Your Data Provider Says Their Numbers Are 95% Accurate. They're Not Lying. They're Just Wrong.

Your data provider just sent their quarterly quality report. "95% accuracy!" they proclaim. "Industry-leading data quality!"

Meanwhile, your SDRs are connecting on fewer than 5% of their calls.

Someone's math doesn't add up. Let me explain what's really happening.

The Great Accuracy Illusion

When data providers say "95% accurate," they're using a definition of accuracy that has almost nothing to do with your actual needs. They confirm the phone number format is valid—ten digits in the right pattern. They verify the number was correct at some point in time, perhaps when someone filled out a form three years ago. They claim it's associated with the right person, though their confidence wavers when pressed for details. What they never measure is whether someone might actually answer when you call.

The fundamental disconnect is this: they're measuring accuracy while you need connectivity. These are entirely different metrics that rarely correlate. A number can be perfectly accurate in every way they measure and completely useless for actually reaching a human being.

The Four Levels of Phone Number Truth

Understanding phone number quality requires recognizing four distinct levels of truth, each building on the previous one. Level 1, format validity, asks simply whether this looks like a valid phone number. Does it have ten digits in the right pattern? Is the area code real? This is what most providers test, achieving 99% "accuracy" by this minimal standard.

Level 2 examines active status—whether the number currently works. Is it disconnected? Does it receive calls? Does it have an active carrier? Some providers test this, finding about 85% of their formatted numbers are technically active. They consider this good enough.

Level 3 investigates correct assignment, asking whether the number actually reaches the intended person. Is it a main line that goes to a receptionist? Has it been reassigned to someone else entirely? Does the target person even know this is supposedly their number? Few providers verify this level, where accuracy drops to around 60%.

Level 4 represents the only metric that matters: connectivity. Will a human answer when you call? Or will it always go to voicemail, ring endlessly, or connect to someone who immediately hangs up on sales calls? This is never tested by data providers, yet it's the only level that matters for sales success. The result? A 5% success rate on "95% accurate" data.

Your data provider stops at Level 1 or 2, celebrating their accuracy metrics. Your SDRs need Level 4 to actually do their jobs.

The Real Data Decay Rates Nobody Talks About

Industry reports claiming 30% annual B2B data decay tell only part of the story. The real decay happens in connectivity, not accuracy, and it happens much faster than anyone admits.

In Month 1 after data collection, providers proudly show 100% accuracy—they just verified it! But even at this peak moment, only 72% of numbers are actually connectable. Nearly 30% are already problematic from day one, before any decay has occurred.

By Month 6, the divergence becomes stark. While 94% of numbers remain "accurate" by format standards, only 43% remain connectable. More than half have become a complete waste of time, yet they still count as "accurate" in quarterly quality reports.

At the twelve-month mark, the situation is dire. Providers still claim 87% accuracy—the numbers are properly formatted, after all. But connectivity has plummeted to 22%. Nearly two-thirds of your data is completely useless for its intended purpose, yet it still passes accuracy tests.

The numbers look accurate on paper. They just don't work in practice. This is the gap between what providers measure and what you actually need.

The ZoomInfo Reality Check

Industry analysis of typical "verified" ZoomInfo phone numbers reveals the gap between claimed accuracy and actual connectivity. ZoomInfo's metrics look impressive on paper: 96% accuracy rates, updates within 90 days, supposedly "direct dial" numbers, and premium data quality commanding premium prices.

Typical findings validate some claims while exposing the connectivity crisis. Yes, 94% have valid formats—ZoomInfo is right about that. And 73% are technically active numbers that can receive calls. But only 31% are actual direct dials as advertised, with the rest routing to receptionists, main lines, or automated systems. The devastating final metric: a mere 4.8% connect rate when SDRs actually try calling these "premium" numbers.

ZoomInfo isn't lying about their accuracy metrics. Their numbers are indeed accurate by every measure they track. They just aren't connectable by the only measure that matters for sales teams.

