How Did I reduce Bounce Rate from 87.55% to 1.19%, in a span of 3 months?

Bounce Rate being one among few site health indicator metrics, it is always challenging to control and correct bounce rate either in case of e-commerce or an information blog.

Before listing down 5 point strategy, down load case study on Bounce Rate Metrics from metricsmania.com resource center.

It is simple and straight forward I just followed 5 point strategy to control and correct bounce rate in my blog. They are as follows:

 

1. Choose Your Digital Marketing Channels Judiciously

All marketing channels are not suitable to your business model, product and Services. Choosing a right set of channels is wise step towards reducing bounce rate. Because, irrelevant channels bring bouncing visitors to your website.

2. Know Your Audience Persona

‘Persona of your prospect’ figures out who is your audience who fetch you the economical value and benefit out of your goods and services. Next set of audiences could be researchers who may visit your website to learn and take way some goodies. In fact they are patrons, who may be your brand loyal and spread awareness about your business.

3. Research.. Research..Research

Your front line digital marketing channels SEO, SEM, Social Media, Referral and affiliate programs fetch you major chuck of visitors. But how strong your keyword research? How robust your referral and affiliate programs?

 Have you addressed Who, Why, When, What and How questions during your Branded, Non Branded and Negative keyword research phase, affiliate and referral marketing strategy.

4. Think Why Should Visitor Move to Next Page

May be the right and honest answer to this question would solve 95% of your Bounce Rate correction. Every move in the website should be mutually beneficial to you and your visitor.

5. Pass variable to Java Script method in Google Analytics

Google Analytics offers a technical solution to tackle a single 1X1 pixel image transmission by implementing google analytics event method as shown below :

ga(send, event, event_category, event_action, event_label, event_value, non_interactive)

The last parameter non_interactive should be set to the boolean value ‘TRUE’.

Google Analytics View Set up and Configuration – Best Practices

Google Analytics has evolved from neonatal to very matured stage by launching ‘Universal Analytics’. The journey from Web Analytics 1.0 to Web Analytics 2.0 has brought a sea change in Google Analytics Tool implementation and configuration. A web analyst and digital marketer, being a business catalyst should be aware of industry best practices. I have made an attempt to consolidate and present relevant best practice in Google Analytics Best Practices Series -1. Thank you so much for visiting , read on and let me know your opinion.

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Google Analytics view being fundamental building block of Google Analytics Account needs a special attention for righteous implementation. Views are required to serve your long term data analysis requirements. Any mistake in configuring views result in Fundamental Mistake. The following are Google Analytics view set up and configuration  best practices to achieve data quality in web analytics.

1.    View Configuration Best Practice – 1: Default page field configuration.

A default page is one which loads when a user enters only the domain name of site into address bar. In fact www.metricsmania.com/ and www.metricsmania.com/index.php are technically same as the server returns home page only. But according to Google Analytics ‘/’ and index.php are two different page views. So Google Analytics registers page views under two dimensions as shown below:

Users who type www.metricsmania.com, would be registered under ‘/’ and users who type www.metricsmania.com/index.php would be registered under ‘index.php’ as shown under.

But how to determine the technology on which web site is built and what pages does server return? In some situations it is not easy to learn what technology has been used to build the web pages, because developers may hide the details. No worries! I have listed down few useful tools to determine the technical details of website. These following tools help you to determine the type of the page server returns.

Online Tools

•    www.builtwith.com
•    www.domaintools.com
•    www.netcraft.com
•    www.w3techs.com
•    www.similartech.com

Firefox addons:

•    Wappalyzer – CMS, frameworks/libraries, e-commerce, message boards etc.
•    Domain Details – IP, country and webserver details
•    Library Detector – Javascript libraries in use

Chrome Extensions:

•    Wappalyzer
•    SimilarTech
•    PageXray

Bookmarklets:

•    WTFramework – shows Javascript framework in use

Once you are sure with type of web page your server returns, enter the details in as shown below:

Google Analyitcs Default page configuration Best Practice at view level

Google Analytics Default page configuration at View Level- Best Practice 1

 

2.    View Configuration Best Practice  – 2 : Exclude URL Query Parameters

URL parameters are very robust features of web 2.0 framework. Web 2.0 has seamless ability to create dynamic pages to respond to complex http request in client-server architecture. Server side scripts (PHP, ASP) append URL parameters to create dynamic web page on the fly.

