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7 Ways to Improve Google Analytics Data Analysis

To get a better view of your website, make sure you import as much detail as you possibly can into Google Analytics. Here are 7 ways you can do just that.

1. Adwords data

What do you infer when you see “other unique queries” under your keyword info in Google Analytics? Not much. By pulling your adwords keyword data into your main Google Analytics interface you can get access to a whole other level of keyword detail. The keyword on the left is the keyword or phrase you are bidding on in Google Adwords and the keyword in parentheses is the exact term the user searched. This can help you refine your campaigns as you can see exactly what is being searched to display your ad. You might discover that you need to narrow the search match or add a negative keyword to your campaign.

2. File tracking In order to track files you should tag the link with the _trackPageview() JavaScript. For example, to log every click on a particular link to www.example.com/files/bime-desktop.pdf as a pageview for /downloads/bime-desktop you would add the following attribute to the link’s <a> tag:

<a href="http://www.example.com/files/bime-desktop.pdf" onClick="javascript: pageTracker._trackPageview('/downloads/bime-desktop'); ">

You can track files such as PDF, AVI, and CSV.

3. Track Universal Traffic

With the evolution of universal search it can be hard to know which type of listing a user clicked on. What if 3 links to your website turn up in a search result? How do you know what the visitor clicked on to get to your site?

You need to apply these advanced filters:

Step 1 : Create filter for organic traffic
New filter -> Filter name `Organic`
Filter Type -> Custom Filter
Checked : include
Filter Field: Campaign Medium
Filter Pattern `organic`

Step 2: Create filter for All Universal Search traffic
New Filter: ‘Universal Search Items
Filter Type: Custom Filter
Checked: Advanced
Field A -> Extract A -> Referral -> (.*)oi=([a-zA-Z_]+)&(.*)
Field B -> Extract B -> Referral -> (\?|&)q=([^&]*)
Output To -> Constructor -> User Defined -> $B2 : $A2

You can also create separate filters for some of the Universal Search items instead of all of them.

Custom Step: Create filter for Universal Search - specific
New Filter: ‘Universal Search | images’
Filter Type: Custom Filter
Checked: Advanced
Field A -> Extract A -> Referral -> (.*)oi=image(.*)
Field B -> Extract B -> Referral -> (\?|&)q=([^&]*)
Output To -> Constructor -> User Defined -> $B2 : $A2

4. Track Full URL

Using the full URL can help you to see exactly where someone came from, instead of just the root level domain. Add this filter to your Analytics profile:

Custom Filter
Advanced
Field A -> Extract A: Referral (.*)
Field B -> Extract B:
Output To -> Constructor: User Defined $A1 
Field A Required: Y
Field B Required: N
Override Output Field: Y
Case Sensitive: N

5. Tracking Social Media Traffic

See our previous post How to Track Twitter Clicks in Google Analytics.

6. Tracking SEO Rankings

You can do this by setting up an advanced filter. Get detailed instructions on how to add rankings to Google Analytics by visiting the Yoast website.

7. Tracking Website Optimizer Data

Make the most out of your A/B and Multi-Variate tests, by leveraging Website Optimizer data using this script.

Bime Tip: Decompose, Drill Through & Focus features

In the new version of Bime, you can use the Decompose, the Drill-Through & the Focus features. Here’s a quick tutorial on how each one works.

Decompose

If you choose to decompose then you can analyze data using a different axis (i.e. a different attribute).

The cartesian and pie charts allow you to ‘decompose’ your visualization, both on queries and on dashboards (if allowed in the dashboard preferences). Click on a data range and a pop-up appears, offering you this option. Click, and you can select which attribute you want to dig down into.

For example, this pie chart shows results based on one attribute (here, ‘Year(Ship Date)’) - but you can focus in on one element of that (here ‘2005’) by using decompose.

Having opted to decompose using ‘Sales Channel’, the chart changes to show results only by the chosen Year, which has been moved to be a filter.

