Blog / Marketing
Why cleaning your contact list before an SMS campaign saves real money
Here is the arithmetic nobody runs before their first campaign. Say you have 4,000 contacts and your provider charges $0.0079 per segment, which is roughly Twilio's US rate. One send to the full list is about $32. Not frightening.
Now say 9 percent of that list is duplicates, which is on the low side of what I see in real address books. That's 360 wasted messages per campaign. Send weekly for a year and you have paid about $148 to text the same people twice. The money is annoying. The complaints are worse.
Duplicates are not the only dead weight
Landlines take your message, fail silently, and still bill you. Contacts with no phone number at all sit in your CSV taking up a row and sometimes breaking an import. Old work numbers for people who changed jobs in 2021 bounce forever.
A realistic breakdown of a 4,000-contact phone book looks something like 350 duplicates, 200 entries with no mobile number, and a few hundred numbers saved in local format that your provider cannot parse. That is a fifth of the list doing nothing useful.
The iPhone's own tool will not find most of them
iOS has a duplicate finder built into the Contacts app, and it is better than nothing. It matches on identical names. That means it catches "John Smith" saved twice and misses "John Smith" and "Jon Smith" sharing one mobile number, which is the far more common case after years of syncing between Gmail, iCloud and a work account.
Matching on the normalised phone number instead catches both. That's what merging duplicates properly requires, and it's why the built-in tool leaves so much behind.
Strip the rows that cannot convert
Before export, cut anyone with no number at all. There is no scenario where those rows help an SMS campaign, and they inflate every count you report to yourself. Removing contacts without phone numbers takes one toggle if your export tool supports it.
Do it once, properly
The reason most people skip this is that doing it by hand in a spreadsheet takes an afternoon. Sort by name, eyeball the repeats, find the ones with different spellings, check which of the two entries has the better number, delete the other. For 4,000 rows that is genuinely hours of work, and you have to repeat it every time you export.
Doing it on the phone before the CSV ever exists is the shortcut. Pluck reads each number, works out which entries are the same person, and leaves one. The export that lands in your downloads folder is already clean.
The ones that look fine and are not
Two entries, same person, different numbers. One is their old work mobile from a job they left in 2021. Deduplication by number will not catch this because the numbers genuinely differ, and name matching catches it only if the spelling is identical.
There is no automatic fix here. What helps is sorting the export by name so near-identical entries sit next to each other, which turns a hunt into a scan.
Landlines bill the same as mobiles
An SMS to a landline is accepted, charged, and never delivered. Most providers will not flag it for you. In a phone book built over a decade, office and home numbers are a meaningful slice, and they quietly take a cut of every campaign.
Exporting mobile numbers only, where your tool supports the distinction, removes the problem at source.
Do it before every export, not once
A list cleaned in March is dirty again by June, because you keep saving numbers. The reason to do this on the phone rather than in a spreadsheet is repeatability: thirty seconds each time beats an afternoon once and never again.
Get Pluck for iPhone
Pluck does the steps in this guide on your iPhone, with no server, no account, and no analytics. Group your contacts by country, find duplicates the iOS tool misses, and export to CSV, Excel, TXT, or vCard.