WattShed Yield
Where applications stall, and how long each step takes.
Export your program's application-stage events to CSV, choose it here, and tell this tool which columns are the application ID, the stage, and, if your export has one, the date each row happened. Set the order your funnel actually runs in, and it computes how many applications reached each stage, the conversion from the stage before, and the median days between them, computed in this browser from the export you load. Nothing is uploaded.
The funnel order is yours: reorder the stages found in your data, or leave one out, and every number below recomputes against that order. An application counts as reaching a stage if it reached any later one, the monotone assumption this tool makes, whether or not your export logged a row for that earlier stage.
Thin dates mean thin medians: a stage with only one or two dated transitions is reporting on just those points, not a stable average. This is a funnel check, not a pipeline audit. Use it to see where applications stall before a check-in call, not as the program's system of record.
1. Load an export
Choose a CSV file
Export your program's application-stage events to CSV, then choose it here. Or load a small example first to see how the funnel works.
Computed entirely in this browser. Your export never leaves this device, and nothing is uploaded or stored.
Load an export and map its columns to see a funnel here.
No file handy? Load the example data to see the full report first.
Related tools
How to read it
Four ideas, and the whole report follows from them.
Reached vs. conversion
"Reached" counts every application that made it to a stage or any stage after it in your order. "Conversion from previous" divides one stage's reached count by the stage right before it, so it reads as the share that made it one step further, not a share of the funnel's very first stage.
The monotone assumption
An application counts as reaching a stage if it reached any later one in your chosen order, whether or not this export logged a row for that earlier stage. It is stated here because it is doing real work: a funnel with a skipped logging step still counts correctly, as long as the order you set is the order the program actually runs in.
Medians, and why they thin out
Each stage's median days is the middle value of every dated transition into it from the stage before. Thin dates mean thin medians: a stage with one or two dated transitions is reporting on just those points, not a stable average, and a stage with no date column mapped reports no median at all.
Off-funnel stages
A stage value this tool found in your data but that you left out of the funnel order. Its events are counted on their own and never folded into a stage's reached total or conversion rate, so an odd status like Withdrawn or On Hold does not quietly distort the numbers for the stages you kept.
Nothing beyond the columns you map is read for this report. If your export carries applicant names or other sensitive columns, they load into this browser tab like the rest of the file and are never sent anywhere, but you are still handling that data, so treat the file the way your program already requires.