URL parameters are appended after ‘/? ‘ in the URL, for example in the URL www.mywebsite.com/?pid=001#sessionid=1,  pid=001#sessionid=1 is URL parameter appended by servers to create dynamic pages.

Server returns numerous URL parameters for single dynamic page, whereas GA generates various page views for single page. Page views junk data just gets inflated! hence these URL parameters are of no use to web analyst, whose job is to construe some meaningful insights. So dispose the junk, which has no value to analyze.

To identify URL Parameters it takes some time or you can go to ‘All Pages’ report of Site Content in Behavior section, enter  ‘\?’ in the table filter as shown below to list down possible URL parameters.

Exclude URL Parameters from All Pages report in Google Analytics

Excluding URL Query Parameters from Site Content Reports in Google Analytics

 

The possible URL parameters could be sess,var1, var2, pid,sessid, token.

In case you do not have patience to wait and update URL parameters, apply the following filter.

Filter name: Remove Query Parameters from URI

Filter type: Search and replace

Filter field A: Request URI

Search String: ^([^\?]+)\?.*

Replace String: /

Case Sensitive: NO

 

Google Analytics Property level Roll up Reporting : Google Analytics Best Practices

Google Analytics has evolved from neonatal to very matured stage by launching ‘Universal Analytics’. The journey from Web Analytics 1.0 to Web Analytics 2.0 has brought a sea change in Google Analytics Tool implementation and configuration. A web analyst and digital marketer, being a business catalyst should be aware of industry best practices. I have made an attempt to consolidate and present relevant best practice in Google Analytics Best Practices Series -1. Thank you so much for visiting , read on and let me know your opinion.

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Roll up or Aggregation of data into one Google Analytics Account is method of consolidating web analytics data into one, to derive the aggregate insights into website performance.

When to implement Google Analytics Property Level Roll up reporting?

In case you have two or more websites which are dedicated to different regions, for example you have dedicated website for Spain, Portugal, UK and Germany. Whereas individual google analytics properties are collecting data pertaining to their respective websites. Now you want these individual google analytics properties to be consolidated into one.

Roll up Property Reporting in Universal Analytics

Roll up Property Reporting in Universal Analytics

Note: Google Analytics Premium has dedicated property level Roll-up Reporting under Audience section to capture data from multiple trackers or different source properties to give consolidated insights of customer behavior on different websites of single business group.

Work Around

Google Analytics Standard Reporting does not support Property level roll up by default, you need to work around as following:

Create a property ID for a fictitious or virtual URL, as I have mentioned in one of my post GA does not check for the very existence of your website!

Here I name it as rolluprop.com is virtual URL and corresponding property ID is: UA-22222-1

You have other website and corresponding  PropertyIDs as below:

www.germanwebsite.com        :   UA-33333-1
www.spanishwebsite.com        :   UA-44444-1
www.portuguesewebsite.com  :   UA-55555-1
www.ukwebsite.com                  :   UA-66666-1

Google Analytics allows multiple trackers on a web page. A tracker can be assumed as camera set on page. Here we place two trackers / cameras on pages of above mentioned 4 regional websites.

A.    Master/Primary Camera   :  UA-22222-1
B.    Website specific / Secondary Cameras:  UA-33333-1, UA-44444-1 , UA-55555-1, UA-66666-1.

Note: The fundamental code customization with GA asynchronous code to implement roll up property is to create master Tracker: UA-22222-1 and assign a reference name to it, in our example we shall name it as: roll-up-prop

Here we go with actual code customization:

1. www.germanwebsite.com :        UA-33333-1

<script>
(function(i,s,o,g,r,a,m){i[‘GoogleAnalyticsObject’]=r;i[r]=i[r]||function(){
(i[r].q=i[r].q||[]).push(arguments)},i[r].l=1*new Date();a=s.createElement(o),
m=s.getElementsByTagName(o)[0];a.async=1;a.src=g;m.parentNode.insertBefore(a,m)
})(window,document,’script’,’//www.google-analytics.com/analytics.js’,’ga’);
ga(‘create’, ‘ UA-22222-1’, {‘name’: ‘ roll-up-prop ‘});
ga(‘create’, ‘ UA-33333-1’);
ga(‘ roll-up-prop’, ‘pageview’);

