When working with data in Tableau, there often comes a moment where standard aggregations aren’t enough. That’s where Level of Detail (LOD) expressions come into play. In this blog post, I’ll walk through a simple use case and show you exactly how and why I used LODs.
What are LODs expressions?
LOD (Level of Detail) expressions in Tableau allow you to control the granularity of your aggregations independently from your view. That means you can calculate metrics at a more detailed (or broader) level than what your chart or visual is currently showing.
FIXED helps you answer things like:
- What’s the total sales per customer (even if I’m not looking at customers)?
- What is the average order value per product across the entire dataset?
- What percent of total sales does this row contribute?
You get consistency as the calculation stays steady even if the user filters or drags other dimensions around.
Just to give more context as to what LOD’s are and how they can be used we can use the superstore dataset to address a very simple business question:
We want to see the spread of customers based on how many orders they have made.
The LOD that we will use to show this is as follows:
{ FIXED [Customer Name] : COUNTD([Order ID]) }
Breakdown of the LOD:
{ FIXED [Customer Name] : ... } - For each individual Customer Name, do the calculation inside the brackets — no matter what else is in the chart.”
You’re fixing the level of detail at the Customer Name level. So even if your visualisation is showing Regions, Segments, or Categories, this will still calculate the same way, once per customer.
COUNTD([Order ID]) - This is the distinct count of orders, it counts how many different Order IDs belong to each customer.
Why Is This Valuable?
This LOD expression gives you a stable measure of customer engagement. Because it’s FIXED at the customer level, this number won’t change when you slice your data by other dimensions — that makes it reliable and consistent for deeper analysis.