You can continue to ‘pivot’ your data by altering the filter. Alternatively, decompose another segment of the pie and each new view adds that segment’s attribute to ‘filters’, enabling it to focus in on that segment, and uses the new chosen attribute in ‘columns’.

Thus, decompose allows you either to drill down into the detail, or ‘flip’ the visualization from being defined by one attribute to another.

Drill through

If you choose to drill through then you can visualize the underlying data in each query.

In the pivot table, you can use the Drill Through feature on cartesian and pie charts to see underlying data for a selection of data points, displayed as detailed lines. For instance, the following figure illustrates the result of a query for which we visualize the Shipping Cost per Region. Let us imagine you want to see the underlying data for the Region Central. To do this, click on the Central horizontal bar and then click on the Drill Through item.

Once you click on Drill-Through for selected data points, Bime retrieves & computes all the underlying data and displays them in the Drill-Though pop-up illustrated by the image just below. In our current example, the Drill-Through operation has retrieved 2100 underlying lines (i.e. 21 pages of 100 lines). Consequently, keep in mind that the more numerous the underlying data are, the longer the Drill-Though computation time.

In the Drill-Through pop-up, you can navigate through the underlying data with the ‘Next’ & ‘Previous’ page buttons, visualize a specific page directly through setting the index of the wanted page in the numeric stepper, and exporting the underlying data as an CSV file through clicking on ‘CSV’. In addition, you can modify the number of lines which are displayed per page. Then, click on ‘OK’ to close the drill-though pop-up.

To conclude, please note that the Drill-Through feature is available only on in-memory & RDBMS connections.

Focus

If you choose to use focus then you can restrict and execute an original query of the dashboard only for elements you have selected.

In the pivot table, the focus feature is a shortcut to filter elements visually. As illustrated in the following figure, let us imagine we are analyzing the profits we realize per customer segments.

Let us imagine now that we want to restrict our analysis to the Corporate & the Home Office customer segments. For this, we have only to multi-select Corporate & Home Office, and then click ‘Focus on selection’.

As a result, the current result is restrict for Corporate and Home Office, as illustrated by the following figure.

To test out these awesome features, sign up for the free trial now!

Christmas Greetings from Bime

Wishing You a Very Happy Christmas and New Year

We’ve come to the end of another very busy year here at Bime HQ, and we are even more excited for the year ahead! We would like to take this opportunity to thank you for your support during 2010 and wish you a Happy Christmas and New Year!

Click here or on the tree below to view our Christmas card.

Have a great Christmas!

Remember: we are always online, contact us at any time!

The Bime Team

Optimizing for Mobile Devices - What Should You Look at?

Take a look at your mobile traffic data in Google Analytics. What do the trends and patterns mean, and what can you take away from this?

Something you probably want to know is how mobile trends affect the organization as a whole.

Using Bime, you can easily segment to show only mobile devices. Then choose a visualization that will show you clearly the proportion of your measure each mobile device is attributed to, such as the pie chart.  Choose a measure such as revenue (if you are tracking e-commerce or goals with a monetary value) or visits.

This will show you where your revenue (or visits etc.) is coming from. Say 50% of your revenue from mobile traffic is attributable to iPhones. You can use this information to make sure your site is optimized properly for iPhone users, or even run a campaign for iPhones.

A cool feature of Bime is the groups feature. I put all Blackberry devices in the same group, and eveything else in a group called “Other”. See the screenshot below.

What else should you look at? Look at the total revenue mobile traffic brings in. Is it worth spending time and money building a mobile site? By looking at these figures you can be more sure that you are making the correct investments.

There are many ways you can use your GA data to reveal trends that can help you optimize your offering. The trick is just to know where to look!

3 Tips For a Better Web Analytics Dashboard

The advantage of marketing online is that measurement is now so much easier than before. Huge volumes of data are created every day - email marketing, Pay Per Click, Search Engine Optimisation, Display, Affiliates and A/B testing can all be monitored and recorded.

