A few month ago, I decided that doing SEO without knowing good analytics was probably making me waste a lot of resources in working hard to earn non converting traffic. And god was I right. So about a month and a half ago I picked a copy of Advanced web metrics with Google Analytics by Brian Clifton to reach “the next level” and started learning how to analyse my data and I will share a fraction of my newly acquired knowledge in this post.

Prelude – Show real bounce rate in Google Analytics

A lot of people refuse to use Google analytics for many reasons, one of them being the stupid way GA treats bounces. Basically if someone visits your page, even for a while, and takes the time to read it entirely but does not visit a second page on your website, this is considered as a bounce. Pretty stupid since that visitor was clearly engaged, found what he wanted and then left because he had something else to do. By default the bounce rate in GA is close to useless but here is a little trick to make it meaningful again :

Just add the red bit (identical for everyone) in your analytics script the way it’s done in this example :

<script type="text/javascript">

  var _gaq = _gaq || [];
  _gaq.push(['_setAccount', 'UA-9903060-19']);
  _gaq.push(['_trackPageview']);
setTimeout('_gaq.push([\'_trackEvent\', \'NoBounce\', \'Over 10 seconds\'])',10000);

  (function() {
    var ga = document.createElement('script'); ga.type = 'text/javascript'; ga.async = true;
    ga.src = ('https:' == document.location.protocol ? 'https://ssl' : 'http://www') + '.google-analytics.com/ga.js';
    var s = document.getElementsByTagName('script')[0]; s.parentNode.insertBefore(ga, s);
  })();

</script>

What this will do is this will set “bounced” visits to anyone that stayed less than 10 seconds on the website and only saw 1 page which is the most commonly agreed definition of a bounced visit. Here is what your GA bounce rate should look like once you’ve inserted the code :

From 75% fake bounce rate to 7.22 real bounce rate, now we’re talking Especially when you’re a content rich site and people find your site through search typing “how to” keywords, you will experience this kind of drop because your users find the answer they were looking for and leave most of the time which is perfectly normal .

Now that we’ve set Google Analytics straight, let’s dive into advanced segments!

But first, how do you create advanced segments in GA? Follow the guide :

Part 1 : Basics of Advanced segments

In this part we’ll go over the basics of advanced segmentation, I’ll take a few examples of things I’ve personally used and explain how they are useful and what action you can take to improve your user experience using them.

Platform type

The mobile web growing more and more and offering a totally different experience compared to the desktop/laptop web, it is good to see how users using mobile platform interact with your website as opposed to the desktop users.

Here is the segment :

I know, pretty basic and you could go in users > mobile to see the mobile stats but when you try to cross it with other types of data such as source+landing pages the data gets hard to read. If you have an advanced segment on the other hand, this is extremely easy. In order to only select the desktop users, simply replace the include part with exclude.

English Speaking Vs Rest of the World

This one can be useful say if you run Adsense on your pages (and most affiliate offers) you want to mostly focus on your english speaking countries traffic. I would largely ignore the rest (and no I’m not racist) if you use any of these 2 monetisation methods which is the case for most content websites in english. Here is the segment :

Social Traffic

If you haven’t already engaged in social to earn traffic (and you should), you should know that when they come from social media, people usually interact in a very different way with your website. They didn’t actively search for you most of the time, they stumbled upon your content. That doesn’t mean the traffic is less valuable. In many cases, especially for content sites, social is a prime source of traffic and monetisation. It simply needs to be treated differently which is why creating an advanced segment for all social sources can be a good idea. Here is what the segment looks like :

Branded/non Branded search traffic

Because users interact with your pages differently wether they heard about it before or not, it’s good to separate branded traffic from non branded traffic. Non branded traffic often times discovers your website and it’s an occasion for you to convert them into recurring visitors. You can set specific goals for them and track the success of these through an advanced segment. Here is how I set it up :

Question keywords

More and more people type questions in Google, to know if your content actually answers their question, creating an advanced segment for these people is a great idea. If you drill it down per landing page and then check the time on site, you can easily find the content that does not answer people’s question, fix it and enjoy increased site engagement here is the segment credits to my personal Ninja Than Pham for this one :

That’s all for the basic ones, if you have more to suggest, hit the comment box, I’ll be happy to add them and give you credit and links for it. Now let’s dive into some more advanced ones.

Part 2 : E-Commerce application

Alright, this part is still experimental but I’ve tried to apply the basic theory to more advanced and real life (understand money oriented) situations.

For the first case study I took one of my E-Commerce stores selling a very specific type of shoes. I decided to stop for a minute and brainstorm the different scenarios possible that would lead to a conversion, I came up with these ones :

• Source : Organic, 1 visit => bought 1 or more than 1 pair (easy buyer)
• Source : Organic, More than 1 visit => bought 1 pair(window shopper)
• Source : Organic, More than 1 visit => bought more than 1 pair (future loyal customer?)
• Source : Direct, More than 1 visit => bought (loyal customer1)
• Source : Organic, More than 1 visit => bought (loyal customer2)
• Source : Direct, first visit => bought (real life referral)
• Source : Organic Brand keyword OR Referral , first visit => bought (real or or online referral)

Now that I have established these profiles I could pull some great data out there. My goal being to not only convert once, but convert as many buyers as possible into loyal customer1 and 2. through that path :

Easy buyer or window shopper or referrals => future loyal customer => loyal customer

some sort of super long term conversion funnel, and using these segments allows me to see how I’m doing at creating more and more loyal customers. Using each segment, you can see which type of customer constitutes most of your sales and see where most drop off in the “funnel”, you can then take action to ease the process of converting into a loyal customer.

Creating these segments also allows me to ask fundamental questions about my business. If my % of repeated purchases is low (under 5%) over 6+ month, is my product up to my customer’s expectations? Should I change my product provider? Was the buying experience detrimental to my buyers? Do the window shoppers convert enough ? Are my competitor’s offer more appealing ? How ?

You can answer most of these questions setting these advanced segments up and analysing the data.

An example, a cool insight I could extract from this is the following :

According to this set of data, 44%+ of my “window shoppers” take 4 or more visits to eventually convert. 10% of them take 15+ visits. Clearly if I find a way to pull them back on the website frequently (through social media ? Or retargeting ?) I will probably be able to increase my share of window shoppers (and they are over 30% of my sales)

Now if you cross this data with the recency data :

Over 80% of my window shoppers convert in the 3 days following their first visits, which means that if I say, setup a very short retargeting of 3 days, my repeated visit number will increase and chances are my sales will too. This is the kind of cool data you can pull from Advanced segments in analytics.

If you use these, please tell me how it’s working for you, I’d be interested to see what you guys can come up with when it comes to “advanced” advanced segmentation .

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