The more you read/study/implement/collect/analyze metrics and data, more your interest grows in web analytics.
Data is huge but you need to take care what exactly to look for. Thats the key. An interesting case study I am currently thinking is how do the IT staff measure the benefit being acheived by created a knowledge base articles/quick pointers to issues/help webpage. one User is staying on the web page for 50 minutes and another for 5 minutes, which one is earning benefits to the company? also which one is exiting happily from the website?
Think
Wednesday, January 6, 2010
Tuesday, January 5, 2010
My International Publications reaches 5 :)
1) Jain, A. (2009): “E3 – 3 effective ways of increasing test coverage”, International Conference of Information Systems andSoftware Engineering, India 2009.
2) Jain, A. (2009): “Retrospective Analysis and Prioritization Areas for Beta Release Planning Improvement”, 27th Annual Pacific Northwest Software Quality Conference (PNSQC), USA, 2009.
3) Jain, A. (2009): “Sprint Retrospective Checklist – Method and Mechanism to Track Project Health and Dev‐QE Goal”, 9th International Software Testing Conference (STC), India 2009.
4) Jain, A. (2009): “Well Processed, Well Done”, Software Process Improvement and Capability Determination Conference, Finland, TUCS General Publication No. 54, 2009.
5) Jain, A. (2008): “Power of Glide Path: Statistical Approach for Controlling and adding Predictability in a Testing Project”, 8th International Software Testing Conference (STC), India 2008.
2) Jain, A. (2009): “Retrospective Analysis and Prioritization Areas for Beta Release Planning Improvement”, 27th Annual Pacific Northwest Software Quality Conference (PNSQC), USA, 2009.
3) Jain, A. (2009): “Sprint Retrospective Checklist – Method and Mechanism to Track Project Health and Dev‐QE Goal”, 9th International Software Testing Conference (STC), India 2009.
4) Jain, A. (2009): “Well Processed, Well Done”, Software Process Improvement and Capability Determination Conference, Finland, TUCS General Publication No. 54, 2009.
5) Jain, A. (2008): “Power of Glide Path: Statistical Approach for Controlling and adding Predictability in a Testing Project”, 8th International Software Testing Conference (STC), India 2008.
Enter the Mysterious world of Web Analytics
that's my latest love on technology front. Web Analytics, hot happening and interesting subject. Would like to share the 10/90 principle as called out by Avinash Kaushik. (Courtesy: Avanish's blog). I will be sharing more on web analytics practicalities and optimization opportunities and building your websites better for each user.
Goal: Highest value from Web Analytics implementation.
Cost of analytics tool & vendor professional services: $ 10.
Required investment in “intelligent resources/analysts”: $ 90.
Bottom-line for Magnificent Success: Its the people.
The rule works quite simply. If you are paying your web analytics vendor (Omniture, WebTrends, ClickTracks, CoreMetrics, HBX, etc) $25,000 for a annual contract you need to invest $225,000 in people to extract value from that data. If you are actually paying Omniture, WebTrends, HBX etc $225,000 each year then…. well you can do the math.
Most people reading this post probably think this is way overblown or silly or just plain stupid. I can understand that. Here are some of the reasons I have come to formulate this rule:
If your website has more than 100 pages and you get more than 10k visitors a month you can imagine the complexity of the interactions that are happening with your website. Drop in marketing campaigns, a dynamic site, SEM, more pages, more traffic, promotions and offers and you have a very tough situation to understand.
Most web analytics tools will spew out data like there is no tomorrow. We seem to be a rat race, one vendor says I can do 100 reports, the next says 250 and the one after that says I can measure the eye color of people who look at your web pages and on an on. Bottom line is that it will take a lot of intelligence to figure out what is real in all this data and what is fake and what, if anything in the canned reports, is meaningful in all this.
It is a given that if you open most web analytics tools that they show the exact same metrics, almost all of them measured and computed differently! You are going to have to sort this out.
Finally actionable Web Insights (or as I have now copywrited: KIA’s, key insights analysis) does not come simply from ClickStream, you are going to have to have people who are smart and have business acumen who can tie clickstream behavior to other sources of data / information / company happenings.
Goal: Highest value from Web Analytics implementation.
Cost of analytics tool & vendor professional services: $ 10.
Required investment in “intelligent resources/analysts”: $ 90.
Bottom-line for Magnificent Success: Its the people.
The rule works quite simply. If you are paying your web analytics vendor (Omniture, WebTrends, ClickTracks, CoreMetrics, HBX, etc) $25,000 for a annual contract you need to invest $225,000 in people to extract value from that data. If you are actually paying Omniture, WebTrends, HBX etc $225,000 each year then…. well you can do the math.
Most people reading this post probably think this is way overblown or silly or just plain stupid. I can understand that. Here are some of the reasons I have come to formulate this rule:
If your website has more than 100 pages and you get more than 10k visitors a month you can imagine the complexity of the interactions that are happening with your website. Drop in marketing campaigns, a dynamic site, SEM, more pages, more traffic, promotions and offers and you have a very tough situation to understand.
Most web analytics tools will spew out data like there is no tomorrow. We seem to be a rat race, one vendor says I can do 100 reports, the next says 250 and the one after that says I can measure the eye color of people who look at your web pages and on an on. Bottom line is that it will take a lot of intelligence to figure out what is real in all this data and what is fake and what, if anything in the canned reports, is meaningful in all this.
It is a given that if you open most web analytics tools that they show the exact same metrics, almost all of them measured and computed differently! You are going to have to sort this out.
Finally actionable Web Insights (or as I have now copywrited: KIA’s, key insights analysis) does not come simply from ClickStream, you are going to have to have people who are smart and have business acumen who can tie clickstream behavior to other sources of data / information / company happenings.
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