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Analysing Indian Internet users
Behaviour in Manufacturing
Industry Sector Websites
Vinodh Reddy Chennu
MBA Business Analytics Student (2018-20)
University of Hyderabad
ICBAI 2018 1
Google Analytics
1. From which traffic source users are coming from,
2. From which location users are browsing the site,
3. How many are viewing the webpage,
4. what time users are viewing,
5. what pages users are viewing.
6. Tracking landing page quality and
conversions(goals). Goals include sales, lead
generation, viewing a specific page, or
downloading a file.
Through Google Analytics we can know
ICBAI 2018 2
Dashboard of Google Analytics
ICBAI 2018 3
User Behaviour Metrics
POPULAR TIMINGS
ON A DAY
POPULAR DAYS OF
THE WEEK
WEB BROWSER
USAGE
OPERATING
SYSTEM USAGE
ICBAI 2018 4
Internet Usage on
a day
• During 10th, 11th, 12th
hour as per IST will
get most internet traffic
usage.
• Traffic almost remains
same from 19th to 22nd
hour.
• Between 2nd to 6th hours
we can observe there is
less internet traffic usage.
ICBAI 2018 5
User traffic % on Days
of the week
• The observed data of 42
months data (1st January 2015
(Thursday) to 27th June 2018
(Wednesday)) shown in table,
is cumulated and found the
percentage of page views on
the day of the week.
Day of the
week
% of
pageviews
Sunday 12.48
Monday 14.76
Tuesday 15.68
Wednesday 15.85
Thursday 15.38
Friday 13.9
Saturday 11.95
ICBAI 2018 6
ICBAI 2018 7
Segmenting
days of The
Week based on
Website Traffic
Low TrafficHigh Traffic
ICBAI 2018 8
Web Browser
usage %
2015 2016 2017 *2018*
Chrome 46.72 53.08 63.4 74.75
Opera Mini 13.93 8.97 4.01 2.12
Opera 11.87 8.65 1.77 1.08
UC Browser 11.79 15.53 18.93 10.51
Firefox 7.47 6.42 4.99 4.16
Internet
Explorer
2.68 1.73 1.29 1.07
Safari 1.88 2.8 2.27 2.53
Others 3.66 2.82 3.34 3.78
ICBAI 2018 9
ICBAI 2018 10
Operating System
usage %
2015 2016 2017 *2018*
Windows 46.23 39.77 37.67 34.59
Android 35.16 45.97 57.00 61.04
Linux 13.32 9.62 1.84 0.76
Windows
Phone
1.53 1.14 0.40 0.22
iOS 1.51 2.34 2.29 2.69
Macintosh 0.31 0.42 0.44 0.49
Others 1.94 0.74 0.36 0.21
ICBAI 2018 11
ICBAI 2018 12
References
1. Google Analytics Tool Homepage: https://www.google.com/analytics/
2. Google Analytics Wikipedia page: https://en.wikipedia.org/wiki/Google_Analytics
3. Basic Steps of Web Analytics Process – Wikimedia Commons:
https://commons.wikimedia.org/wiki/File:Basic_Steps_of_Web_Analytics_Process.png
4. Google Analytics: Hour of Day & Day of Week Reports https://www.hallaminternet.com/google-
analytics-hour-of-day-day-of-week-reports/ published on 5th Jan 2007.
5. Firefox Usage – Does the Day of Week Have an Effect? -
https://blog.mozilla.org/metrics/2007/10/10/firefox-usage-%E2%80%93-does-the-day-of-week-
have-an-effect/ Published on 2007 October 10th.
