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Analysis of USER BEHAVIOUR

                www.about.me/eashwar
Some of the
famous tools in
 market for the
analysis of user
   behavior
What Is available with us
                   Real-time user behavior data on the website
                   Server behavior towards the user


our technology with click tale:
Will get the user behavior from the webpage


supported by Splunkst technology:
Will get the server(one) OR servers(many) behavior towards the user on the webpage
HOW?
                WEB LOGS
                Access patterns
   Our JS
   SCRIPT
User behavior
With the page
CLICK TALE JS script

           User Behavior on the page

             Data collected:
             User mouse movement
             Scroll reach
             Hot zone in the page
Web log
 Number of visits and number of unique visitors
 Visits duration and last visits
 Authenticated users, and last authenticated visits
 Days of week and rush hours
 Domains/countries of host's visitors
 Hosts list
 Number total page views
 Most viewed, entry and exit pages
 Files type
 OS used
 Browsers used
 Robots
 HTTP referrer
 Search engines, key phrases and keywords used to find the analyzed web
 site
 HTTP errors
 Some of the log analyzers also report on who's on the site, conversion
 tracking, visit time and page navigation.
Web log
Data collected
LogFormat "%h %l %u %t "%r" %>s %b" common

109.230.246.148 - - [07/Sep/2011:00:00:00 +0800] "POST /ucp.php?mode=register HTTP/1.0"
200 27873
"http://www.sgevoclub.com/ucp.php?mode=register&sid=ea40bb9c24c6fe0b237a98d89335
a2c7" "Mozilla/4.0 (compatible; MSIE 5.5; Windows 95; BCD2000)"



94.228.34.207 - - [07/Sep/2011:00:00:02 +0800] "GET
/forum/read_msg.php?tid=349&forumid=seriousth HTTP/1.1" 200 3751 "-" "magpie-
crawler/1.1 (U; Linux amd64; en-GB; +http://www.brandwatch.net)"
What can be done with the
            information?

See everything visitors do on a website!
Discover what page elements, images and content visitors like and pay attention
to.

Troubleshoot a site quickly and effectively to find frustration points, improve
visitor engagement and help visitors get what they want.

Analyze the performance of the online forms, and all kind of input elements
What are we capable of doing with
      available resources?

         Search
         Mobile OS(touch tracking)
         Multi-domain tracking
         Website speed
         Event tracking
         E-commerce
         User-defined variables
         Forms and fields analytics
Data Analysis Methods
                                                            Funnel visualization
                                                                Click vs View
                                                             Measuring Visitors
                                                              On-page analysis
                                                                 Visitor path
                                                         prospective & retrospective
                                                                    Filters
                                                                    Trends
                                                                  Predictive
                                                               Internal search
                                                             Alerts and flagging
                                                               Custom reports
                                                           Multi-user dashboards
                                                          Customizable dashboards




Source: http://www.aboutanalytics.com/select-tools
                                                            Red titles not completed
Funnel visualization
Click          vs            View


 Clicks vs. Visits
             Visits vs. Visitors
                        Pageviews vs. Unique Pageviews
Measuring Visitors
                  Loyalty                                           Recency                                      Length of Visit   Depth of Visit




http://www.siliconbeachtraining.co.uk/free-resources/google-analytics-measuring-success-using-visitor-loyalty/
Measuring Visitors
Loyalty   Recency   Length of Visit   Depth of Visit
Measuring Visitors
Loyalty   Recency   Length of Visit   Depth of Visit
Measuring Visitors
     Loyalty                 Recency                  Length of Visit                     Depth of Visit




Understanding your customer, listening to them, talking with them, and giving them what they want = Visitor Loyalty
OnPage Analysis
                                     Titles
                              Meta descriptions
                                Meta keywords
                            Page relevant keywords
                               keyword phrases
                                URL extensions
                                   Headings
                               Phrase elements
Measures the performance of a website in a commercial perspective, as data is
characteristically compared against key performance indicators for performance, and
used to advance a web site. This usually includes its drivers and conversions to attain
a high search engine status. To achieve this you actually need to undertake some
onpage analysis and verify each page to guarantee it is correctly optimized for a
targeted keyword.
Visitor path
       A               B                    C    D

A
      1000              250                 90

B


C
        100

D
                                                 500




    A is Home page   D is contact us page
prospective & retrospective
                                                                        STUDY