ga(‘send’, ‘pageview’);
</script>

2. www.spanishwebsite.com        UA-44444-1

<script>
(function(i,s,o,g,r,a,m){i[‘GoogleAnalyticsObject’]=r;i[r]=i[r]||function(){
(i[r].q=i[r].q||[]).push(arguments)},i[r].l=1*new Date();a=s.createElement(o),
m=s.getElementsByTagName(o)[0];a.async=1;a.src=g;m.parentNode.insertBefore(a,m)
})(window,document,’script’,’//www.google-analytics.com/analytics.js’,’ga’);
ga(‘create’, ‘ UA-22222-1’, {‘name’: ‘ roll-up-prop ‘});
ga(‘create’, ‘ UA-44444-1’);
ga(‘ roll-up-prop ‘, ‘pageview’);
ga(‘send’, ‘pageview’);
</script>

on similar lines customize the code in www.portuguesewebsite.com    (UA-55555-1) and www.ukwebsite.com (UA-66666-1).
If you customize as I have explained above your roll up property implementation is done !.

Remember, the rolluprop.com is a property name created for the sake of getting a propertyID UA-22222-1. As I have mentioned above you can create virtual propertyID, even though the website does not exist.

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Google Analytics Multiple Trackers Implementation Best Practices

Google Analytics has evolved from neonatal to very matured stage by launching ‘Universal Analytics’. The journey from Web Analytics 1.0 to Web Analytics 2.0 has brought a sea change in Google Analytics Tool implementation and configuration. A web analyst and digital marketer, being a business catalyst should be aware of industry best practices. I have made an attempt to consolidate and present relevant best practice in Google Analytics Best Practices Series -1. Thank you so much for visiting , read on and let me know your opinion.

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Google Analytics supports multiple trackers on a web site.  But what are the scenarios we need to consider for multiple trackers is a million dollar question. It has been a usual practice of most web analyst to implement Google Analytics multiple trackers for better understanding of different parts of the website or multiple websites of multiple brands of a business group to analyze customer behavior on website.

Are there any caveats to obey? Are there any best practices established so for by our Web Analytics Community? To answer this question there is very less information available on internet and this million dollar question is very much falls in Strategic decision of Digital Marketing. So there are very less disclosures on this topic.

Google Analytics Multiple Trackers

Google Analytics Multiple Trackers

Well, when I started my research on finding answers for this question I have ended up in drawing few frameworks to guide in deciding about this million dollar question i.e. to go or not to go for Multiple Trackers.

Before going for this decision I strongly assume that you have following fundamental factors.

A.    You have defined a killer process for Digital Marketing.
B.    You know Traffic Sources to your website.
C.    You have a clear vision of different parts of website and their individual importance. Here different parts of website I meant are Blogs, Forums, and sub domains etc., which drive relevant traffic to the website.  Probably, it is very important factor because; Blogs, Forums and Sub domains can be indispensable or independent digital marketing entities. Either indispensable or independent plays very crucial role in finding the answer to go for single tracker or multiple tracker implementation.

Following are few instances where we can consider Multi Tracker implementation:

1.    Size matters!
If your website is relatively big whereas pages could be 3000 or above implement different trackers for different parts of the website. A website with 3000 and above pages approximately needs different section to drive traffic. Even if your website spans across sub domains and top level domains, you can implement multiple trackers for better insights. According to my experience, most of the small and middle level companies fall under this category, where their requirement for Web Analytics Data insights is growing. But these small and middle level always stumble in hiring a right person or right web Agency for this task.

Google is generous in giving as many Property ID as you require, but do we have necessary resources ( people, process) to draw necessary insights into data dump gathered by multiple trackers. In fact many a times we ignore the importance of natural resources ( Free Google Analytics data dumps).

2.    Data Sampling
A self-Imposed Constraint by Web Analytic Tools.  If your marketing decision mechanism is hurt by insufficient web analytics data, probably you are the victim of Data Sampling. Read out my blog post Data Sampling: How to achieve Data Accuracy from Sampled Data?

If your website is reaching the threshold of data sampling, and you do not want data to be sampled out, then multiple trackers are the best solution to avoid data sampling. Here, you have identified different sections of website, which is to be implemented with different tracking ids.

It is worth to take a note that, Data Sampling is always done at Property level. So multiple trackers helps you to avoid reaching the sampling threshold to the greater extent, thereby you have greater chances of analyzing Un sampled data.

3.    Persona of Visitor or Visitor Segmentation at Root Level
Website serves wide spectrum of visitors, not all visitors contribute revenue or lead acquisition to your business. Visitors can be classified into various segments like researchers, blog content consumers, forum participators, value contributors etc. Driving all visitors to a single tracker website results in.

