5 Awesome Google Analytics Tips

“Marketing without data is no marketing at all”

Makes sense isn’t it?
Businesses are going online, and it becomes imperative for businesses to monitor user behavior on their websites and landing pages in order to make better informed decisions.
Google Analytics just does that. By placing a small Google Analytics code on a website or App, a business can collect, analyze, interpret and implement data on how users actually behave with these.
Most of businesses already have the Google Analytics code installed in their websites. (Don’t have it yet? Read here to get started)

My post below describes 5 tools within Google Analytics which gives commendable insights to a user behavior.

1. UTM Parameters :

   Short for Urchin Tracking Module, this parameter helps track the source, medium, term, content and campaign name of a visit to a site from another online property.
   
   Here is the key :

• Medium defines the type of origin that triggers the visit. A cost per click campaign, an email activity, a social media platform etc.
• Source defines the origin that triggers the visit from the medium. Google, Yahoo, Facebook etc.
• Term identifies the keywords which triggered the visit. Only applicable for paid campaigns.
• Content defines the ad copies/content which triggered the visit.
• Campaign Name defines the specific campaign that a business is promoting that triggered the visit.

For example,

A user saw one of the Spring Collection Ads on Google when he was searching for shirts for men over Google.

A Sample UTM URL will look like :
www.example.com/?utm_source=google&utm_medium=cpc&utm_term=buy%20shirt%20online&utm_content=discount%20voucher&utm_campaign=spring%20collection

The UTM URL builder can be accessed from here.

2. Comparison to Site Average View :

This is one of my personal favorites. It not only gives a pictorial representation of the data I am viewing, but also gives how does each metric / data row performs against all others metrics /data rows.
Hence, winners (green) and losers (red) segregated in an instant! 

For example,

For the sessions above, Organic Search, Direct and Referral Sources perform better than the site average than Paid Search, Display, Social and Other.

3. Goals :

This is perhaps the most important element for any business wanting to calculate RoI of the visitors on the website.
Goals are tags placed on the widgets/buttons/pages on the website that defines a user activity critical to the business.

For example,

A visitor clicking on “Submit” button of the Application Form of a college.
A visitor clicking on the “Toll Free Number” on the website when viewing it from a mobile.
A visitor successfully completing a transaction on an e-commerce store.

Goals those are synced with ecommerce functionality in Google Analytics track the value of the transaction automatically. (The developer of the e commerce website needs to however, customize the goal code with an ecommerce snippet).
Other goals can be labeled with monetary figures.

For example, successful submission of an application form might be worth Rs 500 to the college.

The below example shows goals recorded for 2 goals set : 

> Visitors on the contact page of the website.
> Visitors submitting the contact form on the contact page.

Read here on how to set up goals in Google Analytics

4. Segmentation by Visitor Type:

Ever wondered how do visitors who browse a website and do not convert are likely to behave versus visitors who browse a website and convert?
This is exactly what segmentation in Google Analytics does.

Here is how :

Notice the difference in behavior in monetized and non – monetized visitors with respect to different metrics (users, sessions, etc). Also notice, that monetized users are in the age group of 25- 34 years of age vs non-monetized users who are in the age group of 18-24.

Read here on how to set up custom segments

5. Multi- Channel Funnels :

Google Analytics allows businesses to track the conversion path of visitors who have converted on the website. Google Analytics by default works on the “last click” model which means Google Analytics credits the last click source/ medium for the conversion irrespective of other source or medium clicks before.

For example,

If a visitor saw an ad over Facebook, visited the website later via Google organic listings and eventually bought a product online by clicking on a Google Ad, the credit for the purchase shall be credited to the Google Ad. All other media/sources are termed as assisted conversion channels.

This data help in accounting the effectiveness of branding activities.
Branding activities rely heavily on Social Media. Direct conversions from Social Media are economically insensible to project. However, if good number of conversions through the MCF analysis demonstrates that these have Social Media Platforms as assisted conversions, it broadly implies that the branding campaign of the business bears fruit.

Read here more on the different Attribution Models in Google Analytics here

These are tools that I love to test Google Analytics with.
How do you like doing it?

Please feel free to drop comments /inbox messages for any suggestion, feedback or consultancy.