                A retrospective study is a study that                      A prospective study looks forward in time. For
                looks backwards in time. For                               example, we select a group of subjects and sit
                example, we find people that are already                   around and watch them for a decade. A
                dead and try to figure out why they died.                  prospective study is slow. Unless you are
                A retrospective study is fast. Since the                   studying a rapidly fatal disease, you have to
                subjects are already dead; we just have                    wait years or even decades to accumulate
                to tabulate all the results. The one                       sufficient data to draw any strong conclusions.
                problem is that it's hard to interview a                   On the other hand, live subjects make for a
                dead person.                                               more informative interview.




http://www.childrensmercy.org/stats/definitions/retrospective.htm
Filter
Text string or regular expression that is applied
to incoming traffic data. Filters are used to
manipulate this data before it appears in
Analytics reports, either by excluding certain
page views or by rewriting data to make
reports more readable or relevant.
Predictive Analytics
Improve Our Future Based On What We Know From Our Past
    Business Intelligence
    1) Data cleaning takes 80% of the time -- Analyzing takes 20%
    2) BE aware of GIGO (garbage in, garbage out).
Data cleaning                   Analyzing                       GIGO
It an important procedure       It is done with the             Selective about the
during which the data are        unique our analysis Theory     data you feed into
inspected, and erroneous                                        your model
data are corrected(if
necessary, preferable, and
possible)
 Give me the grace to accept the things I cannot measure, the courage to measure
              the things I can, and the wisdom to know the difference
"If we do this then we start small, see what we find, if it is actionable then build on
 it some more and then check again for actionability. If we don't find actionability
                         then scrap it and do other things."
INTERNAL SITE SEARCH
http://www.kaushik.net/avinash/kick-butt-with-
        internal-site-search-analytics/
What is our plus?
No information loss because all original data is recorded and stored

Every analysis and every filter is executed based on the complete data set and
always in real time. This means that the data is not aggregated (summarized) and
not sampled.

Retrospective segmentation is possible at any time. All data and analyses can be
evaluated retrospectively, on-the-fly, and

at any time with any correlations and links that you wish, and can be filtered
using multiple filters.

Change filter criteria whenever you want and take account of other
analyses, e.g., for the previous month or a different keyword.

          Drill down analytics to the lowest granular level, the individual
 user, i.e., analytics data can be evaluated in terms of individual user behavior.
What is splunk?




Splunk is software to search, monitor and
analyze machine-generated data by
applications, systems and IT infrastructure at
scale via a web-style interface. Splunk captures,
indexes and correlates real-time data in a
searchable repository from which it can
generate graphs, reports, alerts, dashboards
and visualizations.
THANK YOU