ICBAI 2018 13
ICBAI 2018 14
Questions Time
ICBAI 2018 15

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Analysing Indian Internet Users Behaviour in Manufacturing Industry websites

  • 1. Analysing Indian Internet users Behaviour in Manufacturing Industry Sector Websites Vinodh Reddy Chennu MBA Business Analytics Student (2018-20) University of Hyderabad ICBAI 2018 1
  • 2. Google Analytics 1. From which traffic source users are coming from, 2. From which location users are browsing the site, 3. How many are viewing the webpage, 4. what time users are viewing, 5. what pages users are viewing. 6. Tracking landing page quality and conversions(goals). Goals include sales, lead generation, viewing a specific page, or downloading a file. Through Google Analytics we can know ICBAI 2018 2
  • 3. Dashboard of Google Analytics ICBAI 2018 3
  • 4. User Behaviour Metrics POPULAR TIMINGS ON A DAY POPULAR DAYS OF THE WEEK WEB BROWSER USAGE OPERATING SYSTEM USAGE ICBAI 2018 4
  • 5. Internet Usage on a day • During 10th, 11th, 12th hour as per IST will get most internet traffic usage. • Traffic almost remains same from 19th to 22nd hour. • Between 2nd to 6th hours we can observe there is less internet traffic usage. ICBAI 2018 5
  • 6. User traffic % on Days of the week • The observed data of 42 months data (1st January 2015 (Thursday) to 27th June 2018 (Wednesday)) shown in table, is cumulated and found the percentage of page views on the day of the week. Day of the week % of pageviews Sunday 12.48 Monday 14.76 Tuesday 15.68 Wednesday 15.85 Thursday 15.38 Friday 13.9 Saturday 11.95 ICBAI 2018 6
  • 8. Segmenting days of The Week based on Website Traffic Low TrafficHigh Traffic ICBAI 2018 8
  • 9. Web Browser usage % 2015 2016 2017 *2018* Chrome 46.72 53.08 63.4 74.75 Opera Mini 13.93 8.97 4.01 2.12 Opera 11.87 8.65 1.77 1.08 UC Browser 11.79 15.53 18.93 10.51 Firefox 7.47 6.42 4.99 4.16 Internet Explorer 2.68 1.73 1.29 1.07 Safari 1.88 2.8 2.27 2.53 Others 3.66 2.82 3.34 3.78 ICBAI 2018 9
  • 11. Operating System usage % 2015 2016 2017 *2018* Windows 46.23 39.77 37.67 34.59 Android 35.16 45.97 57.00 61.04 Linux 13.32 9.62 1.84 0.76 Windows Phone 1.53 1.14 0.40 0.22 iOS 1.51 2.34 2.29 2.69 Macintosh 0.31 0.42 0.44 0.49 Others 1.94 0.74 0.36 0.21 ICBAI 2018 11
  • 13. References 1. Google Analytics Tool Homepage: https://www.google.com/analytics/ 2. Google Analytics Wikipedia page: https://en.wikipedia.org/wiki/Google_Analytics 3. Basic Steps of Web Analytics Process – Wikimedia Commons: https://commons.wikimedia.org/wiki/File:Basic_Steps_of_Web_Analytics_Process.png 4. Google Analytics: Hour of Day & Day of Week Reports https://www.hallaminternet.com/google- analytics-hour-of-day-day-of-week-reports/ published on 5th Jan 2007. 5. Firefox Usage – Does the Day of Week Have an Effect? - https://blog.mozilla.org/metrics/2007/10/10/firefox-usage-%E2%80%93-does-the-day-of-week- have-an-effect/ Published on 2007 October 10th. ICBAI 2018 13

Hinweis der Redaktion

  1. Good afternoon everyone, My name is Vinodh Reddy, MBA business analytics student at University of Hyderabad. Prior to this, I have worked as digital marketing executive. Coming to the study In this digital age, the business of any industry sector needs to know their customers and their Behaviour for getting business success. During my period of work as a digital marketing executive, I have observed that users browsing through business web properties of same industry type show common behaviour. For example, entertainment industry sector gets most web traffic during weekends than week days.  because ticket happen on saturday and sundays In this ppt I will be showing u the Study on internet users behaviour in Manufacturing sector industry website.
  2. For conducting this study, need to use tracking tools, there are many tracking tools Mixpanel, adobe analytics, google analytics available in the market, webmasters install tracking code to get insight into website analytics,  I have used Google Analytics tracking tool, Tracking code is implemented on footer of webpage. Google Analytics tracking code is of javscript code. I have implemented this tracking code on ‘Me Mechanical’ popular portal for mechanical engineering students and engineers. Through GA we can know From which traffic source there are coming from, From which location they are browsing the site, How many are viewing the webpage, what time they are viewing, what pages they are viewing. Tracking landing page quality and conversions(goals). Goals include sales, lead generation, viewing a specific page, or downloading a file. 
