Index/ CSM/ The Data Fix, Explained and Running Live
Customer Success · The Data Fix

Understand the problem. Watch the fix work.

Three parts, in plain English: the problem — why risk slips past; the fix — a simple way to keep account facts trustworthy; and a live demo of the fix running on three sample accounts.

01

The problem: customer facts are scattered, so risk gets missed.

Everything you need to judge an account lives in different places — who they are, what they pay, how they use the product, whether their renewal is coming up. None of it sits in one current record you can actually act on. So judging “is this account healthy” means stitching facts together by hand, and an account slipping toward trouble can go quiet for weeks before anyone notices. With thousands of accounts, that isn’t a process annoyance — it’s a blind spot. A missed renewal is real money.

Scattered facts, hand-stitched, risk goes quiet.

02

The fix: one current record per account, kept honest by its own history.

Keep a single current record for every account. When the system notices something new — usage down, tickets up, a renewal window opening — it writes that down, then re-figures the account’s health fresh from everything it has learned. Nothing is ever overwritten, so every conclusion has a traceable “why,” and an account in trouble surfaces the moment it appears, not weeks later. In one line: a trustworthy current record, rebuilt from its history, that flags risk as it happens.

three lists of data · nothing edited, only added · every flag has a reason

One record, rebuilt from history, flags risk as it happens.

03

Watch it work

Three sample accounts, watched one at a time. Press Step to run the loop — the screen holds one account and the one fact it just handled, so you watch each move land. When one account’s story finishes, the next steps in.

Money at risk $0k the accounts that are not healthy, summed
Run 0 — start
The loop 01spot the change 02write the story 03check the story 04decide next step
Loop step Ready
Press Step to move through it one piece at a time. Each piece explains itself here.
The account the current state — what you act on · derived from the log 3 rows

The account we're watching, rebuilt fresh from its log as each fact lands. Health and next step are the working answer. Nothing here is typed by hand — it’s derived, so every flag has a reason you can point to.

idaccountvaluehealthstatuswhynext step
The log the raw record — everything noticed, in order 0 rows

One row per step, tagged with what the system did to the record. added — a new fact or verdict written to the log, append-only, never edited. used — the check step reads the existing facts to verify the story. The full log keeps every row — nothing is ever deleted — so you can always look back. This is the proof behind the account row.

idaccountwhenwhat happenedthe detail
The history the trend — a snapshot after each run 0 rows

The snapshot from the most recent run. Every run saves one and keeps it — read them in order and you see the trend.

accountwhenhealthwhy
What you just watched

The same simple fix ran on all three accounts. Each time the system noticed something new, it wrote it down, then re-worked that account’s health from everything it knew. Nothing was overwritten — so every “at risk” has a reason you can point to.

By the end, $750k of the book sits at risk, and every dollar of it has a next step:

Granite — goes to a director  ·  Meridian — the renewal gets a call  ·  Sunrise — gets an expansion offer

A person signs off before anything actually ships.

One honest note. This shows the record-keeping working. Two real-world details still need a quick check before it could run for real: the trigger that catches a change, and getting write access to the data warehouse. That check is part of the plan, not hidden.