Ever since I started working professionally with web development, I've been interested in how we can improve the user experience by learning from the current users / visitors behavior. How it's possible to turn raw statistics into actionable insights - and maybe even optimize their experience automatically.
One of the first companies I worked for was Mondosoft - a site search vendor. There, I was part of a team that spearheaded our efforts into search behavior - already back in 2001 - and launched a product called 'Behavior Tracking' that (among other things) automatically would learn synonyms and common spelling mistakes from the users - and improve the search from that.
Later, within Episerver, I've spend a lot of time experimenting with (and making prototypes of) various behavioral mechanisms that aims at improving and personalizing the online experience based on behavior. For instance with content recommendations, automatic visitor segmentation and the Self Optimizing block that does real-time multivariant testing and automated improvements.
Relevant Blog Posts
Profile Manager v2 - KQL edition
We just launched a new version of the online tool Profile Manager - a tool that makes it easier for developers and content analysts to work with Episervers Profile Store. The new version lets you easily try out different KQL queries and build Filter Definitions with them.
Getting more Insight (pun intended) into Episerver Profile Store
Profile Store, Insight, Tracker, Advance - Episerver offers a myriad of different (but connected) REST services for managing and tracking your visitors and prospects. It can be slightly confusing at first - and some of the documentation might be a tad misleading - but once you get the hang of it, they are really powerful tools. I've recently had a chance to explore them in depth. Here is what I've learned so far.