  3. I have done the study during the data collected during the period 1st January 2015 (Thursday) to 27th June 2018 (Wednesday). A total of 30,71,861 user sessions were recorded in the Google Analytics tracking tool between the period, After applying the filter in the data with Indian users sessions from Global user sessions, a total of 15laks user sessions and 23,53,107 user pageviews were observed and used these user sessions and page views of Indian users data for analysing the Indian user’s Behaviour metrics.
  4. Website analytics data has been extracted from Google Analytics tracking tool and exported to MS Excel format by applying filters which segregates Indian users from worldwide online user’s audience metrics, then custom reports were made on the Google Analytics tool. Then using exported data in Excel format, pivot tables have been generated and then visualizations like bar charts, graphs were plotted, the conclusions were drawn. My study primarily consists of the audience behaviour metrics such as popular timings on a day and popular days of a week where most pageviews browsed by Indian internet users as per Indian Standard Time (IST), percentage usage of type of internet browsers, percentage usage of type of operating system (OS) by Indian users and the change in usage of percentage of browsers, OS over the years from 2015 to 2018.
  5. From the 42 months data extracted from Google Analytics Tracking tool, I have plotted to plot the visualization that shows 24 hours time on x-axis and % of visitors during that hour. we can observe that during 10 AM to 12 PM as per Indian Standard Time (IST) will get most internet traffic usage. Traffic almost remains same from 7 pm to 10pm. From 2 AM to 6 AM we can observe there is less internet traffic usage by Indian users in manufacturing industry sector website.
  6. To find the popular days of the week where the most sessions come, a custom report has been made using past data on Google Analytics using metric group as ‘Page Views’, dimension drilldowns as ‘Day of the week name’.
  7. We can divide the data into three categories as high web traffic, medium web traffic and low web traffic. We can observe Saturday and Sunday, days of the week have the least user sessions. Wednesday, Tuesday and Thursday have the highest user session views.
  8. This segmentation of days of the week based on traffic for manufacturing industry sector websites. Wednesday, tuesday, Thursday get most pageviews, Sunday and saturday get less traffic. This is different for different sectors, Here for entertainmet industry get most traffic on Sunday and Saturday, it almost reverse pattern of manufacturing industry sector website. Sunday, Saturday days of the week get less amount of user sessions traffic for manufacturing sector web properties as weekends are holidays for most of the Business and Industrial sector companies. Tuesday, Wednesday, Thursday observed to get high traffic of user sessions. Planning of social media updates on business accounts can be done on these days instead of weekends. 24-hours graph IRCTC many companies take this as a convenient time in launching new products online and while making social media posts on their business accounts, make their social media updates often in afternoon time to make the most people catch updates instead of posting in late night nights.
  9. Chrome browser has increased its market share from 46% to 74% . There could be many reasons for increase one could be default browser or preinstalled in android OS mobiles.
  10. From the audience metrics, we have identified popular browser internet sessions usage among Indians over the years from 2015 to 2018 and identified popular operating system internet sessions usage over the years from 2015 to 2018. By knowing the share of OS usage by users, companies make their plan of developing apps for the business. If it is a large enterprise with huge customers base to their business can focus on building apps for Android, iOS and Windows platform. It is suitable for small enterprise/startup who customer base is low, initially need to focus on building Android app, as the user base goes on increasing can develop apps for iOS and other platforms. One more thing can be observed here, increase in Android OS market share has also an increase in the percentage of Chrome browser users sessions, as the Chrome browser is pre-installed in most of the Android OS.
  11. If it is a large enterprise with huge customers base to their business can focus on building apps for Android, iOS and Windows platform. It is suitable for small enterprise/startup who customer base is low, initially need to focus on building Android app, as the user base goes on increasing can develop apps for iOS and other platforms. India business need to focus building on Android app instead of going for iOs. In us scenario is different, more % ppl will be using iOs than android, there ppl need to focus on Ios
  12. There are few pf my references for the study of indian internet users behaviour