In a previous post I described how to create a custom sort order in QlikView by assigning a sort order value in the load script or by using the match function. This post describes two other clever methods that I recently became aware of:
Read on to see how these methods work.
A short tip today on how to ensure that dimensions in different charts get assigned the same color, regardless of how the data is sorted or if dimensions are missing.
The image on the right shows an example in which revenue per beverage is visualized in a number of different charts and tables. Each beverage is assigned its trademark color (Coca-Cola Red, Heineken Green, Pepsi Blue etc.) and this color is used consistently in each of the charts. Read on to see how you can accomplish this effect.
(Please note that using lots of very bright/saturated colors in your dashboard or report is generally not a good idea, I am only using these colors because they are recognizable to many. Do not try this at work!)
It’s a rainy Sunday here in the Netherlands, a good time to catch up on some reading and share with you some of the QlikView-related blog posts, articles and discussions that I found interesting in the past week.
Do you know if your customers are profitable? All of them? Performing Customer Profitability Analysis can answer these questions and give you some amazing, and sometimes counter-intuitive, insights into your customers’ contribution to your bottom line.
This post describes one of the visualizations that you can create once you possess accurate data* on the profitability of your customers: the whale curve.
In a whale curve, customers are ranked by profitability, from highest to lowest, on the X-axis while their accumulated profit is plotted on the Y-axis. The curve that results can, with some imagination, be said to look like a whale coming out of the water. An example of a whale curve chart is shown below.
When you look at this chart, you may notice that the top 200 customers generate the bulk of the profit. You may also notice that the you are losing serious money on the bottom 100 customers and that the customers in the middle are more or less break-even.
Read on to learn how to create a whale curve in QlikView. Even if you’re not interested in creating a whale curve, you might still want to read on to learn more about the rank function and the continuous x-axis. read more
Decile analysis is a popular segmentation tool. Where a pareto analysis splits the top 20% customers (or products, regions, etc.) from the bottom 80%, decile analysis divides them into equally sized groups of 10%.
The image below shows an example of a decile analysis.
The example shows how a group of 1.000 customers is divided into deciles of 100 customers. Lots of interesting things can be learned from this analysis, amongst other things:
So, how do we create a decile analysis in QlikView? read more
Learn Qlik, the Qlik APIs and Web Development at your own pace at Websy Academy
Supercharge your QlikView designs
(c) 2010 - 2024 