With Google’s goal conversion and filtering now all being able to accept regexs all over the place, it is a skill all analytics people should have up their sleave, rather than running to the dev team.

So What Exactly are Regular Expressions

I cannot say it much better than this:

A way of describing a pattern in text - for example, “all the words that begin with the letter A” or “every 10-digit phone number” or even “Every sentence with two commas in it, and no capital letter Q”. Regular expressions are useful in Apache because they let you apply certain attributes against collections of files or resources in very flexible ways - for example, all .gif and .jpg files under any “images” directory could be written as “/images/.*(jpg|gif)$”. Apache uses Perl Compatible Regular Expressions provided by the PCRE library. - Apache Glossary

Where Can I Learn About Regex?

There are plenty of places online that provide regular expression tutorials and how to implement them into your code. However, we do not need to implement them into PHP or JavaScript, we just need them to filter data in big analytics reports.

Google has recognised this and as part of becoming an Analytics Qualified Individual, there is an entire section of the conversion university regarding the topic. Visit the Google Analytics Regex Lesson and see exactly their application in your context.

Any Regex Builders out there?

Why of course there are! Here are just a couple:

• TrakkBoard - You can run this little app as a desktop version that has filtering already built in for a couple of small areas.
• RegExr - This is an app that lets you build, test and store regular expressions which you can cut and paste across into Analytics

So in conclusion, this might be the most painful part of the job (definitely the less sexy) but there so much awesomeness that comes out of nailing a regex just right (it’s better than crossing items off a to-do list).

But Wait - Don’t Get Greedy

Specifically relating to Google Analytics, Regular Expressions, and Goal Conversion tracking - there is one problem that always creeps up on the new guys.

You will discover that .* catches absolutely everything and you think it is a nice and easy default way to make sure everything is included and all goals track in one nice tiny expression. What you don’t realise is that by default regular expressions are greedy, and when you tell it everything, it does include everything. So resist the urge to take the easy way out. For example:

• If you know that there is only going to be numbers in the URL, use [0-9].

Have fun!

The reason why you should update to this piece of code (even though it is in beta) is that it can notably speed up the page load time of your website. With Google and the web itself starting to pay even more attention to the time it takes to load a website, you could actually be getting penalised and frustrating your users if it takes longer than needed to load one page.

How the javascript becomes faster is by dynamically generating and modifying Javascript objects as the page loads. This also has added benefits as has a less likely chance of freezing or not loading your page when it hits javascript code, meaning that the quality of the data it is collecting is a step closer to being even more accurate.

The other clear reason why you should be upgrading is the fact that it is working towards HTML5 standards, the biggest movement online currently. Any website that is taking the required steps in being cutting edge will greatly benefit all of its users.

So do your company, your website visitors, and the search engines a favour by migrating to the new code. Check out the instructions on how to upgrade your google analytics code provided by Google.

What I discovered is that we can determine which pages had the best performance for particular keywords on particular search engines. Obiviously the ones that the highest amount of traffic or are preferred by the search engines would have the highest rank. Also if any of those pages have changed over time, we can analyse what words were driving traffic previously compared to the current. And most importantly for the SEO analysts out there, they can see whether the same page is choosen across all the major search engines and if not, figure out the difference between them.

Let’s take it step by step shall we?

The GA Report You Need to Build

OK, before we can analyse some data, you need to have some of the new features of Google Analytics available under your account, namely the Pivot tables. What exactly the pivot tables do is out of the scope of this post, we just need the feature to do proper analysis of the data.

So firstly, bring up your standard generic Keyword Report that is generated by default.

Then we start to segment the data, so with the new second drop down in the keyword column we can select “Landing Page” to bring up the most used landing page for that particular keyword. Then we need to move across to the icons on the right hand side of the screen to select the “Pivot Report” option, which will then make available even more drop downs to segment the data.

We now want to Pivot by: and select source, for the various search engines. As you can see our data, whilst filled with numbers, is now a lot more interesting. For bonus points and even further analysis, you can Show both visits as well as Bounce Rate.

Your Report should now look something like this:

Example of how your report should look

So What do you do with this data now?

So from this data we can look at the performance of particular pages as well as their main search traffic drivers.

In the screenshot above we notice that “cars” was our best performing word but here is the most shocking news: none of the traffic came from Google! How many reports have you seen that could provide you with that insight. Now I know this is a highly unique situation, but it clearly shows my point - without this level of segmentation, we could never know that, or even worse, assume it came from Google in the first place.

The actionable item I would be presenting to my client is that whilst we have managed to drive a significant amount of traffic for this keyword, the next task for our SEO team is to make sure that we start ranking for that keyword in Google. How they go about that is up to their strategy they have set in place.

