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Introduction to e-Commerce. Web Analytics. Dr. Michael D. Featherstone Summer 2013. Business Metrics and Analytics. Metrics represent raw data Raw Data require analysis by the site owners or management “ BIG DATA ” is the buzzword de ’ jour. Web Analytics. Web Analytics-Big Data.
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Introduction to e-Commerce Web Analytics Dr. Michael D. Featherstone Summer 2013
Business Metrics and Analytics • Metrics represent raw data • Raw Data require analysis by the site owners or management • “BIG DATA” is the buzzword de’ jour
Web Analytics-Big Data BIG DATA REVIEW BYTES KILO BYTES, MEGA-MBYTES, GIGA, TERRA, PETA Review Cloud computing and the cost of storage So a BYTE is a character of information (remember?). This sentence consists of 54 bytes (including spaces). A K- BYTE (Kilobyte) is 1000 characters of information A Megabyte is a million characters of information (1000 K-bytes) A Gigabyte is 1000 Megabytes A Terabyte is 1000 Gigabytes A Petabyte is 1000 Terabytes Here is the numerical representation of a Petabyte 1,000,000,000,000,000 An Exabyte is 1000 Petabytes
Web Analytics-Big Data BIG DATA REVIEW BYTES KILO BYTES, MEGA-MBYTES, GIGA, TERRA, PETA Review Cloud computing and the cost of storage That means massive amounts of data generated from social media, GPS, search, etc. is “stored/saved somewhere “Big Data is used in the singular (Latin scholars, sorry!) and refers to a collection of data sets so large and complex, it’s impossible to process them with the usual databases and tools. Because of its size and associated numbers, Big Data is hard to capture, store, search, share, analyze and visualize. The phenomenon came about in recent years due to the sheer amount of machine data being generated today – thanks to mobile devices, tracking systems, RFID, sensor networks, social networks, Internet searches, automated record keeping, video archives, e-commerce, etc. – coupled with the additional information derived by analyzing all this information, which on its own creates another enormous data set. Companies pursue Big Data because it can be revelatory in spotting business trends, improving research quality, and gaining insights in a variety of fields, from IT to medicine to law enforcement and everything in between and beyond.” http://www.forbes.com/sites/ciocentral/2012/10/04/the-death-of-big-data/
Web Analytics-Big Data BIG DATA REVIEW BYTES KILO BYTES, MEGA-MBYTES, GIGA, TERRA, PETA Review Cloud computing and the cost of storage That means massive amounts of data generated from social media, GPS, search, etc. is “stored/saved somewhere Big Data refers to things one can do at a large scale that cannot be done at a smaller one, to extract new insights or create new forms of value, in ways that change markets, organizations, the relationship between citizens and governments and more (Big Data: A revolutions that will transform)
Web Analytics From IBM ad in WSJ 4-29-13 “According to IBM, there are 5.2 million gigabytes of mobile data generated each day. Not just from phones and tablets but also machine to machine exchanges such as vehicles connecting to utilities (GPS), car makers, and even roads.” IF THAT IS SO --- 5,200,000 X 1,000,000,000 or 5,200,000,000,000,000… That’s 5.2 petabytes of data every day! That is about 2.5 times the total content of all US academic research libraries EVERY DAY. Only from Mobile Data.
Web Analytics • A page view is the simple metric to understand. It’s every time a single page is rendering a browser. • A unique page view is the same as a page view, but multiple visits to the same page during the same visit (see below) are only counted once. So if Bob visits the home page, then the mortgage page, then the home page again, he has racked up three page views, but only two unique page views. • (Why care about the difference? If you sell advertising on your site, you care about raw page views. If Bob visits the same page 10 times during a visit, you don’t care, because you get an ad impression every time. But if you’re actually trying to measure the effectiveness of your site, then multiple views of the same page are not worth noting, so you’d care about unique page views.)
Web Analytics • A visit is a single user session. So Bob, in the above example, has generated a single visit. If he comes back tomorrow, that’s a new visit. (Visits time out after 30 minutes, so if Bob came back 45 minutes later, it would also be a new visit.) • Visitors (also known as “absolute unique visitors”) get a little more complicated. A visitor is the number of unique people that visited during the reporting time period you’re looking at. Remember that every report in GA is limited by a date range. If you’re looking at one month, Bob will only be counted as one visitor during that period, even though he may have visited every day (incurring a visit each time). • A new visitor is a visitor who has not be recorded visiting prior to the time period being viewed. A returning visitor is a visitor who has visited prior to the reporting period being viewed. • Here’s an example that brings them all together — • Bob visits your site on December 12, 2012, viewing 10 total pages. However, he kept returning to the home page, • In this case, Bob has generated one visit, 10 page views, and 7 unique page views (six pages and the home page, counted only once). Bob returns on January 5, 12, and 20, 2013. • If you look at the reports for January only, you would see. • Bob would be a single visitor during that time. He would be classified as a returning visitor, because of his visit in December. (If you looked at the report for December, however, he would be classified as a new visitor in that month). • Bob would also have registered three visits during January, plus any page views and unique page views that he generated during his visits.
This Concludes the Web Analytics Presentation Thank you for your attention
