Google Analytics Formula
Google has reversed its decision to update the "average time" formula in Google Analytics, the search engine reveals.
A post on the Official Google Analytics blog explains that the formula had been changed to ignore visitors who view only one page before leaving the website.
In this way, senior manager Brett Crosby argues that the average time statistic became a measure of how long "engaged visitors" spent navigating the site.
"However, many of you prefer the original calculation - the total time on site for all visits divided by the total number of visits," he writes.
Historical data already stored in Google Analytics accounts has been updated to reflect the reversion to the former method, Mr Crosby adds.
Meanwhile, a bug which meant the number of unique visitors was sometimes displayed by summing the daily totals - meaning users were classed as 'unique' if they returned the next day - has also been ironed out, according to the post.
The news follows an upgrade to Website Optimiser which allows for different versions of a web page to be supplied at random in order to gauge which achieves the greatest response from customers.
A post on the Official Google Analytics blog explains that the formula had been changed to ignore visitors who view only one page before leaving the website.
In this way, senior manager Brett Crosby argues that the average time statistic became a measure of how long "engaged visitors" spent navigating the site.
"However, many of you prefer the original calculation - the total time on site for all visits divided by the total number of visits," he writes.
Historical data already stored in Google Analytics accounts has been updated to reflect the reversion to the former method, Mr Crosby adds.
Meanwhile, a bug which meant the number of unique visitors was sometimes displayed by summing the daily totals - meaning users were classed as 'unique' if they returned the next day - has also been ironed out, according to the post.
The news follows an upgrade to Website Optimiser which allows for different versions of a web page to be supplied at random in order to gauge which achieves the greatest response from customers.
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