Customer Health Score Builder (Renewal Risk from Your Accounts)
Which accounts are healthy, which are slipping, and why — well before they renew.
Try before you buy.
- Free preview: the green, amber and red counts and the first rows of each table (up to 10), with revenue at risk hidden.
- Locked until you unlock it: download and copy.
- Unlock: Pro pass, ₹179 for 30 days or ₹79 for 1 week, a one-time payment that never renews. Unlock: Pro pass, $5.99 for 30 days or $2.99 for 1 week, a one-time payment that never renews.
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Your accounts
One row per customer account from your CRM, billing or customer-success tool, or a sheet: the account and whatever signals you have — logins or usage, seats used and bought, open support tickets, NPS or CSAT, late invoices — with the plan, the renewal date and the revenue. For the back-test, a column saying which accounts churned.
Signals, weights and thresholds
Each signal scores 100 at its green threshold or better and 0 at its red threshold or worse, in a straight line between. The health score is the weighted average of the signals an account has: a missing signal is left out and the others count for more. Your settings are kept in this browser.
Account health
Renewal risk: red and amber accounts still to renew, the soonest renewal first
Every account, the lowest health first
Back-test: would the score have flagged the accounts that churned?
Compare with signals from before each account left (an older export): signals read after an account churned flag it too easily.
Churned accounts the score calls green
Rows left out or read with a note
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About the Customer Health Score Builder (Renewal Risk from Your Accounts)
For subscription and B2B businesses: open an accounts export — logins or usage, seats used against seats bought, open support tickets, NPS or CSAT, late invoices, the plan, the renewal date and the revenue — and give each signal a weight and a green and red threshold. Every account gets a health score from 0 to 100, a green, amber or red status and the signals that drove it, and the red and amber accounts still to renew are listed by renewal date with the revenue at risk.
Mark the accounts that churned and a back-test shows whether the score would have flagged them, and how many healthy accounts it flags by mistake. A missing signal is left out of an account’s score and the others count for more — never read as a bad value. It is a rules model you control and can explain, not a churn prediction.
Without a pass the scores are a free preview: the green, amber and red counts and the first rows of each table show, with revenue at risk hidden; the renewal-risk list, the CSV of every account and the workbook unlock with a Pro pass. Everything runs in your browser.
How to use it
- Open your accounts export and check under “Columns used” that the account and your signals were found (seats need both seats used and seats bought).
- Give each signal a weight and the values where it turns green and red; usage starts at your own file’s quartiles, the others at common starting points. Choose the NPS or CSAT scale and how late invoices are counted (a count, or days overdue when the column says days).
- Set where green and amber start, and the date days to renewal count from.
- Read the renewal-risk list, every account’s health and — when the file says who churned — the back-test. The lists and the workbook unlock with a Pro pass; without one the scores stay a free preview.
Examples
Usage 12.5 (green 20, red 5); seats 6 of 10 used = 60% (green 80%, red 40%); 3 open tickets (green 1, red 5); NPS 7.5 (green 9, red 6); 1 late invoice (green 0, red 2)
Every signal scores 50, so the health is 50: amber. Usage costs the most (30% of the weight × 50 = 15 points).
An account with no NPS answer; its other four signals are at red or worse
Health 0, red, from the four signals it has — the NPS weight is left out, not scored as zero.
Two churned accounts (health 50 and 0) and two that stayed (100 and 100)
One churned account is red and both are red or amber; no account that stayed is flagged.
Common uses
- A customer-success team deciding which renewals to call about this month.
- A founder of a SaaS business seeing how much revenue renews at risk next quarter.
- Checking whether a new health model would have caught last year’s churn.
- An account manager preparing a quarterly business review with the weak signals of each account.
How the score is worked out
- A signal where higher is better (usage, seat use, NPS or CSAT) scores (value − red) ÷ (green − red) × 100, between 0 and 100; where lower is better (open tickets, late invoices), (red − value) ÷ (red − green) × 100.
- Seat use = seats used ÷ seats bought × 100.
- Health = Σ weight × signal score ÷ Σ weight, over the signals the account has.
- Status: green at or above the green line, amber at or above the amber line, red below it.
- Driven by: the signals that cost the account the most points (their share of the weight × (100 − their score)).
- Revenue at risk: the revenue of the red accounts still to renew; the amber ones are the revenue to watch. An account the churn column marks as gone, or as renewed with a renewal date that has passed, is not in the renewal-risk list or these figures.
Starting thresholds
- Usage has no common unit (logins, sessions, events), so it starts at your own file: green at its 75th percentile, red at its 25th.
- Seat use: green from 80%, red at 40% or below.
- Open tickets: green at 1 or fewer, red at 5 or more.
- NPS question (0 to 10): green at 9, red at 6, the bands of the Net Promoter System, where 9 and 10 are promoters and 0 to 6 detractors (how NPS is measured). A 1-to-5 CSAT starts at 4 and 2.
- Late invoices: green at none, red at 2 (or 0 and 30 days overdue).
They are a starting point: set them to what healthy looks like in your business.
Reading the back-test
The back-test compares the status with the churn column of the same file. It is fair only when the signals were read before the accounts left: export the signals from a past date (say 90 days before each renewal) and add who churned since. Accounts marked “No” (they renewed) are the ones that stayed; when the column also has blanks, those accounts have not come up for renewal yet and are left out of the back-test. A score that catches most churned accounts as red or amber, and flags few of the accounts that stayed, is worth acting on.
Limitations
- A rules model shows what your thresholds say, not what will happen: a healthy account can still leave for a reason no signal shows (a merger, a new budget holder).
- Signals in different files must be joined into one row per account before they are opened.
- The back-test is only as fair as the dates of the signals: signals read after the churn make the score look better than it is.
- Files of up to 40 MB (and up to 300,000 rows in a workbook sheet), scored on your device.
Privacy
On this device; its files download once
Your accounts stay in this browser on this device; nothing you open is uploaded. Your signals, weights and thresholds are kept in this browser.
Frequently asked questions
What do I get without a pass?
Without a pass, Customer Health Score Builder (Renewal Risk from Your Accounts) shows the green, amber and red counts and the first rows of each table (up to 10), with revenue at risk hidden. Until you unlock it, the result can’t be downloaded or copied. A Pro, Premium or Ultimate pass, a one-time payment that never renews, unlocks the full result. The pricing page lists the passes and their prices.
What weights should I use?
Start with usage 30, NPS or CSAT 20, seat use 20, tickets 15 and late invoices 15, then let the back-test tell you: raise the weight of a signal the churned accounts were weak on, lower one that flags healthy accounts.
How is this different from a churn prediction?
A prediction learns from data and is hard to explain; this is a model of your own rules. Every score can be explained signal by signal, and you can change any threshold and see the result at once.
Can I use CSAT instead of NPS?
Yes: choose the 1-to-5 scale (or 0 to 100). The thresholds change to that scale’s starting points, and you can set your own.
What if an account has no usage data?
Its score uses the signals it has; the weight of usage is shared by the others, and the account is listed with the signals it lacks.