Today's post is a Guest Post by Blaire Jones, Spinnakr’s answer to a Swiss Army Knife. She does a little bit of everything in regards to customer and business development, digital marketing, and operations. She’s got a hidden talent for technical recruiting and finding beautiful (and affordable) real estate, and can probably answer your questions about business law if you catch her in an accommodating mood. When undertaking a website optimization effort, the first step is admitting you have a problem, but the harder part is knowing what that problem means vis-a-vis a remedy.
In the course of onboarding Spinnakr customers to our referral-targeting beta, the number one question I am asked is what insights can be derived from analytics data. Just knowing what the data are saying isn’t really that helpful. The helpful thing is knowing what the data are telling you to do (or not do, as is often the case).
Listen closely. Here are 9 things that your website and its analytics data are trying to tell you:
1. I really need a directive.
If you aren’t sure what your website analytics data means, or think there’s a lot of information you can’t use, your data is telling you it needs a clearer purpose.
Your analytics data must have a purpose that tracks the purpose of your website. Your website’s purpose may be to drive sales, signups, or other conversions, or it may be an online equivalent of a business brochure. Whatever you want your website to do, tell your analytics tool what the objective is by focusing only on the Key Performance Indicators relevant to that directive.
Otherwise, you’re going to be looking at a massive amount of information that isn’t too helpful and, probably, trying to reverse-engineer the information that you have to shoehorn a purpose and measure performance for your website from there. It’s much more efficient to start with the directive, and measure only the KPIs that will give you insights into relevant performance.
If you can’t resist measuring absolutely everything, just go ahead and set up multiple dashboards in Google Analytics. You can have one that takes a kitchen sink approach, and one that measures only the information you really need to track website performance. (Note: you can have as many as 20 dashboards in Google Analytics concurrently, so there is some room for experimentation).
2. People don’t find me the way you think they do.
Some of the most valuable pieces of information your analytics tells you about are traffic sources. If you know where big groups of people are coming from, you can market to them there. You’ve got some combination of traffic from organic search, social media, paid search, referrals, and direct traffic. Great. Now that you know something about volume, identify their behaviors. The sources that are sending you lots of converting visitors are worth a bit of marketing focus. On the other hand, if your referral links aren’t sending you converting visitors, you might want to dial back on affiliate marketing, writing guest blog posts, or doing anything else that’s high cost (in time or effort) and low return.
3. Your content isn’t that interesting.
If you’re using your website for content marketing, and your number of returning visits is low, your website is trying to tell you that your content isn’t yet doing its job engaging prospective customers at key points as they evaluate and make a purchasing decision.
4. Your Conversion Rate is Higher Than You Think.
A low conversion rate is usually considered a bad sign. But your website analytics data is never casting judgment on your approach. It could be telling you something else entirely; for example, a low conversion rate might tell you that you’re doing a good job casting a wide net to refer tons of traffic to your site (provided volume was your objective); it might also tell you that you’re driving traffic from the wrong sources. The latter bit of information is especially helpful when you look at conversion rate by top referring URLs. Your conversion rate by top referring URLs is much more telling than conversion rate overall, because some one has taken an affirmative effort on those URLs to paste in a link that sends you inbound traffic. If that link is working for you, do more similar efforts, and less (if any) of the activities that aren’t producing a return.
5. Percentages are not going to help you fix me.
A percentage doesn’t really tell you what you need to know. By being oblique, your percentages are telling you to look at raw data instead (or at least in addition) so you have contextual information that shows the volume of return, as in number of conversions per page compared to percent conversion rate, for your various website marketing efforts.
6. Please. Stop with the averaging.
When measuring website engagement, there’s an irresistible impulse to find averages in website visitor data. Average time on site, for example. Or average number of page-views per visit. The fact that average information isn’t that helpful to you is a signal from your analytics to look at the numbers a different way.
Your website is telling you it’s much more valuable to look at frequency distributions so you can see the impact of engagement on conversions. This is an easy setup in Google Analytics “advanced segments” that can reveal lots of interesting, relevant insights when reports are applied. Plus, once you have information about time on site laid out in a frequency distribution, you can decide what you really want to do with the information along the spectrum, like really focus on bringing the less engaged people up, or giving the highly engaged folks more of what they seem to like.
7. If you must see averages, look at averages by segmenting traffic sources.
Average time on site for all social referral traffic, average time on site for all paid referral traffic, etc. is more meaningful than average overall, because it tells you which of your digital marketing efforts are producing the best return, so you can focus on those efforts and let some of the low-return efforts slacken a bit.
8. Your own team is interfering with my reporting!
You’ve got a handful of visitors that are highly engaged on your website. They spend 1600 or more seconds per visit! They come back more than 3 times each week! That would be great, if you could be sure they weren’t members of your own team working on content or the website. IP Exclusion is not too difficult to set up in Google Analytics. (From your admin account, select “Profile Settings,” scroll to “Filters Applied to Profile,” click “Add Filters” and enter IP addresses to exclude. Then save.) Excluding staff IPs will give you more confidence in your analytics hygiene, which is always a good thing.
9. You should not care about bounce rate on low-returning pages.
Website optimization is great, but you do not have time to optimize every page and even if you did, the effort would be wasted. Find out which of your pages is steadily pulling a medium amount of traffic relative to others, and focus your efforts there.
Would love your comments about what your website analytics data told you, and how that made a difference to your digital marketing strategy via email to blaire (at) spinnakr (dot) com, or in the comments section below.