Deduplicate and clean every lead list before it reaches the dialer. Merge duplicates by phone and address, normalize the formats, and drop junk records, so reps work clean lists instead of burning dials.
Point it at a raw list from any source. Get back a deduped, dial-ready file plus a record of exactly what was merged or removed.
Lists arrive from vendors, forms, exports, and spreadsheets, each with its own format and its own duplicates. Dial them as-is and reps call the same person twice, contact rates look worse than they are, and reporting drifts. Cleaning by hand does not scale past the first few thousand rows.
Drop in a CSV or connect a source. Vendor files, form exports, CRM pulls, and spreadsheets all normalize into one clean shape, regardless of column names or phone formats.
Records are matched by phone and address with fuzzy name handling, so "Jon Smith" and "Jonathan Smith" on the same number collapse into one. Junk and placeholder rows are dropped. You choose what wins on conflict.
Get back a clean, deduped file ready for the dialer, plus a per-record log of what was merged, kept, or removed. Plug in your own DNC or suppression step and it runs on every future list automatically.
Match on phone and address, not just exact name. Catch the same person entered three ways across three list sources.
When duplicates disagree, keep the most complete record and carry forward the fields that matter instead of dropping data.
Phone numbers, names, and addresses land in one consistent format so the dialer imports cleanly and reporting lines up.
Placeholder names, empty rows, and obviously invalid numbers are flagged and removed before they ever hit an agent.
Bring your own DNC, litigator, or internal opt-out list and apply it as a step. Hygiene and dedupe stay separate from your licensed compliance data.
Every merge, keep, and drop is logged per record, so a removed lead is auditable instead of silently gone.
Records are matched by phone number and address with fuzzy name handling, so the same person entered different ways across different list sources collapses into a single record. You decide which record wins on conflict, and every merge is logged so nothing disappears silently.
Yes. Matching runs on phone and address rather than exact name, which catches the real-world duplicates that exact-match dedupe misses. On a match, the most complete record is kept and its fields are carried forward.
Cleanup focuses on deduplication, normalization, and junk removal. If you need DNC, litigator, or internal opt-out suppression, you plug in your own list as a step. We keep hygiene separate from licensed compliance data rather than reselling it.
Both. Clean a one-off file, or wire it as a workflow so every incoming list, from every vendor and form, is deduped and cleaned automatically before it reaches the dialer.