Picture this situation: Your company has a long list of products in its catalog, and you want to compare sales per product. Further, the company has recently created a promotional pack with 4 products and you want to see this as one product in your QlikView app. As this is a limited time only situation there’s no need to create a permanent group in your system.
If you ever faced a situation as described above, you will probably already have found several approaches in our community. Most of them will imply a reload process to store the new groups in the backend.
This time cschwarz has created a different method using a combination of the functions PICK () and MATCH () allowing the users to create and administer the grouping on the fly without reload the entire app.
This way to group items is especially well conceived for those situations where users need that flexibly of creating and administering non-persistent groups on the fly, and letting them to check individual items within the group itself.
For those occasions where users’ needs to be able to store new groups to make them available for later analysis sessions and\or dealing with large data sets it still makes sense to go through a different approach that in most of the cases will involve a script process.
ABC analysis is also based in groups, but this time we'll be using three alternate states and Pareto-Select action to solve the ABC customer classification.
Christof’s ABC analysis approach comes with two significant features: It classifies the ABC relatively to the current selection and it stores those classes as is they were normal dimensions until the user recalculate ABC.
This is a very simple and performant way to implement an A/B/C classification letting users to generate the ABC groups dynamically based on their business needs and to compare those values with other elements in the app.