But I have another trick up my sleave, I want to see the history of this keyword and page combo over time.

The Keyword/Landing Page/Referrer Report

So we have our keyword - “cars” and our landing page, now lets track the history and see if this page ever ranked in Google.

Go back to our original keyword report, before our fancy segmentation and you should be able to click on the keyword in the report, which will take you to a keyword specific report, with a generic overview.

Now we need to pull the history, in this case I am going to take the last 12 months of so of data, you should be able to go up to the calendar in the top right of the screen and adjust the dates, very straight forward. And since im pulling monthly data, I press the Graph By button and change it to monthly numbers.

Then on the drop-down I select Landing Page to get a list of all the landing pages that have ever been used by that keyword. Then the final piece of data that really makes this report pop is changing the secondary drop down to add the Source so we can see the search engines. So you should end up with something like this:

Keywords/LandingPage/Source

What this report tells us?

Well it shows us that this keyword really did not start performing for us until July, almost 6 months after its creation. For that small period of time, the search engines jumped around a little bit picking a few different pages, but Yahoo really locked that page in. Interesting Google never thought that page was worth anything at all, and that is something our SEO team needs to address.

What should you do now?

Well the ball is really into your court. You have your list of keywords and their performance. If you feel they are not working for you as well they should, then this report can help you present your case to your relevant SEO team in order for them to understand the issue. These reports can all be saved and scheduled as well for future reporting. And you might have noticed we didn’t even discuss the other metrics in this report such as bounce rate and time on site, that is a whole other ball game.

• Engagement Goals - I think these are great for brand new websites with little to no feedback on how the design they chose is working for them. Also, if it is a blog, the time on site and page views can be nice and high - you are hoping visitors are hanging around and reading as much as they can.
• Mobile Reporting - A must have for any website with a mobile version. A trend I am noticing as well is that due to the nature of mobile websites and their clean and simple UI, people are using the mobile version even though they are on a desktop.
• Advanced Analysis Features - Great for when the client requests that quick once off report. The power of advanced custom segments without having to go to the trouble of creating them.
• Multiple Custom Variables - This is fantastic, you can segment until the cows come home all your regular and repeat visitors, and detect patterns in their behavior.
• Custom Alerts - This feature is perfect on being alerted straight away of your online marketing campaign objectives. Rather than going into just to see how your tracking, you are alerted, get the report and leave, spending less time babysitting the data.

So if you already have these features available in your account, leave how your using them for your own campaigns in the comments!

(not set)

Now this item can appear in various places in various Google Analytics reports. So I will attempt to cover the most common areas it can appear and explain the reasons why.

(not set) in the Geographic Report

GA picks up geographic data primarily from your IP address. This IP lookup is conducted using a 3rd party vendor (ie. not Google themselves). According to the documentation then, if the 3rd party was unable to identify the location of your IP, it will set it as (not set). If your visits view your website through some proxies, it could be one reason for this.

(not set) in the Campaign Report

This one is a nice and easy reason. Basically you haven’t tagged your links correctly and there was a problem parsing the data. Use one of the many URL builders and other analytics tools provided by Google and others to make sure your custom tagged URLs are formatted correctly.

(not set) in Traffic Report

Since there are new portals, search engines, social networks and other websites appearing online almost everyday, it is impossible to keep up with them all. Hence for some of the smaller ones that are yet to gain traction, they are not included in Google’s list (think Bing - when it was launched Google was a few days behind on including it in its search engines list). So until GA figures out the best way to identify the particular website, it sets it as (not set).

In line with that, it is good to note that it is possible for Google.com to come through as a Referring Website when by all rights it should be coming from a search engine. This occurs when someone comes to your website from Google, but not from a SERP (Search Engine Results Page). For example if you use iGoogle for your RSS feeds, and someone clicks thru from that to read your blog post, that is a Google.com referral.

So how can you Minimise the Amount of Times (not set) Appears?

The easiest way is to make sure if you are running any campaigns (PPC, email marketing, social media, etc) to make sure your links are being tagged correctly. Stay tuned for a future post on how to do that.

Other than that? Analytics data collection is not perfect, and we all know that. So unfortunately we just have to deal with these little bumps. In reality it should only be an extremely small subset of your data. If it is accounting for more than 20%, its time to dig deeper into your Analytics installation for some underlying problems.

I want to take it in a little bit of a different direction. I find it difficult (probably as most bloggers do) to generate feedback on my posts in the form of comments or tracbacks. And to be honest, I can’t really determine what would influence someone to leave a comment versus someone who reads regularly. The more experienced bloggers would be able to give me a clear answer, however I am going to try to work it out with Google Analytics.

Modifying the GA Code - setVar

The answer lies with the pageTracker._setVar() function of the Analytics API. What this function does according to the documentation is allow you to create custom variables that you can tag your visitors with when they visit your website. It adds it to the __utmv cookie and lasts for 2 years.

