Cleanse data with validation rules

Our contact emails, phone formatting, and required country fields need fixing across 12,900 records. Enforce validation: email must match a standard email regex and phone must be E.164 format for mobile and phone fields. Country must be one of the ISO list and Billing Country required on account if Billing Street exists. Run a validation pass that tags records failing rules and create a report with sample records for each rule violated. Do not block records from saving yet; deliver the list by Thursday noon so reps can update high-value accounts first.

I want the validation rules to be usable by reps and not cause constant save failures. Surface which rules will block saves and which should be warnings. Put a short help text next to each rule explaining why it matters and an example of correct formatting. Flag the top 200 accounts by revenue that would fail the rules and suggest automated fixes for common issues like missing +1 country codes or misplaced extension formats.

I enabled E.164 phone validation on contacts and several reps report they can no longer save new leads from trade shows because phones are formatted differently. I don't know how many critical saves are being blocked or whether to loosen the rule. Recommend the likely impact of the strict rule, the minimal relaxation that preserves data quality, and a short message I can send reps explaining the change and next steps.

Every few months we create stricter validation rules, reps revolt, we relax them, and data quality never improves. Where am I failing in rolling out validations with users, and what one habit change plus one rule design would let data quality improve without disrupting front-line selling?