GratisAIbusiness · field guide · local-first · no account
churn tally wheel

Pool Monthly Churn Into One Honest Rate — Free

Averaging monthly percentages lets a small month shout as loud as a big one. Pool all accounts lost over all accounts at risk to get one weighted rate, and flag the months that cross your review line.

The proof surface

Concentration checks measure revenue dependence. This measures account loss: per-month churn against a threshold you set, plus a pooled rate that weights each month by its real book size.

Inputmonth | accounts at start | accounts lost; monthly churn percentage that triggers review
Rare deviceConcentration checks measure revenue dependence. This measures account loss: per-month churn against a threshold you set, plus a pooled rate that weights each month by its real book size.
Output artifactpercent churned per row with transparent workings
Cost$0 · local-first · one free run · samples labelled
Sample, not your facts: Illustrative sample: March | 3200 | 96; April | 800 | 16. With monthly churn percentage that triggers review set to 3, pooled rate is 2.80 percent churned.

Why the flat version breaks

Averaging percentages unweighted

A tiny month counts as much as your biggest one.

Changing the account definition mid-table

The pooled rate only means something with one definition.

Reading one month as a trend

Pool several months before drawing conclusions.

How to work the churn tally wheel

Count accounts at the start of each month

Use the same account definition every month — seats, customers or subscriptions must not change meaning mid-table. March starts with 3,200 accounts and loses 96, a 3 percent month.

Set your review threshold deliberately

The sample 3 percent is illustrative; what counts as alarming depends on your business model. Months at or above it are flagged for review, including exactly 3.

Trust the pooled rate over the average

Pooling divides total losses by total starting accounts: 112 lost from 4,000 is 2.80 percent. An unweighted average of the two monthly percentages would say 2.50 and let the small month shout as loud as the big one.

Investigate flagged months separately

A launch-month spike can be one cohort or one bad onboarding week. Bring the underlying account list to the review; this tool never sees your customers or their data.

What the churn tally wheel replaces

QuestionBeforeVisible working
Averaging percentages unweightedA tiny month counts as much as your biggest one.Set your review threshold deliberately
Changing the account definition mid-tableThe pooled rate only means something with one definition.Trust the pooled rate over the average
Reading one month as a trendPool several months before drawing conclusions.Investigate flagged months separately

A local arithmetic aid replaces hand calculation, not expert review. No paid AI service is needed.

Run it on the samples, right here

FIRST-LOAD

Input is processed locally and a draft is saved automatically in this browser profile when storage is available. Reset to sample clears that draft; Pro history has its own clear button. A state link encodes your inputs in its URL: share only non-sensitive rows. Browser history, clipboard and anyone receiving the link may retain it. Optional AI use below leaves this device; it is not required.

Arithmetic on counts you enter, with no access to your systems. Not a retention diagnosis, cohort analysis or a prediction; investigate flagged months with real customer data.

Data note: Everything runs in this browser tab on the churn tally wheel: your month | accounts at start | accounts lost stays on this device, nothing is uploaded, and the reading is rebuilt only when you press run.

Go deeper: the companion app files the same reading as a triage clipboard with three lanes

The article demo above runs without limits. The companion app keeps a local history, exports the rows as CSV, prints the churn tally wheel reading, and holds your drafts on this device — one free run, then $ 4 one-time for the layer that keeps filing.

The churn tally wheel reading is complete for free. The optional $4 layer adds print, row CSV and the last five local reading summaries; it does not add hidden answers. Checkout is not configured yet; the article demo remains unlimited.

Open the pool monthly churn into one honest rate companion

Boundary

Arithmetic on counts you enter, with no access to your systems. Not a retention diagnosis, cohort analysis or a prediction; investigate flagged months with real customer data.

What this is built on

Before: A tiny month counts as much as your biggest one. After: the churn tally wheel shows the working beside each named row so the reader can change the assumption and inspect the consequence.

Optional AI formatting, not calculation

For this churn tally wheel, use the free AI Studio interface only if available to you, with no paid API key. Manual entry completes the same workflow for free. Supply only fictional or non-sensitive notes. Review its output against the source; never paste unresolved questions into the numeric rows.

Format my non-sensitive notes for a churn tally wheel. Return plain rows only: month | accounts at start | accounts lost. Preserve supplied quantities exactly. Do not guess missing values; list questions separately. Do not calculate or add advice. I will check every row before pasting into the local tool.

Accepted schema: month | accounts at start | accounts lost. No AI response is executed as code.