Comparing Phone Data Accuracy Across Three Vendors

We compared Wiza, ContactOut and DataGMA phone numbers to test which phone provider rises above the rest.

Article
September 15, 2025

Background

A leading payroll solution wanted to evaluate which data vendor could deliver the most accurate and actionable phone numbers for outbound sales. We ran a head-to-head comparison of ContactOut, Wiza, and DataGMA using the same set of target contacts. The goal: determine who provides the best data for connecting with real decision-makers.

Method

  • Each vendor supplied phone numbers for the same group of contacts.
  • The sales team dialed into those numbers and logged the outcomes:
    • Connected: Live conversation with the right person.
    • Wrong Number: Disconnected, invalid, or not the right contact.
    • No Answer/Voicemail: Dialable, but no confirmation of accuracy.
  • We then compared the results side-by-side.

Results

  1. ContactOut
    • The only vendor that produced confirmed live connections.
    • Slightly higher share of wrong numbers compared to the others.
    • Balanced outcome: more risk of dials that don’t connect, but proof of numbers that do.
  2. Wiza
    • Very low wrong number rate.
    • Majority of numbers went to voicemail or no answer.
    • No live connects recorded in this test, so accuracy is unproven beyond being dialable.
  3. DataGMA
    • Similar to Wiza: very low wrong number rate.
    • No confirmed live connections.
    • Slightly fewer wrong numbers than Wiza, but still no evidence of true accuracy.

Key Takeaway

  • If your priority is real conversations and pipeline creation, ContactOut stands out as the only vendor to deliver true connects.
  • If your priority is simply minimizing wasted dials on wrong numbers, Wiza and DataGMA both perform well—but they didn’t prove their ability to actually reach buyers.

Recommendation

For revenue teams at payroll, fintech, and SaaS providers, we recommend:

  • Use ContactOut when sales productivity depends on connecting with the right people, even if it means tolerating a few more wrong numbers.
  • Treat Wiza and DataGMA as supplementary sources for volume, but validate with calling tests before scaling.
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