Online Analytics in Action: Footprints in the dark


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“When I can’t see clearly, I know you’re still there.

When darkness swarms around me, I know you’re still there.”

When it comes to online footprints we are starting to see the light and it’s old technology that is slowly illuminating those footprints and tying the steps together effectively so analytic consultants like myself may convert that data into actionable insights.

Many online tracking systems predominantly use javaScript tags and cookies to track online behaviors and tie individual user’s sessions together over time. This was a nice way to track 10 years ago when all devices that accessed the Internet were hard-lined computers with out of the box browsers with JavaScript and cookies auto-enabled. However, many different devices now-a-days access the Internet (some of which do not handle JavaScript and cookies) and consumers are becoming more Internet and browser savvy so there is a growing trend to disenable cookies and JavaScript.

So what’s the answer? All Online Analytic providers understand this issue and are working on resolutions but one solid option in my opinion, in terms of data capture alone, is AtomicLabs‘ PION solution. PION is able to track online behaviors by integrating with your current Online Analytic providers, through web logs and through their secret sauce, packet sniffing. Packet sniffing has been around for a long time and is a process which passively listens to network traffic without the need to tag web sites with programs such as JavaScript. PION takes it to another level in being able to not only listen in but also easily capture the data, tie user behaviors together (sessionize) and load the data into any type of database for quick use in reports and subsequent analyses.

This is not to say that your Online Analytics vendor is not doing a good job as those solutions provide very robust business intelligence environments. PION, I believe, provides a very nice augmentation service to capture data seamlessly and capture additional data (especially mobile) and make it usable quickly within ALL channels.

Republished with author's permission from original post.

Roman Lenzen
Roman Lenzen, Partner and Chief Data Scientist at Optumine, has delivered value added analytical processes to several industries for 20+ years. His significant analytical, technical, and business process experience provides a unique perspective on improving process efficiency and customer profitability. Roman was previously VP of Analytics at Quaero and Director of Analytics at Merkle. Roman's education includes a Bachelor of Science degree in Mathematics from Marquette University and Masters of Science in Statistics from DePaul University.


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