1.    Data Sampling thresh hold is reached and data sampling is triggered.
2.    Inflated sessions and page views
3.    Inflated metrics in Frequency and Recency reports
4.    Inflated Engagement metrics in Engagement Report
5.    Lowest conversion rate.

Among above all metrics Frequency and Recency, Engagement and Conversion rate metrics are foundational metrics which throw light on real business results. If these metrics are inflated by driving all visitors (via researchers, blog content consumers, forum participators, value contributors) other than value contributors to website, your webs analytics tool is a source of irrelevant consumer Analytics generating system.

In general following type of websites are best candidates for considering multi trackers for Visitor Segmentation at root level.

1.    E commerce websites with huge customer base.
2.    Company Websites with Research and Development services.
3.    University websites.
4.    Websites who drive traffic by Content Marketing.
5.    Web sites with blog as pivotal point of Content Marketing Strategy. Where blog drives traffic to website.
Final Thoughts:
Google Analytics Premium has dedicated property level Roll-up Reporting under Audience section to capture data from multiple trackers or different source properties to give consolidated insights of customer behavior on different websites of single business group.   But what if you have standard Google Analytics privileges, check out Roll up Property implementation with Universal Analytics tracking code.

2 Simple ways to secure your Google Analytics Property ID from Hijakers

Google Analytics has evolved from neonatal to very matured stage by launching ‘Universal Analytics’. The journey from Web Analytics 1.0 to Web Analytics 2.0 has brought a sea change in Google Analytics Tool implementation and configuration. A web analyst and digital marketer, being a business catalyst should be aware of industry best practices. I have made an attempt to consolidate and present relevant best practice in Google Analytics Best Practices Series -1. Thank you so much for visiting , read on and let me know your opinion.

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Google Analytics is built on Java script, the client side high level scripting language . It is an open source scripting language developed by Netscape. Javascript code can be viewed by any one by viewing at source code of the web page. Hence, your Google Analytics Code or asynchronous Java script code can be easily viewed along with your Google Analytics Property ID i.e. UA code.

‘Hijackers can copy your UA code, place in their website to skew and mess up your Google Analytics data.

Google Analytics Property ID

Following are the few ways you can absolutely secure your Google Analytics Property ID.

1. Google Analytics Filter Implementation.

Implementing following ‘Include Visit / Traffic to Host’ will ensure that traffic to www.metricsmania.com will only be included in google analytics reports.

Include Visit / Traffic to Host Name Filter

Include Visit / Traffic to Host Name Filter

 

2. Migrate to Google Tag Manager.

Google Tag Manager allows you to implement and customize all your Google Analytics code in your Google Tag Manager account so that all your critical codes
are not disclosed to outside world.

Google Analytics implementation and customization is totally off from the website. Thanks to Google Tag Manager, now you can implement and customize all
your digital marketing codes like

1. Adwords Conversion Tracking code

2. Adwords Remarkting

3. DoubleClick Floodlight Counter

4. DoubleClick Floodlight Sales

4. Google Analytics

5. Adwords Remarketing Tag

6. AdRoll Smart Pixcel

7. Display Ad Tracking

8. Custom HTML Tag

9. Custom Image Tag

Many more other tags.

Series – 1: Google Analytics Accounts, Properties and Views implementation Best Practices

Google Analytics has evolved from infant to very matured stage by launching ‘Universal Analytics’. The journey from Web Analytics 1.0 to Web Analytics 2.0 has brought sea change in Google Analytics Tool implementation and configuration. A web analyst and digital marketer, being business catalysts, should be aware of industry best practices. I have made an attempt to consolidate and present relevant best practices in Google Analytics Best Practices Series -1. Thank you so much for visiting my blog. Read on …..

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Google Analytics Accounts Best Practices

To own a Google Analytics account all you need is an email address (not necessarily gmail account) which is being associated with a Google Account.

A ‘Google Account’ is typically google services like :

  • Google Maps
  • Google Drive
  • Blogger
  • Google Wallet
  • Google adwords

You can associate any email address or gmail address with a google account to open google analytics account.

Google Analytics Account Limitation

1. You can open 100 Google Analytics Accounts per google login/account, earlier 25 Google Analytics account was the limit per Google Login.

