Tag Archives: Google Analytics

The Evolution of Google Analytics: A Timeline

This entry was posted in Google Analytics and tagged , on by .

Marketing and web design professionals with less than ten years of experience may take robust, free, analytics software for granted. But the wizened “old-timers” of online know that analytics technology has evolved immensely over a short period of time.

Think about it: Google Analytics (GA), the leader in this space, is less than 10 years old. GA is “younger” than Facebook. When Paul Muret, the engineer behind the first incarnation of GA was writing this important code, Justin Beiber was a newborn infant (my how quickly they grow up.) Let’s take a look back at the evolution of GA from its inception in the late 90s until today.

The Early Days of Analytics

Early 1990s: Two future founders of NetGenesis Corp., one of the earliest analytics software providers, room with Phil Mui during undergraduate studies at MIT. They introduce Mui to the topic of analytics. (In 2001 SPSS Inc., bought NetGenesis for $44.6 million.)

1995: Web Depot is founded in San Diego, providing web development and hosting to businesses.

1998: Paul Muret, Engineer and CEO of Web Depot creates the first version of Urchin, an analytics software.

September 1998: Google launches.

October 2001: Google AdWords launches.

June 2004: AdSense is introduced.

2004: Google first approaches Urchin to discuss an acquisition.

2005: Phil Mui joins Google and chooses analytics as the product he wishes to focus on.

March 2005: Google acquires Urchin and Paul Muret becomes directer of engineering at Google Analytics. Related geeky fact … did you know that the “UTM” code in Google Analytics stands for “Urchin Traffic Manager?”

October 2005: Google Analytics V1 is announced and then quickly shut down due to too much demand.

November 2005: Google releases V1 again, but this time with limited access using an invitation system.  The V1 tagline focuses on accessibility: “Democratize advanced analytics for the masses.”

November 2005 through August 2006: As it adds server capacity, Google sends out batches of invitation codes for new analytics users to sign up.

June 2006: The first GA product update is the addition of AdWords analysis reporting, allowing users to manage AdWords ROI. 

August 2006:  Google announces that GA access is open to all. No more invites or waiting. 

Throughout 2006: The analytics UX team works to change the original Urchin dashboard, which looked very 90s in version one of Google Analytics. (see the screenshot below).


Fig 2: A screenshot from Google Analytics version one in 2005. This dashboard reflects the design of the original Urchin software.

February 2006: Google acquires Adaptive Path and integrates ideas from its Measure Map product into the upcoming GA redesign.

GA Gets More Robust

April 2007: Google releases V2 of analytics. The V2 dashboard is redesigned to reflect the Google brand and looks much like the design interface users are familiar with today. With the V1 release, the GA team saw that the product was perceived as a tool for techies and web geeks and was not as widely adopted by marketers or c-level executives. That’s why the V2 tagline is all about organization-wide adoption, “Moving analytics from the back room to the board room.”

Fig 2: A screenshot from the 2007 version two dashboard redesign.

October 2008: Google releases GA V3, with a focus on making enterprise-level features accessible to everyone. Version three features advanced segmentation, custom reporting, and an external API. These are features that previously required plenty of time and resources to develop and Google wanted to open them to all users.

March 2009: Google launches its Conversion University courses and the Google Analytics Individual Qualification Test. Now users can become GA qualified experts.

April 2009: Google releases an AdSense integration feature, so users can measure content performance and revenue.

April 2009: Google Analytics Data Export API becomes available to all users, which opens the door for organizations and developers to integrate analytics into other platforms.

October 2009: V4 of Google Analytics releases featuring analytics intelligence, an algorithm that detects anomalies in site data and alerts users to those changes.

December 2009: Asynchronous tracking launches, greatly improving the speed and accuracy of tracking website data.  

October 2010: GA rolls out its in-page analytics feature. 

April 2011: GA V5 is released featuring multiple customizable dashboards.

August 2011: Google releases multi-channel funnel tracking capabilities. Now marketers can see a 30-day path to conversion and not just the last click before a purchase.

September 2011:  Google Analytics premium made available to power-users.

September 2011: The real time reports feature launches, so that users can monitor data as campaigns unfold.

October 2011: GA introduces flow visualizations. Now users can see how different types of visitors flow through the site and where users may have dropped-off during the goal completion process. Around the same time, Google begins encrypting search data for all searches signed into a Google account. Marketers begin seeing “keyword not provided” for those searches (collective sigh).


Fig 3. Goal flow visualizations provides crucial insights for users interested in conversion optimization.

March 2012: The client-hosted version of Urchin is discontinued and Urchin users are encourage to migrate to GA. Social reports are rolled-out to show the links between social media, ROI, and engagement.

June 2012: Google Analytics integrates the functionality of the former Website Optimizer tool and rebrands it with GA as Content Experiments. Users can now test website changes within the GA interface.

June 2012: Google Analytics for Mobile Apps releases.

