Fill rate is one signal. A useful Salesforce field audit tool surfaces fill rates, hidden populated fields, layout coverage, FLS visibility, and required-field status together — so cleanup candidates can be reviewed with context, not guessed at.
Read-only diagnostics · Review-ready XLSX workbook · No package install · No Connected App
Most field cleanup requests start with a question: which fields on this object are actually being used? The answer depends on what "used" means — and that is harder to determine than it appears.
A field that has a low fill rate may still be on every page layout. A field that is not on any layout may still hold data written by a retired integration. A field that appears unused by most users may be restricted through FLS so only a small group can see it — which means it was always functioning as designed, and the fill rate was always going to look low.
A Salesforce field audit tool needs to surface multiple signals in one view so admins can evaluate cleanup candidates in context, not in isolation. That means more than an export — it means a workbook structured for review.
The Field & Object Audit workbook produces one row per field per selected object. Each row contains structured review signals so admins can triage and filter without running additional queries.
The workbook also includes object-level summary tabs with headline counts, a Schema Health Score, and a cleanup candidate tracker for review sign-off.
Relevant Workbook
The Field & Object Audit workbook surfaces field inventory, fill rates, hidden populated fields, layout coverage, FLS visibility, and required-field indicators across selected objects — formatted for structured admin review.
Fill rate is the most visible signal in a field audit, but it needs to be read carefully. The same percentage means different things depending on the field type, the object, and who has access.
0%
Never populated
No record on this object has a value for this field. This is a strong cleanup candidate signal — but still requires checking whether the field is a formula, required by a validation rule, referenced in automation, or reserved for future use. A 0% fill rate field that is also on zero layouts and has zero FLS profiles is a high-confidence candidate for review.
1–5%
Very low use
Only a small fraction of records have a value. This may indicate a field used only for a specific record type, a specific import scenario, or a manual admin-only workflow. Check the FLS profile count and layout count before flagging as unused. A field with 3% fill rate but 1 layout and 2 profiles may be working exactly as designed.
5–20%
Selective use
The field is being used, but not broadly. This range often indicates a field tied to a specific process, a record type, or a conditional workflow. Record-type breakdown can show whether usage is concentrated in a subset of records rather than spread across the full object. Review before cleanup.
20–60%
Moderate use
The field is in regular use across a meaningful portion of records. Cleanup decisions in this range are uncommon and require a strong justification — usually a confirmed process change or data model redesign. These fields should be excluded from routine cleanup reviews.
60%+
Active
The field is actively populated across the majority of records. Do not flag for cleanup without business owner review and a documented reason.
Fill rate thresholds above are starting points for triage, not firm rules. The right threshold depends on your object volume, business process, and the other signals in the row.
For a full treatment of fill rate as one signal among many, see the fill rate reference signals guide.
Hidden populated fields are fields that contain data but do not appear on any active page layout. They look unused at a glance — nothing on the layout, minimal visibility in reports — but they still hold values.
An Account object has a field called Legacy_Region__c. It was added during a 2019 migration from a legacy CRM to map regional territory data. After the migration was complete, the field was removed from all layouts because the new region logic lived elsewhere. Two years later, an admin running a cleanup review sees 0 layouts, 2% fill rate, and flags it for deletion.
What the layout and fill rate signals do not show: the field still has values written on 8,400 Account records. A reporting tool used by the finance team runs a monthly SOQL query against it. Deleting the field breaks the query and loses the historical region values permanently.
A field audit tool should flag this field as "hidden but populated" — a distinct category that gets stakeholder review before any cleanup action.
Hidden populated fields are not rare. In orgs that have gone through integrations, migrations, or multiple admin transitions, they are common. A field audit that only reports fill rate and layout presence will not surface this risk explicitly — which is why the hidden-populated flag needs to be a first-class column in the workbook, not derived from other signals.