How we are going to do it today is everytime someone comments on a blog that I author for, it will tag that visitor as a “commenter”. That will allow me to monitor their movement through the website and determine any correlations between commenters, return visitors and converters.

How do we do it in Wordpress?

Very easily in fact. Look for the file that generates your comments template and styling. Generally it is in your theme directory and the comments.php file.

Much like all the other Javascript function calls, I will be attaching it as an onclick event on the submit button. We make the assumption that someone has filled in all the key elements of the comment (name, email, the comment itself) and is now ready to submit. Whether the person is a spammer or not, or even if the comment is approved or not does not matter. The fact is someone (or something) was motivated enough to leave something behind on their visit.

My submit button code now looks like this:

After about 24 hours or so, you will be able to view your Google Analytics User Defined Reports and see that information in there. For further refinement you can even set up a separate profile to generate reports specific to their actions across the website.

Tune in next week as I further dig around the cookie structures of Analytics and see what other gems are in store. After a few months of data collection, I will be giving tips on what to do with the data once we have collected it.

Recently Google Analytics allows you to track events (such as clicks on objects on a web page) and I will show you how you can do this for your own Wordpress blog.

Step 1: Have the Latest GA code

In order for the Event Tracking code to log the events correctly, you need to use the ga.js code and not the legacy. Please check before going ahead.

Find the Relevant Wordpress Theme Files

Now we have to find out where in the Wordpress theme the link is generated that allows people to click through to the full post. But here is the catch - there is more than one way to go through to the post from these index.php and/or archive.php - the headline and the read more link. So we have 2 events to track:

• Visitors Clicking the Headline
• Visitors Clicking the ‘read more’ link

The Code to Add to the Anchor Tag

Ok, so now you have found the location where the anchor tag is generated, its time to add our javascript code. It will follow this format:
onClick=”pageTracker._trackEvent(’post-click-thrus’, ‘going-to-read’, ‘Identifier’);“>Play

Lets break this down parameter by parameter:

• Category: This basically groups all our events under one kind of category - in this case post-click-thrus
• Event: What this does is register the type of event that is performed under the category. In this case we can assume that if a visitor clicks on the ‘read more’ link or blog title they are going through with the parameter going-to-read
• Identifier: This will now tell us how we can identify this event, whether it was a ‘read more’ click or a headline click. In this case we did read-more-link, we will need to create a separate event tracking for the headline, and I would use headline-link to identify that.
• Source: Google Event Tracking Guide

Play the Waiting Game & Checking the Data

So where can we see the report? Well that is the easiest part. Google has put it in a very handy place, under the umbrella of the content reports. If you Content Report, depending on your setup it will be toward the end of the reports list, under the heading Event Tracking. The rest of the report is fairly straight forward with the data it provides. At a later date, we will talk about a quick and easy way to extract data from large analytics report.

Leave your comments as to any fancy implementations of event tracking you have done on your website/blog and we can add it to the list.

The __UTMZ Cookie

According Google themselves:

When visitors reach your site via a search engine result, a direct link, or an ad that links to your page, Google Analytics stores the type of referral information in a cookie. The parameters in the cookie value string are parsed and sent in the GIF Request (in the utmcc variable). The expiration date for the cookie is set as 6 months into the future. This cookie gets updated with each subsequent page view to your site; thus it is used to determine visitor navigation within your site.

So what this means whatever method was used by that visitor to access your website for the very first time is how it is recorded for each and every visit after that as long as the cookie lasts on the visitors computer.

So is That a Good Thing?

Well it all depends. Where this cookie comes to the fore is when someone is doing research, say “digital cameras” and then spends the next few hours researching. Whilst they might not convert on the first visit, they might come back towards the end of the research and buy based on that original search. Rightly then, that keyword gets the credit for the conversion, no matter how the visitor accessed the website later on down the track.

However, my problem with this particular default setting is that the cookie lasts for 6 months. Is that really a reasonable amount of time to expect someone to make a buying decision. Sure there are extreme cases were this kind of buying cycle exists, but I am positive it is not the norm. And I am also going to make the assumption that not many search marketers are aware of this themselves - or they know and use it to bias their monthly reports towards making them look like their campaigns better than they really are.

How to Modify the Cookie

Thankfully, all is not lost, as those in the know can now modify the standard Google Analytics javascript to modify the length the cookie hangs around for.

The function that you need to modify is:

pageTracker._setCookieTimeout("");
The parameter to send to this function is really dependent on your own website’s needs and objectives. Cookies are stored based on the number of seconds. So if you wanted the cookie to last a day, the parameter should be 86400 or if you want it to last a month, try 2629743.