Universal Analytics and Beyond…

October 2012: Universal Analytics is announced. Universal analytics reflects where GA is headed. Its designed to track users across multiple devices using user IDs. Universal will also enable users to track offline behavior and augment customer data with external demographic or other data.

September 2013:  Google search terms encryption to non-signed in Chrome users.

Today: GA releases more than 70 product updates in 2013 alone.  In 2013, GA had the largest market share in the online analytics space. As Universal Analytics begins to roll out to more users, experts predict the adoption rates to increase.

Resources for More Information

To read more about the beginning of GA, check out this awesome post from Attendly about The Real Story on How Google Analytics Got Started.  Here’s a video of Phil Mui describing the history of GA. You can also view Google’s evolution using its interactive timeline  or this infographic on the Digital History of Google from Search Engine Journal.

Image Credits: Fig 1. Source; Fig 2. Source; Fig. 3 Source.

Why You Want Sticky Fingers on Your Website

Vinyl records collectorsIn 1971, the Rolling Stones released Sticky Fingers, which would become known as one of their best albums of all times… and one of the most controversial pieces of cover art ever. The front of the cover displayed a close-up of a man’s denim-clad groin, with early vinyl editions featuring a working zipper and a real belt buckle you could actually undo. (It would even be dubbed the greatest album cover all of time by VH1 in 2003.) It was also the first work that the Rolling Stones would release that featured their trademark lips and tongue logo.

Over 40 years later, the lesson from this release holds true for everyone with a website today: be usable, be fun, be yourself, and don’t be afraid to cut through the clutter. And most importantly: be sticky.

Sticky? My website? What?

In the world of website owners, “sticky” is a term that means different things, depending on your business goals. It usually means that people stay on your website, looking at multiple pages and spending quality time with your content before leaving. Sometimes it means that they come over and over again to your site, always eager for the next big thing that you’re talking about or promoting. Whichever way you look at it, “sticky” is a good thing.

How do I know if it’s sticky?

There are two main indicators of whether or not you’re “sticky” enough to be successful. The first one is your bounce rate. Your bounce rate is the percentage of people that leave your website after only looking at one page. One of the greatest minds in all of web analytics, Avinash Kaushik, refers to this phenomenon as “I came, I puked, and I left.” No matter what business you’re in, you want your bounce rate to be as low as possible.


Keep in mind that it makes sense for some businesses to have a high bounce rate. For example, if you’re a breaking news site, people tend to only check the headlines on the first page before leaving, so you might see bounce rates of 50% or higher. However, for most businesses, we recommend at most a 25% bounce rate (preferably less). If you can’t get 1 in 4 people to learn more, you need to update your website copy or your offer.

Whatever website analytics tool you use, whether it’s Measureful or another tool like Google Analytics, bounce rate is always on the main dashboard because it’s so important.


Sample snapshot from Google Analytics: bad bounce rate, low page views per visit, not enough returning visitors


Sample from the Measureful report: good bounce rate, not enough returning visitors (3 out of 33 is not good)

Sticky = multiple touches

You can also determine your website’s stickiness by how many pages people look at when they visit. This metric is also known as “page views per visit.” This is usually an indication of how useful your website is at providing information people want. If you have a good average page views per visit (which is usually 3 or more pages per visit) but low conversions, you need to work on your offer. If you have low average page views per visit (2 or less), you need to work on your content and find out what your audience wants to read that they aren’t getting from you right now.

You can also look at the percentage of returning visitors you have. There’s no industry benchmark, but we recommend at least 30% or higher – you want at least 1 in 3 of your visitors to want to come back, in most cases. Even if you’re a business that deals with one-time or very low-frequency needs (such as a home purchase, wedding planner, estate planning, etc.), these are typically high-consideration items and you should expect several visits prior to purchase.

Sticky = attention

In conclusion, you want to be fascinating, just like in real life. Your website should make people babycomebackwant to get to know you or your business better. They should want to read more about what you do, and keep up with breaking news and new content. Keep your bounce rate low, your pages per visit at 3 or above, and your returning visitors over 30% or you’ll be singing along to a much less successful 70’s song: Baby Come Back.



The Ultimate Guide to 57 Ultimate Guides [Online Marketing Edition]

Ultimate guides are the new infographics. They are “everywhere,” and virtually every topic has been covered in exhaustive detail. Here are the top ultimate guides for online marketing, selected by relevancy, time, and popularity (number of backlinks). We’ve also included links to the authors on Twitter, so you can connect with them.

SEO Ultimate Guides

 Content Marketing Ultimate Guides

SEO (Platform Specific) Ultimate Guides

PPC Ultimate Guides

Social Media Ultimate Guides

Google Plus Ultimate Guides

 Facebook Ultimate Guides

Twitter Ultimate Guides

Pinterest Ultimate Guides

Analytics Ultimate Guides

There’s even an Ultimate Guide to Creating Ultimate Guides from Kristi Hines.