Fill rate is calculated across all records on the object. But who can actually write to a field is controlled by field-level security. If a field is restricted to a small number of profiles, it will always show a low fill rate — not because it is unused, but because only a small group can populate it.
| Field | Fill Rate | FLS Profiles | Read as |
|---|---|---|---|
| Credit_Score__c | 3% | 2 of 38 | Likely active — only finance team can write to it. Low fill is expected. |
| Referral_Source__c | 4% | 35 of 38 | Higher cleanup candidate signal — wide access, but almost nobody populates it. |
| Legacy_UTM__c | 0% | 0 of 38 | No access, no data — strong candidate, but verify it is not referenced in flows or integrations. |
Reviewing fill rate without FLS profile count leads to false candidates and missed risks. Running the Permission & FLS Audit alongside the Field & Object Audit gives you the access context needed to read fill rates accurately.
Relevant Workbook
The Permission & FLS Audit workbook maps field-level security exposure across profiles and permission sets, helping you interpret field usage data in the context of who can actually see and edit each field.
Layout count tells you how many page layouts include a field. A field that is not on any layout is invisible to users in the standard UI — but that does not mean it is unused.
Layout count also matters for understanding whether a field removal will affect the user experience. Removing a field that is on 8 layouts creates 8 layout change events — each of which needs to be reviewed before deployment.
The Field & Object Audit workbook structures the evidence. The review workflow below shows how admins typically move from raw signals to a cleanup decision with documented sign-off.
Start with fields flagged as Cleanup Candidate in the Status Band column. These are fields where fill rate, layout coverage, and FLS scope all point in the same direction. This is your working list — not your final list.
Before any action, remove hidden-populated fields from the candidate list. These are flagged explicitly in the workbook. They need a separate stakeholder review to confirm whether the data can be discarded before the field is touched.
For each remaining candidate, check the FLS Profile Count column. A field with wide FLS access and near-zero fill rate is a better candidate than one with narrow access. Narrow FLS plus low fill rate means the field was always expected to be sparsely populated.
Zero layouts confirms the field is not user-facing. One or two layouts means it may be tied to a specific record type or admin workflow. Confirm with the layout owner before proceeding.
The workbook does not scan runtime automation references — that requires reviewing Flows, Apex, and validation rules separately. Use the Automation Inventory to check whether any active automation references fields on your candidate list.
The workbook includes a cleanup tracker tab for recording decisions, reviewers, and sign-off status. Keeping this in the workbook file means the review evidence stays with the audit, not in a separate Slack thread or email chain.
The output of this workflow is a cleanup list with review evidence, not a delete list. Each field on the list should have a documented reason, a reviewer, and a sign-off before any change is made in Salesforce.
Several KeelCadence resources cover related ground. This table shows how the field audit tool sits relative to the field cleanup checklist and the metadata audit tool — so you know which to use when.
| Aspect | Field Audit Tool | Field Cleanup Checklist | Metadata Audit Tool |
|---|---|---|---|
| Output | XLSX workbook with per-field signal rows, status bands, health score, and cleanup tracker | Written guide: what to check and why before a field cleanup project | XLSX workbook covering field, object, permission, and automation metadata across the org |
| Focus | Field-level signals: fill rate, FLS, layout coverage, hidden populated, required flags | Cleanup process guidance: when to clean, what to validate, how to get sign-off | Full org health: field inventory plus object structure, automation, permission coverage |
| Use when | You need structured evidence about specific fields before a cleanup decision | You need to understand what the review process should cover before you start | You need a complete first-pass picture of an unfamiliar or inherited org |
| Replaces the other? | No — the checklist tells you what to review; the tool gives you the data to fill it in | No — the checklist is the process; the tool generates the evidence | No — broader scope, less field-level depth; best used before field-specific drill-down |
A field audit workbook surfaces review signals. It does not replace the review conversation.
The workbook gives you a structured starting point for the review. The review itself — including stakeholder input and documented decisions — is still your responsibility.
Once you have reviewed the signals that matter, run the read-only Field & Object Audit to capture fill rates, hidden populated fields, layout coverage, and cleanup candidates in one review-ready XLSX workbook.
Read-only · No package install · No Connected App setup · No Salesforce writes
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