Conclusion

By adding this little hack into your Google Analytics code, you will be left with a much more accurate representation of your website’s traffic patterns, completely tailored to your website.

If you have successfully done this with your installation, leave a comment below and share what you do to improve the accuracy of your website’s data.

What you then, you who understands the important of web traffic data and the analysis of it, need to do is get proactive. You need to spend some time (even in secret) to prepare your case to present to the thought leaders or the decision makers. Most of these people very rarely argue with the facts and figures once presented correctly. What I plan to do here is provide you with the websites and people you should be paying attention to, so that you can give a well rounded educated response and argument to get your agenda at the front of their minds.

Occam’s Razor by Avinash Kaushik

Avinash is widely regarded by many as a major authority in the space. His books and website helps many with no understanding at all become self-taught experts in the field. I have found his book to be of great benefit when trying to educate clients and others about how web traffic actually works.

For your own analysis, his blog posts provide an almost step-by-step guide on how to segment data properly and create reports for your superiors. If you have never done advanced segmentation on traffic data previously, you can spend days going through his guides.

Google Analytics Official Blog

The Official Google Analytics blog is a great place to stay aware of the latest feature releases and overall traffic analysis processes. The main reason why I plug this is due to the fact that for most SMEs, Google Analytics would be the analytics package of choice, and hence, it makes sense that people should become experts in the tool.

As of today as well, they have just started with Data Driven Discussion, including Avinash mentioned above. Staying in touch with the experts whilst learning is the best way to go about it. I myself prefer watching videos then reading, and hence why I think I am going to be a big fan of these episodes.

KISS Metrics

The Kiss Metrics Blog is probably my favourite resource of them all. I really appreciate good website design (which is how I originally found the website) and then realised that it covered my next love, analytics! So not only is this website super sexy but also incredibly useful in providing tips and suggestions for beginners and experts alike.

Conclusion

One thing you will notice though as you progress through your learning and research of analytics is how important userability is when it comes to traffic analysis and website performance. The two go hand in hand so much that many of my clients have experienced a massive increase in volume of traffic, bounce rate and conversions by doing simple little things such as improving meta descriptions, dedicated landing pages and internal search analysis.

So the advice I leave you with is to visit these websites, learn from them, compile a few reports, prepare a presentation, get your voice heard, and then get the resources that you are craving. By the team this is all done, you will have the skills (maybe not the experience) in truely getting the most out of your team and the tools.

Block Your Business’ IP

The first step of any Google Analytics install should be to block out any fixed IPs used by your organisation. If your website is used by your sales team or support staff (*cough* their homepage *cough*) - this traffic shouldn’t be included in with the marketing objectives. This even includes search engine referrals as many less savvy employees could still use an engine to locate the company website.

New Visitors Aren’t Always New

Most analytics figure out if someone is new or old by various means, one of which is cookies. There are many web surfers out there that clean out their cookies regularly or don’t allow anyone to drop cookies on their website. Because of this they will be counted as new each and everytime.

For those that do not know/care about the cookies, these generally expire after 30 days from the last visit. From my point of view if no one has looked at your website for a period of at least 30 days, I don’t have any problems about counting that as a new visitor as there is probably a good chance that your website has changed in one way or another in that period.

There are Very Few One Night Stand Conversions

We setup goals and funnels that we all wish our visitors took each and everytime they come to our website. But we know in reality, only a small percentage of visitors will go landing page -> goal conversion page -> thankyou page in that exact order. That sounds more like the behaviour of a customer that already is familar with the business and the products and services - but more importantly - trusts the organisation.

To get to the one night stand conversion you have to earn that visitor trust, and once you master this extremely difficult step, you can see a nice improvement in your conversion rates.

If you use dynamic IPs it becomes a little more difficult, but as much as you can there should be procedures in place to minimise self driven traffic (is that the term? Let me know in the comments if there is an official phrase).

Website Overlay Link Percentages

Everyone loves pretty reports, whether they are about web traffic, financials, or performance stats. When people start digging around Analytics, many a client have wanted to further understand the website overlay feature. I personally like this functionality (when it actually works) as it can easily disprove the long held stigma that nobody scrolls when they search the Internet.

Anyway, what everyone fails to note is that if there is more than 1 link pointing to the exact same URL on that page, it totals the clicks from all links to that page, and assigns them the same percentage. So if the top homepage link got 3 clicks out of 10, and the footer got 1, the total percentage of clicks for BOTH of those links would be 40%, not 30% and 10%.

I would still not put all my faith on this tool, but just be aware because I have to explain this part of Analytics on regular occassions.

So in conclusion, by keeping these points in mind when you are generating your reports and your analysis, you will get a much more well rounded picture of visitor trending and behaviour on your website.