Philippines staffing research
What can wrong-number rates reveal about a calling list?
A measurement plan for list-source review that keeps data quality separate from campaign performance.
Published: September 7, 2026. This research note asks whether wrong-number outcomes differ across approved list sources and verification ages. It is a measurement design for OutsourcedCallers.com operations, not a claim that one practice is universally best.
Define the unit as one released phone record and its final identity-verification outcome. Freeze eligibility, observation windows, and exclusion rules before reviewing outcomes. Include unsuccessful records so the dataset does not become a success-only story.
Collect source label, acquisition date, verification date, record ID, attempt result, correction, and suppression time. Minimize identifiers, restrict access, set a retention period, and keep consent and suppression controls independent from the study dataset.
Compare source, age band, duplicate state, wrong-party result, corrected record, and suppression completion. Publish counts and denominators for each group, show missing values, and use uncertainty intervals only when the sample and design support them.
Scope and limitations: this analysis can describe associations inside the released sample and period. a wrong-number rate does not measure consent, intent, caller skill, or commercial value. Seasonality, source quality, customer mix, caller assignment, and workflow changes may also explain differences.
Pilot the codebook on a small sample. Have a second reviewer classify ambiguous records without seeing the first decision, then report exclusions, protocol changes, and unresolved disagreement.
Keep the operational conclusion narrow: use a finding to improve a field definition, choose the next controlled test, or identify a handoff for review. Do not turn an aggregate pattern into a promise about an individual call.
Sources: NIST Privacy Framework (https://www.nist.gov/privacy-framework); FTC Telemarketing Sales Rule (https://www.ftc.gov/legal-library/browse/rules/telemarketing-sales-rule); AAPOR Best Practices (https://aapor.org/standards-and-ethics/best-practices/); Philippines National Privacy Commission, Data Privacy Act guidance (https://privacy.gov.ph/data-privacy-act/).