Dette er CodeArts blog. Vi deler thought-leadership og tekniske tips og tricks - men som regel på engelsk.
Preview multiple Visitor Groups directly while browsing your Optimizely site
Visitor groups are great - it's an easy way to add personalization towards market segments to your site. But it does come with it's own set of challenges if used intensively. For example it can be hard to predict how any given page will look for visitors with a specific combination of visitor groups - and viewing it in a proper way often requires more than what you see in the quick preview mode. Here's a bit of code that will help you out.
Adhering to Consent with Cookie Information for Episerver
In the EU the past year has added even more rules and regulations to which cookies can be set, which data can be collected and which consents are needed for it. While it may not be tricky to add a basic consent box, adding one that adhere to all the proper legislation and then follow the consents given can be a bit more challenging. In this post I take a deep dive into how Cookie Information's solution together with their Connector for Episerver can make it easier - and faster to accomplish.
Thoughts on the Episerver/Optimizely Acquisition
When one of the market leaders in digital experience / content management / e-commerce acquires the market leader in Optimization and Experimentation - great things can be expected. But how will it differ from the optimization techniques used by Episerver customers today? Here are my thoughts.
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.
Storage Performance Aftermath - ElasticSearch Joins the Fight
In 3 previous blog posts I compared various azure storage technologies with regards to performance and scalability in typical web usage scenarios. I was actually done with the series, but with all that interesting data, I decided to throw my current favorite search/storage/no-sql technology into the mix to get an idea about how it all compares. So - ElasticSearch enters the competition!
Azure Storage Performance Showdown (Post 3)
This is the 3rd post in my Azure Storage Performance comparison. So far we've examined the typical scenario of storing/retrieving data that most dynamic websites of today deal with. In this post, we'll take a closer look at Update and Delete - and finally review the financial aspects.
Azure Storage Performance Showdown (Post 1)
Almost every project has some data you want to persist, then read, search through, update and eventually delete. With Azure there are loads of great possibilities - for example Blob Storage, Table Storage, CosmosDb, SQL Azure. I've decided to do some simple and fairly naive tests to compare these for some typical usage scenarios and see how they perform.