Clean your contact CSV before it damages your quality rating

On the WhatsApp Business API, the state of your contact list feeds directly into your phone number’s quality rating. Invalid numbers inflate your failure rate, and a sustained pattern of undeliverable sends is one of the signals Meta reads as spam-like behaviour. The consequences are practical: a downgraded quality rating can shrink your messaging tier, capping how many customers you can reach in a 24-hour window just when a campaign needs volume most. Cleaning a list takes minutes; recovering a quality rating typically takes much longer, because it depends on days of healthy sending behaviour that Meta observes before restoring trust.

Deduplication belongs before import, not after. The same customer usually hides in a raw list under several spellings of one number — with a country code, with a trunk zero, as bare digits — and most platforms will happily create a contact for each variant. The result is one person receiving the same broadcast two or three times in a minute, which is precisely the experience that prompts a Block or Report tap. Because blocks and reports weigh heavily in quality scoring, a duplicate isn’t just a wasted message charge; it is an active liability. Normalising every number to a single canonical E.164 string first turns those invisible duplicates into exact matches that can be removed mechanically, which is exactly what this tool does.

The third pillar of list hygiene is consent, and it lives in your spreadsheet too. WhatsApp requires opt-in before you message a user, and the practical way to honour that is to keep the consent record alongside every contact: a column for where the opt-in was collected (website form, in-store QR, checkout checkbox), one for when, and ideally one for what the person agreed to receive. Because this tool preserves every non-phone column untouched, those consent fields travel with the cleaned file into your platform, where they matter the day a contact disputes a message or an audit asks how a number got onto your list.

• Clean and dedupe every list on the way in — never inside the platform after a broadcast has already gone out.
• Keep opt-in source and date columns in the same file as the numbers, so consent evidence is never separated from the contact.
• Re-clean anything that has passed through Excel: it strips leading zeros and can mangle long numbers into scientific notation.
• Fix the rejected rows rather than deleting them — the reject file lists the exact reason each number failed.