1. Think of which segments to configure during the installation phase
2. Raise a Purchase Order when we think of a good segment which was not configured at Implementation.
3. Build the segment in the tag. Our tags are light and powerful; the fact that the segment is not built into the tag is another reason why our solution is fairly easy to implement.

Given how important it is to get segmented data on demand and quickly, minus the hassle of finding budget, our ability to slice and dice every report is a very significant feature for our clients.

[Manoj]: Please tell us more about your Behavior Quotient metric and websites can leverage it. (please provide a screenshot, preferably the one with the radar charts/referrers)

[Dennis Varganyi]: The Behavioral Quotient (BC) is an algorithm which assigns a value to the quality of a visit. This algorithm takes into consideration 5 KPIs:

1. Pages per Visit
2. Entering Visits Rate
3. Pages per Entering Visit
4. Average Duration per Visit
5. Average Duration per Page

This is a relevant metric when comparing different sources of traffic or different periods of analysis or different categories of visitors (male vs female, Canada vs US …).

[Manoj]: Why is the “Degree of Implication” report so useful?

[Dennis Varganyi]: This analysis is very useful for sites who would like to assign a weighted value for specific pages of content or actions.

For example, we can imagine a car manufacturer which has a ‘Design Your Vehicle’ process on their website. The first action is to choose a car. The second is to choose a colour. The third is to choose another option, etc. The last page is to submit a request to be contacted by a dealer. Each action has a degree of (visit) implicated associated with it.

The value is in the application of the results. For example, I can create a segment (on the fly) of all visitors who requested to be contacted by a dealer (highest degree) versus those which only went to the first degree (choose a car, then left). It could be interesting, for example, to understand which source of traffic … or even bought keyword… is associated with visitors which go to the highest degree. Inversely, the source of traffic (or bought keyword) which is associated with the lowest degree is also quite valuable. Both analysis are very valuable for SEO efforts..

[Manoj]: How does your click heat map differ than Google’s or WebTrends solution.

[Dennis Varganyi]: Our Clickzones module offers many features:

• Heatmaps represents mouse clicks with color codes, Red being the most clicked zones (based on mouse coordinates). This module works with all technologies, even full Flash sites. It is also possible to upload page templates to track all product description pages or a news section …
• Heatmaps analysis shows clicks on the page even on non clickable zones, flash movies…
• Overlay gives detailed stats for the clickable items: number of clicks, evolution over the period of analysis and reactivity (Average number of seconds spent on the same page before the click).
• Clicked Zones analyses will show you interactions with zones or page divisions no matter what content is displayed within those sections. It is useful for sites with frequent content changes.

[Manoj]: Your solution also offers the ability to monitor conversations about your brand through a feature called Buzz Watcher, tell us more about that.

[Dennis Varganyi]: Buzz watcher is coming up soon it is still being tested on our development environment. The module will allow you to monitor conversations around your brand or products on big social media networks: twitter, facebook, myspace… as well as your favorite blogs and/or forums.
It will give you general stats on the presence of your brand online, and also show what is being said (analyzing the neutral, positive and negative comments). Because it is also important to know if people are saying good things or bad thing about you.

[Manoj]: Tell us about XiTi Analyzer’s ability to track video, podcasts & RSS

[Dennis Varganyi]: This module measures all types of rich media content: video (including streaming and VOD), music, flash, podcasts, RSS feeds... It tracks all the different actions, play, pause, forward, backward, share... and it allows to create several levels of analysis.

• All types of measured contents (audio, video, animations, podcasts…) whatever the format (swf, mp3, mp4…)
• 14 performance indicators for exhaustive analyses (durations, readings, actions, diffusions, uses…)
• Recognition of diffusion modes (clip or live), even on “external” sites (blogs, sites of video divisions…)
• Thorough analysis of visitor actions (sharing content, put in favourites…)
• Personalization of analyses on 5 levels of tree structure (possibility of integrating personalized measurements)
• Automatic check of content reading (by sending of a hit of every five seconds)
• Segmentation of data and real time
• Fast and easy Implementation whatever the technology of the multi-media reader (Javascript, Flash, AS3…)

Labels: Web Analytics

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