Here are some suggestions for maximising the potential of your web analytics dashboard.

1. Keep It Simple

Either keep your web analytics dashboard to one page to avoid information overload, or simply use a tool which offers the ability to separate your analysis - e.g. Bime offers a grouped dashboard functionality where multiple tabs can be created to separate analyses as required.

You could try to provide further insights and recommendations that just the charts - don’t simply leave viewers to guess or misinterpret the information. Make the most of available functionalities such as comments, display options, sorting options and trend lines.

2. Use Filtered Data

Filters let you exclude and include certain traffic.  This is essential to get a really accurate picture of your web analytics. You might want to exclude internal traffic for example, or website profiles that are only used for testing purposes, allowing you to be sure that you are only looking at data from genuine visitors.

3. Segmentation

Segment your data! Why? This will give you the answers you reallly want, and will uncover hidden trends or patterns.  You may just want to look at search traffic, and from there look at keywords so that you can improve your Adwords campaign.  Segmentation will make your data clearer and easier to interpret accurately, as well as make it simpler to see if you are meeting your KPI targets.

So there you have 3 things you can do to improve the effectiveness of your web analytics dashboard. Can you think of any more?

Privacy and Web Analytics

Privacy is a topic that is becoming increasingly talked about in the web analytics industry. As data is becomes more and more integrated, and tools make functional improvements to respond to demands, data security concerns are finding themselves at the forefront of discussion.

Data needs to be secure, we totally agree. That said, it’s difficult with the world moving towards an increasingly mobile and personalized experience. The dilemma is how to offer these kinds of experiences without being able to collect the data necessary to justify the ROI?  It requires a certain level of trust between the parties, and in order to establish such trust, education about the storage and use of data is highly important.

According to The Wall Street Journal’s What They Know series, the 50 most popular U.S. websites all considerably use various tracking technologies to create profiles of consumers’ habits.  This includes web analytics programs such as Google Analytics.

Many companies used to access (and some probably still do) web analytics data (either their own, or that of a client) using a single username and password. Passwords often went unchanged for quite some time, and the login details were given to various people across the organization.

It goes without saying that this is probably not the best practice in terms of data security, especially from the point of view of client data, if anyone from the CEO to the intern has unprecedented access to their sensitive information. 

Competitive advantage or simple data overload could be other reasons to restrict access to such data - competing branches may not want their data to be viewable by others, and does the summer intern really need administrative access to client accounts? Everyone who has access to a web analytics tool should take responsibility for that access.

Here are a couple of tips and tricks on managing privacy and web analytics:

• Don’t share logins across the organization
• Create different levels of access for different users
• Regularly review existing users - should people that have left the company really still have access to your clients data?
• Encourage users to change their passwords on a regular basis

As we’ve mentioned before, the WAA have released version 2.0 of their Web Analyst’s Code of Ethics, which basically says:

We’re going all the way back to the [individual analytics worker] and saying, “Are you willing to put your name on a line and say you won’t associate personally identifiable information with tracking cookies unless there has been an explicit declaration thereof? Are you willing to say you won’t transfer the data without permission from the consumer?”

Eric Peterson and John Lovett

And privacy is the first item on the Code of Ethics, which reads:

“I agree to hold consumer data in the highest regard and will do everything in my power to keep personally identifiable consumer data safe, secure and private. To this end I will never knowingly transfer, release, or otherwise distribute personally identifiable information (PII) gathered through digital channels without express permission from the consumer(s) who generated the data. I will also work with my legal dept where applicable to enforce a cookie and user identification policy that is appropriate and respectful of the consumer experience in the environment I work in so as not to collect and maintain superfluous customer data.”

So to round off, as web analytics faces growing regulatory and public scrutiny, people who analyze online data are being confronted with various demands concerning privacy.  The Web Analyst’s Code of Ethics is the first document that could hold everyone to the same standard, and begin to combat the war on data privacy.