web_analytics - eSnips Search

Unica NetInsight funnel by Akin Arikan.jpg in The Web Analytics Graph Collection

This is the visualization for a funnel report in Unica's web analytics solution by the name of NetInsight. From a visual aspect, the most important thing to point out is that this funnel actually does change shape based on the data. Hence the yellow slice is so thin because few people reached that step in the funnel.

By Daniel Waisberg on Aug. 28 2007

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Unica NetInsight overlay with customer data segments by Akin Arikan.jpg in The Web Analytics Graph Collection

This is a cropped image from the overlay UI that comes with Unica's web analytics solution. One thing that it enables is to overlay segments based on registered customer data. In this case for example, where did people click who had a loyalty card vs. those that don't.

By Daniel Waisberg on Aug. 28 2007

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Sales Funnel by Tim Wilson.JPG in The Web Analytics Graph Collection

This is an Excel based, weekly updated sales funnel status. The numbers in the blue shaded areas are measures of how many people/opportunities are in each stage of the funnel at the time the report is produced. The numbers in the white areas and the arrows are the number that moved from one stage to another over the course of the reporting period. The presentation of the data steals a page right out of the book of several web analytics packages that have conversion funnel capabilities.

By Daniel Waisberg on Jul. 19 2007

Source: http://www.secondtree.com

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using-rollingaverages.002.png in Web Analytics Graphs

The top graph use a 52 week rolling average to show user growth in a way less affected by seasonality, cookie deletion and the irregular sizes of months. The lower graph shows the New vs. Return Visitors compared to the 52 week rolling average to illustrate how those 2 segments impact audience growth.

By ihouston on May. 13 2007

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Rolling Averages by Ian Houston.png in The Web Analytics Graph Collection

The top graph use a 52 week rolling average to show user growth in a way less affected by seasonality, cookie deletion and the irregular sizes of months. The lower graph shows the New vs. Return Visitors compared to the 52 week rolling average to illustrate how those 2 segments impact audience growth.

By Daniel Waisberg on May. 13 2007

Source: http://www.visioactive.com

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Retention Rate by Daniel Waisberg.jpg in The Web Analytics Graph Collection

This graph represents retention rates over time. Each line shows a group of users that registered on eSnips during a particular month (starting from October). Every point on this line represents the % of those who remained active a month later, two months later, three months later... up to six months later. The data was collected using Google Analytics (user defined report). Using Excel I calculated one, two and three months retention rate.

By Daniel Waisberg on May. 14 2007

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Timelines_webanalyticaltool.pdf in ashokphil's Business Files

time line for web analytical tool project

By ashokphil on Feb. 28 2007

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Trends over time by Robbin Steif.jpg in The Web Analytics Graph Collection

This chart represents clearly the trend over time of conversion for two parameters. It was constructed using Bizzant Sparkmaker. The red and blue on the left margin were used to obscure the private data.

By Daniel Waisberg on May. 1 2007

Source: http://www.lunametrics.com

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Valuable Sources by Avinash Kaushik.jpg in The Web Analytics Graph Collection

This graph is a "instant insights graph", you look at it and you know what action to take. The foundation is knowing clearly what your goal is. For me it is identifying sources of valuable traffic, with valuable visitors being those that stay longer on the site and read lots of content. The graph shows exactly that, but additionally also shows the size of the traffic from each source. A quick glance tells me exactly where I need to spend valuable marketing $$$! :)

By Daniel Waisberg on Apr. 25 2007

Source: http://www.kaushik.net

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Visitor Engagement by Eric Peterson.gif in The Web Analytics Graph Collection

Because I can change the axis and basis for the size of the bubble, the scatterplot visualization becomes deeply exploratory. I like scatterplots like this because they give me a third (bubble size) and fourth (color) dimension in which to work. Plots like this also let me very quickly identify strange patterns that merit additional exploration.

By Daniel Waisberg on May. 2 2007

Source: http://www.webanalyticsdemystified.com

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