Repeatability
High
Formatting normalization and deduplication follow consistent, codifiable rules: trim whitespace, standardize case, canonicalize phone formats, and match on composite keys. The structure is identical across every row, making this highly automatable.
Ambiguity Tolerance
Medium
Most success criteria are crisp (consistent formatting, no exact duplicates), but fuzzy duplicates — slightly misspelled names or transposed address components — require a defined similarity threshold that the user hasn't specified. That threshold choice affects output quality meaningfully.
Data & Tool Availability
High
The input is a self-contained CSV file, and standard libraries (pandas, recordlinkage, phonenumbers) cover all required operations. No external APIs, credentials, or live system access are needed to produce the cleaned output.
Error Cost
Low
The original CSV is preserved, so any mistakes are fully reversible before CRM upload. A bad merge of two distinct customers is annoying but correctable; no irreversible downstream damage occurs at this stage.
Human Judgment Required
Low
The vast majority of deduplication and formatting work is rule-based. A brief human review of the flagged fuzzy-match candidates (likely a few dozen rows) is advisable but not required for the bulk of the task.