Repeatability
High
Phone formatting, address parsing, and company name normalization are structurally identical operations applied row by row. The rules are finite and can be codified once and applied consistently across all 3,500 records.
Ambiguity Tolerance
High
Success criteria are concrete: E.164 phone format, split address fields, and documented normalization rules. An agent can verify compliance programmatically and flag records that don't resolve cleanly.
Data & Tool Availability
High
The task requires only the three spreadsheets, which are presumably shareable files. Standard libraries (pandas, phonenumbers, usaddress, fuzzy matching) cover all transformation needs without external API dependencies.
Error Cost
Medium
Incorrect merges or phone number mangling could corrupt prospect records used in outreach, but the original spreadsheets remain intact as a backup. Errors are reversible if the source data is preserved, though downstream CRM imports could propagate mistakes.
Human Judgment Required
Low
Most transformations are rule-based. The only genuine judgment calls are ambiguous company name variants where fuzzy matching confidence is low — these should be flagged for human review rather than auto-resolved, but they'll be a small fraction of records.