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Overview

A Grade scores a record from 0 to 100 using a rubric you write: a list of criteria, each worth some weight, each reading something the workspace already knows. The score lands in a band you name, and every grade carries the breakdown that produced it, so “why is this a B?” is one click rather than a guess. It is one property type behind four different jobs. Pick it from Complex in the property type list.

Lead fit

How promising a new lead is. A / B / C / D.

Deal confidence

How likely an open deal is to close. Committed down to Unlikely.

Customer health

Whether a live account is in good shape. Healthy down to At risk.

Churn risk

How likely a customer is to leave. A high score is bad news.

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Setting one up

1

Add the property and pick a preset

Create a Grade property on the object you want to score (Contacts, Deals, Accounts), then choose Start from a preset. A preset fills in the bands and sets which way the score reads. It deliberately does not write any criteria: a rubric depends on your own properties, so anything it invented would point at fields you may not have.
2

Check which way it reads

Reads as decides whether a rising score is good news. Leave it on A higher score is better for fit, confidence and health. Set it to A higher score is worse for churn risk, so a climbing score shows a red arrow rather than a green one.
3

Write the criteria

Each criterion has a label, a weight, and one thing it reads. It is all or nothing. The criterion either earns its full weight or earns zero. See what a criterion can read below.
4

Choose when it recomputes

When the record changes, and nightly is the default and is almost always right. See when it recomputes.

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What a criterion can read

Field tests cover is any of, is not any of, is empty, is not empty, at least, at most and contains.
A field criterion can read a computed property, a Usage property, a rollup or a formula, the same way it reads one somebody typed in. That is how you score on product usage: point at least at API calls (30d) and the rubric does the rest.A Usage property is aggregated live each time the rubric runs, so the score is exact at the moment it was calculated rather than reading a stored figure. If the property is misconfigured, its line shows the reason and is left out of the score entirely, rather than quietly counting as a criterion the record failed.
There is no “ask AI” criterion, on purpose. An AI-written score is one nobody can argue with. Instead, have a property agent fill a normal property, then read that property with a field criterion. The AI’s contribution then earns its points as one visible line of the breakdown that you can see, weight, and remove.

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How the score is worked out

Add up the weight every criterion earned, then rescale against the total of all the positive weights. So a rubric of four criteria worth 30, 30, 20 and 20 that earns the first two scores 60. Weights can be negative, a penalty. A penalty subtracts from what the positive criteria earned and is left out of the rescaling, so adding one cannot inflate everything else.
Rescaling is why you can add a fifth criterion to a four-criterion rubric without every existing record’s score dropping. Scores only move when something about those records moves.

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Bands

A band is a label and a floor. Scores take the highest band they clear, and the lowest band catches everything underneath the one above it, so there is no gap a score can fall into and no overlap where two bands both match. Each band also carries a colour, which is how an inverted grade works: churn risk puts green on Low and red on High, the opposite of every other preset.

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Worked examples

A lead with a work email at a 200-person company who has not replied scores 45, a C. The breakdown says exactly which two lines it missed.
Set Recompute to When the record changes, and nightly: the two time-based criteria go stale on their own, and a deal nobody has touched is exactly the one you want to hear about.
Driven by product usage rather than by who has spoken to whom, so a quiet customer who is using the thing every day reads as healthy.An account that has activated and uses it weekly, on one seat and with no contact, scores 60: Steady. Sort the view by the score and work up from the bottom.
The same facts as health, pointed the other way. Set Reads as to A higher score is worse and write the criteria so that firing means bad news.An account hitting the first and the last scores 55: Elevated, in amber, with a red arrow if it climbed to get there.

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When it recomputes

Anything reading recency, a count or a signal needs the nightly run. Those criteria only become true with the passage of time, and a quiet account is precisely the one nobody is editing, so with Only when the record changes, a health score can never slip on its own.

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What it stores

The score, the band, the breakdown that produced it, and a short history of recent scores that drives the trend arrow. Sorting, filtering and a table’s average / min / max footer all see the score as a plain number, so a grade behaves like any other numeric column. Click the grade to open its panel. It shows:
  • the score, its band, and a small line of recent scores beside the change (“+14 since 15 Aug”)
  • the points earned against the points possible (“82 earned of 100 possible”). Penalties count against what was earned, never toward what was possible
  • every band with the score it starts at, with the current band highlighted
  • each criterion, what it tested (“Stage is Proposal or Negotiation”, “At least 3 calls in 90 days”), and what it earned
To show the panel on the record page itself instead of behind a click, add the Grade block to the record layout and pick the grade it shows. What each criterion tested is saved when the score is computed. Scores computed before this was added show the criterion’s name only, until they are next recomputed.

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Setting one by hand

Open the grade’s panel and type a score. That marks the value manual: it replaces the computed one and drops the breakdown, because the rubric’s explanation no longer describes the number on screen. The trend history is kept, so the arrow survives an override. Clear returns the record to the rubric.

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Troubleshooting

A grade with no criteria is never scored, deliberately: a rubric with nothing in it would score every record 0, and 0 is not “ungraded”, it is the worst lead in the workspace on a number your team sorts by. Add at least one criterion. An empty cell also means a record the rubric has simply not run over yet, which the next nightly sweep or edit fixes.
Check When it recomputes. On Only when the record changes, nothing reading recency, a count or a signal can ever move the score, because those criteria only become true with the passage of time. Switch the property to When the record changes, and nightly, or press the ↻ in the grade’s panel to run it now.
That grade reads the wrong way round. Open the property and set Reads as to A higher score is worse for anything measuring risk. It changes nothing about the score or the rubric, only whether a rising number is shown as good news, and a preset sets it for you.
On a grade that reads A higher score is worse, an earned line is bad news by definition: “No reply in 30 days, +30” means the criterion worked and the account got worse. The colour describes the account, not the criterion.
Bands are matched by the highest floor a score clears, so a band whose floor sits above every score in practice is unreachable, and two bands sharing a floor make the lower one dead. A band missing a label or a floor is dropped entirely and will not show in the editor either.
A criterion written against a select or a user field matches either the option’s label or the stored value, so “Qualified” and the option itself both work. If a field is genuinely empty on the record, the criterion earns nothing and the line shows 0 of <weight> rather than being hidden.
The explanation is snapshotted with the score, not recomputed when you open it. If you have edited the rubric since, the panel still explains the score that was produced by the old one. Press ↻ to score the record against the rubric as it stands now.

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See also

  • Property agents: have AI fill a property a criterion reads.
  • Recommendations: the open recommendations a signal criterion can read.
  • Rollup: aggregate across related records, useful as an input to a grade.
  • Formula: compute a value from other fields on the same record.