Create Bin based on Measure value

Create the Furniture Sales (%) Measure:
Furniture Sales (%) =
VAR x = CALCULATE(SUM(Sheet1[Sales]), FILTER(Sheet1, Sheet1[Category] = "Furniture"))
RETURN x / SUM(Sheet1[Sales])

Create a Calculated Column for Binning: Instead of using a measure, create a calculated column in your data model. Here’s how you can do it:
Furniture Sales Bin Column =
VAR FurnitureSalesPercentage =
CALCULATE(
SUM(Sheet1[Sales]),
FILTER(Sheet1, Sheet1[Category] = "Furniture")
) / SUM(Sheet1[Sales])
RETURN
IF(FurnitureSalesPercentage > 0 && FurnitureSalesPercentage <= 0.30, "0%-30%",
IF(FurnitureSalesPercentage > 0.30 && FurnitureSalesPercentage <= 0.60, "30%-60%",
IF(FurnitureSalesPercentage > 0.60 && FurnitureSalesPercentage <= 0.80, "60%-80%",
IF(FurnitureSalesPercentage > 0.80, ">80%", "Other"))))

1. Use the Calculated Column in Visuals: Now that you have the calculated column, you can use it in your visuals, including as a Legend. This approach ensures that the binning logic is applied at the row level, allowing it to be used across different visualizations.

I have implemented a similar approach for analyzing sales data in a furniture store https://cabinetsbay.com/, and it worked effectively in visualizing different sales categories.