User Flow.. A lot of lines, data and can be extremely helpful!

User Flow.. A lot of lines, data and can be extremely helpful!

As we take another step further into the best that is Google Analytics, I would like to pause and take a look at the evolution and history of Google Analytics to understand past trends that may no longer be relevant and understand the more relevant current trends. 

October 2005 - June 2006: Google Analytics V1 rolls out and with overwhelming response needs to shuts down, but quickly reopens by invitation-only.  

June 2006: First new addition: AdWords reporting  

August 2006:  GA V1 is open to all, no more invitations. Continued changes to the user interface 

April 2007: GA V2 is released. User interface more in line with the Google brand and created a UI that was easier for marketers to utilize versus being only for IT professionals. 

October 2008: GA V3 is released. New reports included  advanced segmentation, custom reporting, and an external API. Became more of a universal tool that opens up more possibilities. 

March 2009: Numerous educational opportunities arose with Conversion University courses and the Google Analytics Individual Qualification Test. Now users can become GA qualified experts. 

April 2009: New features: AdSense integration, marketers 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: GA V4 is released. This new release helped with detecting anomalies in site data and featured intelligent analytics. 

December 2009: Increased accuracy and speed of tracking data. 

April 2011: GA V5 is released. More customizable dashboards, JavaScript interface, and general interface upgrades. 

September 2011:  GA premium is released and new report: real-time 

October 2011: New report: flow visualizations.  

June 2012: New report: Mobile Apps  

October 2012: Universal Analytics is released and allows GA to track a single user across various devices.  

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

(Brouse, 2013) 

This outline wasn't meant to bore you, instead it was meant to give a jumping off point of how GA has evolved and why these newer features are becoming much more important. This is my segue into user flow and I will discuss the importance of this report and how to utilize it effectively. 

What is the Google Report, User Flow? 

This report shows the trajectory and path of the user while on a website.  It shows how the user begin their path on your website and the most common paths they take. GA clusters the groups of pages into segments, which appear as colored blocks. (Braaten, 2013). An example would be a user enters the landing page, clicks on a link to an article and decides to leave a comment for the author of the article and clicks out. 

1. Landing Page 
2. Clicks on article  
3. Submits a comment  
4. Exits website 

This is the user flow of one user - easy enough, right? 

SOPs for User Flow 

Before you begin using this report and extrapolating information from this data there are a few things you should do first: 

1. Segment the data. There are a variety of segmentations: country of origin, users who take an action (convert), who didn't take an action (didn't convert), specified locations and more specific locations. 

2. Click on "Highlight Traffic Through Here" - this will give a clearer look of the data 

3. If you want to get an even clearer vision of the data just from the US click on "View Only This Segment". This does not erase any information instead just filters it. 

4. Utilize the sliders for increased readability and greater detail - it can help! 

Analysis on User Flow Data: 

This data shows the percentages of individuals on the various landing pages and the trajectory of the individuals. There is usually a high drop off point after the first page due to information not found, incorrect website or information was quickly found and the user did not need to further investigate. You will also notice the drop off rate decreases as the users go further into the website and the numbers quickly decline. (Roberts, 2014) What can this data do for the marketer? 

1. Conversion Rate Optimization: As stated above, the User Flow data can show which pages are most popular, where the action takes place (conversions) and what pages have no actions (conversions). Where there is no action taking place could be because of a form error, or the users could be clicking back and for the between sub-sections within the website because they can not find what they are looking for. By identifying potential website hierarchy issues, the webmasters can fix this resulting in higher conversion rates. (Braaten, 2014) 

2. User Friendly Website: Utilizing the same analysis as above, a marketer can take data from drop off rates, users bouncing around to different links and general trajectory can show spots where the website is falling short on information for the user. Since, you can segment users from different traffic sources and devices you can see if your site is mobile friendly or has a poor return rate from social media. (Kerschlbaum, 2013) 

References: 

Braaten, J (2013). How to Turn the Google Analytics Visitors Flow Report Into Your Secret CRO Weapon. Search Engine Watch. Retrieved on February 16, 2015 from: http://searchenginewatch.com/sew/how-to/2295813/how-to-turn-the-google-analytics-visitors-flow-report-into-your-secret-cro-weapon 

Brouse, B. (2014). The Evolution of Google Analytics: A Timeline. Measureful. Retrieved on February 16, 2015 from: http://blog.measureful.com/2014/02/the-evolution-of-google-analytics-a-timeline/ 

Kerschlbaum, J (2013). How to Use Google Analytics Visitors Flow Reports to Improve Conversion Rates. Search Engine Watch. Retrieved on February 16, 2015 from: http://searchenginewatch.com/sew/how-to/2273391/how-to-use-google-analytics-visitors-flow-reports-to-improve-conversion-rates 

Roberts, M. (2014). Making Use of Google Analytics' User Flow and Behavior Flow. Retrieved on February 16, 2015 from: http://mudbugmedia.com/blog/2014/09/23/google-analytics-visitor-behavior-flow/