What is a field validation rule?
Validation rules are the CRM's guardrails, rejecting values that fail a defined test before they ever save.
They are prevention in its purest form: a rule that blocks a bad value costs nothing downstream, unlike the cleanup that value would otherwise require.
Short answer
A field validation rule is a condition a value must satisfy before a record can be saved, such as a properly formatted email, a phone with enough digits, or a close date not in the past. Validation rules catch bad data at entry, enforcing quality at the source rather than requiring cleanup later.
Key takeaways
- A condition a value must meet before a record saves.
- Enforces format, range, and logical consistency at entry.
- Prevents bad data rather than cleaning it later.
- Should target the fields that matter, to avoid excess friction.
Why it matters
Catching a malformed email or an impossible date at entry is far cheaper than discovering it when a campaign bounces or a report breaks. Validation rules move quality control to the source, which is the highest-leverage place to enforce it.
How Ardovo handles it
Ardovo validates key fields at entry by default - formats, ranges, and logical checks - so bad values are caught before they save. Rook keeps the rules focused on fields that matter, so validation protects quality without turning entry into a fight.
Frequently asked questions
What can a validation rule check?
Format (a well-formed email or URL), range (a positive amount, a future close date), and logical consistency (a stage that matches a status). Anything expressible as a pass-or-fail condition on a value can be a validation rule enforced at save time.
What is the difference between a required field and a validation rule?
A required field enforces that a value is present. A validation rule enforces that the value present is valid - correctly formatted or logically consistent. They complement each other: required ensures presence, validation ensures correctness.
Can validation rules be too strict?
Yes. Overly aggressive rules block legitimate values and frustrate users into workarounds. Target validation at the fields where correctness genuinely matters, and make the rules match real-world valid values, so they catch errors without blocking good data.