manning and Brief Gasp
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