Have any ultimate guides to add? Send them on over or post them in the comments.



5 Tips for Testing with Google Content Experiments

This entry was posted in Reporting and tagged , on by .

Have you had a chance to use Google Content Experiments to optimize a website? Formerly known as Google Website Optimizer, Content Experiments was introduced in 2012 as a feature within Google Analytics. Content Experiments allows marketers to conduct A/B testing of an original page (A) against a variation (B).

During testing, Google will send a pre-determined percentage of new visitors to the test page and compare metrics for clicks, conversions, time on page, and pages per visit.  If you are new to A/B testing or Content Experiments, then follow these best practices for running successful tests below:

1. Establish a Measurable and Realistic Goal
Content Experiments has four types of goals or visitor behaviors that you can track including: URL destination, visit duration, pages per visit, and events (such as adding something to a cart). Don’t just test alternate web design elements for general usability. Instead, set a measurable and realistic marketing goal and use website testing to reach that goal. Why are you testing? What kinds of results do you hope to achieve? Maybe your goal is to send 10 percent more visitors from the home page to the highest-revenue generating page on your website. Or you could test two different call-to-actions in an effort to increase sales conversions by 3 percent or more. 

2. Keep it Clean
True A/B  testing means experimenting with one variable at a time against your original page. For example, here are three separate variations you can test for in a call-to-action:

  • Changing the language of a call-to-action. For example, “Get Started Today” vs. “Signup Today.”
  • Changing the position of the call-to-action. Testing an upper right hand corner placement vs. a middle of the page placement.
  • Changing the color of the call-to-action. Testing a red button vs. a yellow button.

Each of these individual tests can provide a lift for your marketing results. For accurate test results, keep your experiment clean and limited to one variation at a time. If you test a new color and a new placement for your call-to-action in one experiment, then you will not be able to isolate which change impacted visitor behavior.

3. Set The Right Parameters
If your website is highly trafficked, then running a test for one or two days may give you time to collect a relevant sample size and draw conclusions. However, if your site receives only a few hundred visits per day, then you may want to run your test over the course of a week or longer. Likewise, those sites with fewer visitors should send as much as 75 percent or more of new visits to the test page to help speed up testing. Use this A/B split test calculator from VisualWebsiteOptimizer.com to determine the right timetable for your test.

4. Use Content Experiments to Optimize AdSense Revenue
In September, Google announced Content Experiments integration for AdSense users. If you are a publisher running ads on your web properties, now you can leverage Content Experiments to optimize those ads for the greatest revenue. First link your AdSense and Analytics account, then test ad size or placement variations to determine which ad types  generate the most clicks and ROI for your site. Publishers may appreciate Google’s multi-armed bandit algorithm, which looks at live data and sends more traffic to the winning variation for maximum revenue. Or, publishers can override this option and send a predetermined amount of traffic to each variation. 

5. Take Advantage of the API
In June, Google opened the Content Experiments API to developers, enabling advanced users to pick and choose which testing functionalities they want to include. Using the API allows you to test without redirects, which provides a quicker and more seamless page load experience for visitors. You can also conduct server-side testing or offline testing (great for interactive kiosks). In addition, developers can use A/B or proprietary testing logic in lieu of Google’s multi-armed bandit approach.

What are your tips for testing website variations with Content Experiments? Please share your thoughts in the comments below. 


Measureful for Google Analytics is Live!

This entry was posted in Measureful and tagged on by .

We’re excited to announce the launch of the first Measureful product! We are now live and analyzing data from Google Analytics (more sources coming soon).

Measureful offers a simple yet powerful solution to the mounds of Google Analytics data your team has to manage and interpret. We automatically monitor and analyze all this data every week, allowing marketing teams to focus on taking action using our weekly reports. Here’s a quick rundown on the latest features –

New Report Design

Insights are only as good as the format they’re communicated in. Historically, Excel has been Measureful __ From Data to Decisions-4the de facto tool to report findings and share insights. It’s been awful.

We believe analytics tools shouldn’t be about analytics, they should be about simple communication of findings. We’ve launched an elegant interface that drives team adoption, understanding and sharing.

Support For Teams

https___www.measureful.com_reports_16#teamGreat teams are informed teams. Measureful now supports your entire marketing team and more; giving every role an easy, inside look into at the most important events on your website and across your channels. You can now invite collaborators from your team or vendors to share in the weekly insights.

Hook Up Multiple Reports

data sourcesMost brands and e-commerce websites have multiple Google Analtyics profiles and properties and we’re happy to announce we now support integration with multiple and different Google Analytics accounts. Whether it’s an international website you want to analyze or a microsite, simply connect and we’ll start automatically analyzing and reporting against that property.

We’ve built Measureful with a clear goal in mind – turn marketing data into a competitive advantage for businesses. We’ve started first with Google Analytics with much more goodness coming the next few months as we integrate with more data sources and roll out some exciting new features. Stay tuned!