Custom Field Usage Audit and Cleanup
Every initiative, integration and well-meaning admin project over the years added a handful of new custom fields to the opportunity or contact object, and almost none of them were ever removed when the initiative ended or the integration changed. The result is a page layout with 180 fields where maybe 40 are actively used, a report builder where nobody can tell which 'Status 2' field is the current one, and new reps who spend their first weeks confused about which fields actually matter versus which are vestigial. Admins are reluctant to delete anything because nobody's sure what still depends on an old field.
STARTING PRICE
From €299
Standard tier · Multi-step workflow with AI extraction/decisioning and 2-3 integrations.
Get a quote →Saves roughly 3-5 hrs/week for CRM admin, plus fewer downstream mapping errors from confusing page layouts.
How the automation works
We audit actual field usage across your CRM — data population rate, whether the field appears in active reports or dashboards, whether it's referenced in an active workflow, validation rule or integration — and produce a clear picture of which fields are genuinely load-bearing versus safe to deprecate. Fields with real but low usage get flagged for a decision rather than automatic deletion, since a field used by only one team's critical report still matters even if the company-wide usage rate looks low. Nothing is removed without a documented review, since deleting a field an integration secretly depends on can break something invisible until it fails.
Process flow
- 01
Inventory all custom fields trigger
Every custom field across relevant objects is inventoried with its creation date, description and current page layout placement, giving a full baseline before any usage analysis starts.
- 02
Measure data population and activity integration
Population rate (what share of records have a non-blank value), recency of last update, and presence in active reports, dashboards, workflows and validation rules are measured per field.
- 03
Check integration and automation dependencies integration
Fields referenced by integrations, API calls or automation rules are specifically flagged as dependency-critical even if their direct data population looks low, since these often carry invisible but real risk if removed.
- 04
Classify by usage and risk ai
Fields are classified into clear categories — actively used, low-use-but-dependency-critical, and genuinely safe to deprecate — with reasoning shown for each classification.
- 05
Review and clean up output
A recommended cleanup list goes to admins and relevant team leads for sign-off before any field is deprecated or removed, with the audit trail preserved for reference.
Inputs
- Full custom field inventory
- Field population and update data
- Report, dashboard and workflow references
- Integration/API dependency mapping
Outputs
- Field usage classification report
- Dependency-critical field flags
- Recommended deprecation list
- Cleaned page layouts post-review
Works with
Prefer a fully custom build instead of an off-the-shelf integration? We scope both options during your free consultation — most jobs like this one work fine on standard connectors, but higher-volume or non-standard systems sometimes need bespoke API work, reflected in the complex tier.
Where this goes wrong if you get it wrong
- A field with a low overall population rate across the whole database can still be mission-critical for one specific team or product line that represents a small share of total records but a disproportionate share of revenue — usage analysis needs to be segmented, not just a single company-wide percentage, or a genuinely important niche field gets recommended for deletion.
- Fields referenced by an integration or a scheduled API job often show no visible activity inside the CRM's own reports and workflows, since their only consumer is an external system — an audit that only checks in-CRM usage signals will systematically miss these and recommend deleting fields that would silently break an external integration the moment they're removed.
- A field that looks unused because current reps don't touch it might still hold historically important data on old closed records that matters for trend analysis or compliance retention — 'currently being written to' and 'safe to delete, including its historical data' are different questions, and conflating them risks destroying data that has ongoing reference value even without active new entries.
- Recommending deletion based purely on usage metrics without documenting who originally requested the field and why can repeat history — if nobody records the original business reason a field was low-usage but intentional (a field required for one annual compliance report, for example), a future audit years later will flag it as unused all over again with no memory of why it was kept last time.
Frequently asked questions
Will any fields be deleted automatically?
No — every recommended deprecation goes through a documented review and sign-off with relevant team leads before anything is removed, since a field that looks unused can still carry hidden dependencies.
How do you catch fields used only by an external integration?
Dependency mapping specifically checks for integration and API references, not just in-CRM usage like reports and workflows, since integration-only fields often show no visible in-CRM activity.
What happens to historical data on a deprecated field?
Deprecation typically means removing the field from active page layouts and stopping new entry, not necessarily deleting historical data outright — the specific approach is agreed during the review, not assumed.
How often should this audit be repeated?
Annually or after any major process change is a reasonable cadence, since new field sprawl accumulates continuously as new initiatives add fields over time.