🔍 Executive Summary

In modern outbound, phone data is the most important — and most fragile — part of your go-to-market engine.

The Salesfinity AI Data Team conducted a controlled benchmark across nine leading phone data providers, measuring both accuracy and coverage on a shared dataset of verified contacts.

The results show substantial variance between providers — with accuracy ranging from 63% to 91% and coverage from 26% to 92%. But the deeper insight isn’t just which provider performs better. It’s why even accurate phone data requires continuous re-enrichment, not one-time uploads.

Unlike email addresses, phone numbers don’t bounce — they connect, misconnect, or go nowhere. You only find out a number is wrong after you’ve wasted a dial.

That’s why the next evolution of data accuracy is automated re-enrichment triggered directly from call outcomes.

⚙️ Methodology

Dataset

• 307 verified contacts with confirmed direct dial numbers

• Split evenly between U.S. (153) and Global (154) records

• Sourced from multiple industries and roles

Process
Each provider was used to re-enrich the same contact list. Their outputs were compared to the verified dataset to calculate accuracy and coverage.

Metrics Defined

• Accuracy: % of phone numbers that matched the verified number.

• Coverage: % of contacts for which a valid phone number was returned.

• Overall Score: Weighted blend of both, representing total practical utility.

📈 Results Summary

Data providers that were evaluated:

• Forager

• Amplemarket

• Prospeo

• Wiza

• Datagma

• RocketReach

• Upcell

• Leadmagic

• LeadIQ

• Salesfinity SmartEnrich

🔬 Key Findings

1️⃣ Accuracy is inconsistent across the market

Accuracy ranged nearly 30 points across providers. This means some vendors deliver clean, validated data most of the time — while others introduce large amounts of noise.

For SDRs, that difference directly affects connect rate and rep productivity.
Even a 10% drop in accuracy can mean hundreds of wasted dials every month per rep.

2️⃣ Coverage gaps limit reach

Coverage ranged from 26% to over 90%, showing that some providers return few results even if those few are accurate.

That trade-off means there’s no universal “best” vendor — high accuracy without coverage limits your total reachable audience, while high coverage with low accuracy inflates your connect waste.

3️⃣ True effectiveness = Accuracy × Coverage

The Overall Score captures the intersection of both metrics — representing how usable a provider’s output really is in a live dialing environment.

In practice, teams get the best outcomes when they combine multiple data sources in a waterfall enrichment flow — each vendor filling the gaps left by another.

4️⃣ Real-world call outcomes mirror the benchmark

Across 4.7 million outbound dials, here’s what live call outcomes looked like:

📞 Why Continuous Re-Enrichment Is Critical

With emails, the system tells you immediately if something’s wrong — a bounce gives a clear yes/no signal.

Phone numbers don’t work like that.

A “wrong” number could mean:

• The number is valid but belongs to the wrong person

• The number is disconnected or goes to voicemail forever

• The contact’s title or company changed, making the number irrelevant

If your enrichment stops after the first attempt, you’ll never know if that contact was actually reachable through a different number.

That’s why continuous re-enrichment is essential:
Every bad call, wrong contact, or disconnected line is a signal that should automatically trigger another lookup.

Otherwise, you silently lose valuable prospects you never even reached.

The Problem With Static Enrichment

Traditional enrichment workflows assume static accuracy. Teams enrich once before a campaign and assume the data is correct until proven otherwise.

But here’s what really happens in phone data workflows:

1. Your enrichment tool provides a number.

2. The SDR calls it.

3. It’s either:

   • Correct (live connection),

   • Same Name, Wrong person,

   • Wrong number,

   • Disconnected, or

   • Never answered.

4. The SDR moves on — the record stays stale.

Without automation, that contact never gets another chance to be re-enriched.
You’ve just lost a potentially great prospect — not because they said no, but because their data was wrong.

💰 The Cost of Inaction

If 25% of your phone data is wrong and each SDR makes 300 dials/day:

• That’s 75 wasted calls per rep per day.

• Roughly $7,500/year per rep in wasted dial time and software minutes.

• For a 10-person team, that’s $75,000–$100,000/year in avoidable inefficiency.

Continuous re-enrichment doesn’t just improve accuracy — it recovers lost time and pipeline.

🚀 How Salesfinity SmartEnrich Solves This

To solve this at scale, we built SmartEnrich, a continuous phone enrichment system integrated directly into the Salesfinity platform.

How it works:

1. Waterfall Enrichment: SmartEnrich automatically pulls from multiple verified data vendors in sequence — including those tested in this benchmark.

2. AI-Based Detection: If a call is marked as “Bad Number” or “Wrong Contact,” the system automatically re-enriches that contact using the next vendor in the waterfall.

3. Continuous Refresh: Updates are synced directly back to your CRM or sequence tool — with zero manual effort.

4. Live Feedback Loop: Our AI learns which vendors perform best for your specific segment and adjusts automatically.

The result?
Your reps never stop at a dead number. Every failed call becomes a self-correcting data improvement loop.

🏁 Final Thoughts

Phone data is not like email data — there are no bounces, only missed opportunities.

If you stop after the first enrichment, you’re leaving live prospects unreachable.
Continuous, automated re-enrichment ensures your team never gives up on a lead because of bad data.

That’s what Salesfinity SmartEnrich was built for:
A self-learning enrichment engine that turns every call into data feedback — so your SDRs always reach the right person, every time.