2. If you exhaust 100 Google Analytics Account limit, take up another google account and go ahead with another more 100 accounts

3. Ask your clients or colleagues ( in Digital Marketing Agency scenario) to own a Google Analytics Account and give full access permissions. This way you can go limit less in creating Google Analytics Account.

Best Practices

1. It is always a best practice to dedicate one account for a website.

2. If you have more than one website belonging to same client you can track them in one single account. It is always advisable to open a separate account keeping the dynamics of business to meet any eventualities.

Google Analytics Account Structure

Google Analytics Account Structure

Properties

Properties are websites or apps which can be tracked in Google Analytics Account. A Google Analytics Property is a combination of Alpha Numeric always begins with UA-XXXXX-Y

Anatomy of Property ID:

UA-XXXXX-Y

UA : stands for Urchin( Google acquired technical know-how from Urchin, later on changed to Google Analytics) also it can be understood as Universal Analytics( It is my interpretation not Google’s!).

XXXXX : It is Google Analytics account ID.

Y : It denotes 1st Property in the Google Analytics Account i.e. ( XXXXX)

Do you know ?

1. Google Analytics creates property ID for an existing or non-existing websites. Google Analytics does not validate the existence or non existence of website during the PropertyID creation. It only validates when data actually flows into Google Analytics Account.

2.Your Property ID is easily accessible by anyone looking at your Source Code of webpages. Hijackers can skew your data by stealing your Property ID. Beware of your PropertyID thieves. How do you secure your Property ID from thieves?

3. Google allows you to create Multiple Trackers for your Single Website. Where each Property ID can be used to track separate parts / directories of your website. Google Analytics supports multiple trackers / Property IDs on website in both free and premium versions. But what are the Best Practices to be followed to implement multiple trackers. Do not miss to read the scenario based approach to implement multiple property ids on your web page. Check out, what are the situations we need to consider for multiple Google Analytics tracker implementation?

4. Google analytics also allows you to create multiple trackers on individual webpages. Where as each unique tracker sends data to different stake holder owning his own google analytics account set up.

 As mentioned above multiple trackers allows you to track either different parts of website or individual pages across website, the data needs to be aggregated at one place to derive insights. Check out Roll up Property Reporting web analytics data aggregation.

Google Analytics Views

What is a Google Analytics View?

A view is customized container of your reports. A view can be customized to store required set of reports with relevant website analytics data /   information pertaining to a part of a website or whole website. Views can be customized to receive relevant information by applying filters.

Google Analytics view is your long term Web Analytics Data Management Framework. Web Analysts need to categorize Web Analytics data into 2 important categories i.e. Short term and long term data requirements or Data for continuous analysis and Data for adhoc analysis.

Google Analytics views falls in Long Term Data requirement or Data for continuous analysis category of your Web Analytics Data Management Framework.

As I have observed Google Analytics implementation takes a wrong turn at view level implementation. Views are being a fundamental building blocks any mistake at this level is Fundamental Mistake.

Web Analytics Tools fundamentally misguide you by un realistic and irrelevant information and on other hand we mess up the data by not following certain best practices right from this stage.

Before discussing view implementation check out some interesting information on Google Analytics Views:

1. Google Analytics creates a view by default and this default view is named as ‘All WebSite Data’. This name can be altered to any convenient name as far as you can identify it as ‘Default View’.

2. Default view is a dumping yard in which raw / unfiltered data is dumped for future reference. Here, it is advisable that do not apply a filter. So your ‘Default View’ remains unfiltered view.

3. Google Analytics views collect information from the day of creation and onward. No historic data exist.

4. When view is created you need to set at least 5 basic following configurations. Among 5, first 2 are important for all views.

Set your default home page as index.php / index.html/index.aspx

Eliminate URL parameters

Enable Internal Search Option

Connect Webmaster Tool

Enable E Commerce option [ if your website is E- commerce based]

Check out  Google Analytics View implementation and configuration best practices  for better understanding of Google Analytics view configuration .

5. Views are associated with Property ID in Google Analytics Account. Each property can associate with  25 views. Read out Google Analytics Accounts limit per login ID raised from 25 to 100, to work around with 100 account limitation for per login id.

6.How many views do you create? There is no thumb rule to follow here, but a best practice is to create at least 3 views as follows:

  • All web site Data [ Default view]
  • Test view
  • Reporting view

Views are the fundamental building blocks of Google Analytics, which helps to segment your data right at view level. The best practice to decide how many and what views to be created should be decided with reference to segments identified in ‘Digital Marketing and Measurement Plan’.

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