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User behaviour

  • 1. Analysis of USER BEHAVIOUR www.about.me/eashwar
  • 2. Some of the famous tools in market for the analysis of user behavior
  • 3. What Is available with us Real-time user behavior data on the website Server behavior towards the user our technology with click tale: Will get the user behavior from the webpage supported by Splunkst technology: Will get the server(one) OR servers(many) behavior towards the user on the webpage
  • 4. HOW? WEB LOGS Access patterns Our JS SCRIPT User behavior With the page
  • 5. CLICK TALE JS script User Behavior on the page Data collected: User mouse movement Scroll reach Hot zone in the page
  • 6. Web log Number of visits and number of unique visitors Visits duration and last visits Authenticated users, and last authenticated visits Days of week and rush hours Domains/countries of host's visitors Hosts list Number total page views Most viewed, entry and exit pages Files type OS used Browsers used Robots HTTP referrer Search engines, key phrases and keywords used to find the analyzed web site HTTP errors Some of the log analyzers also report on who's on the site, conversion tracking, visit time and page navigation.
  • 7. Web log Data collected LogFormat "%h %l %u %t "%r" %>s %b" common 109.230.246.148 - - [07/Sep/2011:00:00:00 +0800] "POST /ucp.php?mode=register HTTP/1.0" 200 27873 "http://www.sgevoclub.com/ucp.php?mode=register&sid=ea40bb9c24c6fe0b237a98d89335 a2c7" "Mozilla/4.0 (compatible; MSIE 5.5; Windows 95; BCD2000)" 94.228.34.207 - - [07/Sep/2011:00:00:02 +0800] "GET /forum/read_msg.php?tid=349&forumid=seriousth HTTP/1.1" 200 3751 "-" "magpie- crawler/1.1 (U; Linux amd64; en-GB; +http://www.brandwatch.net)"
  • 8. What can be done with the information? See everything visitors do on a website! Discover what page elements, images and content visitors like and pay attention to. Troubleshoot a site quickly and effectively to find frustration points, improve visitor engagement and help visitors get what they want. Analyze the performance of the online forms, and all kind of input elements
  • 9. What are we capable of doing with available resources? Search Mobile OS(touch tracking) Multi-domain tracking Website speed Event tracking E-commerce User-defined variables Forms and fields analytics
  • 10. Data Analysis Methods Funnel visualization Click vs View Measuring Visitors On-page analysis Visitor path prospective & retrospective Filters Trends Predictive Internal search Alerts and flagging Custom reports Multi-user dashboards Customizable dashboards Source: http://www.aboutanalytics.com/select-tools Red titles not completed
  • 12. Click vs View Clicks vs. Visits Visits vs. Visitors Pageviews vs. Unique Pageviews
  • 13. Measuring Visitors Loyalty Recency Length of Visit Depth of Visit http://www.siliconbeachtraining.co.uk/free-resources/google-analytics-measuring-success-using-visitor-loyalty/
  • 14. Measuring Visitors Loyalty Recency Length of Visit Depth of Visit
  • 15. Measuring Visitors Loyalty Recency Length of Visit Depth of Visit
  • 16. Measuring Visitors Loyalty Recency Length of Visit Depth of Visit Understanding your customer, listening to them, talking with them, and giving them what they want = Visitor Loyalty
  • 17. OnPage Analysis Titles Meta descriptions Meta keywords Page relevant keywords keyword phrases URL extensions Headings Phrase elements Measures the performance of a website in a commercial perspective, as data is characteristically compared against key performance indicators for performance, and used to advance a web site. This usually includes its drivers and conversions to attain a high search engine status. To achieve this you actually need to undertake some onpage analysis and verify each page to guarantee it is correctly optimized for a targeted keyword.
  • 18. Visitor path A B C D A 1000 250 90 B C 100 D 500 A is Home page D is contact us page
  • 19. prospective & retrospective STUDY A retrospective study is a study that A prospective study looks forward in time. For looks backwards in time. For example, we select a group of subjects and sit example, we find people that are already around and watch them for a decade. A dead and try to figure out why they died. prospective study is slow. Unless you are A retrospective study is fast. Since the studying a rapidly fatal disease, you have to subjects are already dead; we just have wait years or even decades to accumulate to tabulate all the results. The one sufficient data to draw any strong conclusions. problem is that it's hard to interview a On the other hand, live subjects make for a dead person. more informative interview. http://www.childrensmercy.org/stats/definitions/retrospective.htm
  • 20. Filter Text string or regular expression that is applied to incoming traffic data. Filters are used to manipulate this data before it appears in Analytics reports, either by excluding certain page views or by rewriting data to make reports more readable or relevant.
  • 21. Predictive Analytics Improve Our Future Based On What We Know From Our Past Business Intelligence 1) Data cleaning takes 80% of the time -- Analyzing takes 20% 2) BE aware of GIGO (garbage in, garbage out). Data cleaning Analyzing GIGO It an important procedure It is done with the Selective about the during which the data are unique our analysis Theory data you feed into inspected, and erroneous your model data are corrected(if necessary, preferable, and possible) Give me the grace to accept the things I cannot measure, the courage to measure the things I can, and the wisdom to know the difference "If we do this then we start small, see what we find, if it is actionable then build on it some more and then check again for actionability. If we don't find actionability then scrap it and do other things."
  • 23. What is our plus? No information loss because all original data is recorded and stored Every analysis and every filter is executed based on the complete data set and always in real time. This means that the data is not aggregated (summarized) and not sampled. Retrospective segmentation is possible at any time. All data and analyses can be evaluated retrospectively, on-the-fly, and at any time with any correlations and links that you wish, and can be filtered using multiple filters. Change filter criteria whenever you want and take account of other analyses, e.g., for the previous month or a different keyword. Drill down analytics to the lowest granular level, the individual user, i.e., analytics data can be evaluated in terms of individual user behavior.
  • 24. What is splunk? Splunk is software to search, monitor and analyze machine-generated data by applications, systems and IT infrastructure at scale via a web-style interface. Splunk captures, indexes and correlates real-time data in a searchable repository from which it can generate graphs, reports, alerts, dashboards and visualizations.

Editor's Notes

  • #22: More reference:http://www.kaushik.net/avinash/data-mining-and-predictive-analytics-on-web-data-works-nyet/ http://cio.co.nz/cio.nsf/news/8896836F10BBEC61CC25765D006A5561http://www.asterdata.com/blog/2012/04/13/connecting-big-data-with-big-analytics-ensuring-business-success/