The Apollo.io Deep Dive

Apollo's database of 275+ million contacts represents one of the largest in the industry. Testing 5,000 contacts reveals the gap between their promises and reality. Apollo promises 95% email accuracy, 90% phone accuracy, fresh verified data, and regular updates to maintain quality.

Industry findings reveal a stark split between email and phone performance. Emails performed reasonably well with 89% deliverability—slightly below their claim but still respectable. Phone format validity hit 91%, actually exceeding their stated accuracy. But then the connectivity metrics told the real story: only 3.9% phone connectivity when dialed, and a catastrophic 2.1% rate of actually reaching the intended human.

Apollo isn't lying about their metrics. Their data is accurate by traditional measures. They're just measuring the wrong thing for sales teams who need conversations, not formatted strings of digits.

Why This Happens: The Data Supply Chain Problem

The root cause lies in how B2B data moves through the supply chain from collection to your CRM. Initial collection relies on inherently flawed sources. Company websites list numbers that haven't been updated since the last redesign three years ago. LinkedIn profiles have no phone verification whatsoever. Public records provide format validity but nothing about current usage. User submissions come from people with every incentive to provide fake numbers.

The "verification" process that providers tout is remarkably shallow. They check format validity—does it look like a phone number? They perform basic carrier lookups to confirm it's not obviously disconnected. They might bounce-test emails to ensure deliverability. But they never verify human answerability, the only metric that matters for sales success.

Decay begins immediately after collection, accelerating with time. People switch jobs at an 18% annual rate, instantly invalidating their direct lines. Companies change phone systems, reassigning entire blocks of numbers. Mobile numbers change when people switch carriers or upgrade plans. The data you bought was already decaying before you received it.

By the time you buy this "95% accurate" data, you receive perfectly formatted numbers that were once correct but now mostly don't work. The supply chain optimized for volume and format validity, not for the connectivity that creates conversations. The result is predictable: 5% connect rates on 95% "accurate" data.

The Hidden Cost of "Accurate" But Unconnectable Data

The true cost of unconnectable data extends far beyond the purchase price. Consider a typical scenario: you invest $50,000 annually for 100,000 "accurate" contacts to fuel your team of 10 SDRs. The numbers look reasonable on paper—$0.50 per contact for verified, premium data.

The reality is devastating. With a 5% connect rate, 95,000 of those contacts won't connect despite being "accurate." This translates to 950,000 wasted dials annually—nearly a million attempts that produce nothing but frustration. At 15 seconds per failed dial plus logging time, that's 3,800 hours of SDR time completely wasted.

At an average SDR salary of $50,000, those 3,800 wasted hours represent $190,000 in salary spent on dialing dead numbers. Add the original $50,000 data cost, and you're looking at $240,000 annually for the privilege of failing efficiently.

But the immeasurable cost might be highest of all: the morale damage to SDRs who spend 95% of their time failing, the lost opportunities while dialing bad numbers, and the reputation damage from appearing incompetent to the few prospects you do reach after leaving dozens of failed attempts.

What Actually Works: The ConnectRate Approach

We've abandoned the meaningless pursuit of "accuracy" in favor of measuring what actually matters: connectivity. Our validation process goes deep into the factors that determine whether a human will answer when you call.

Our multi-step validation begins with active line checks—not just whether the number exists, but whether it's actively receiving and answering calls. Line type analysis distinguishes between mobile, landline, and VOIP, each requiring different approach strategies. Answer pattern analysis reveals when specific numbers are most likely to connect based on historical data. Carrier intelligence identifies which provider handles the number and their specific routing patterns. Finally, connection scoring combines all factors to predict the probability of reaching a human.

The results seem counterintuitive at first. We might mark 60% of "accurate" numbers as bad—numbers that format correctly but won't produce conversations. But the remaining 40% achieve 15-20% connect rates, three to four times the industry average. Your SDRs spend their time exclusively on numbers that work, transforming their daily experience from frustration to productivity. The ROI improvement isn't incremental; it's transformational.

The Connectivity Transformation

Software companies illustrate what's possible when they stop chasing accuracy and start demanding connectivity. Starting with 50,000 numbers from ZoomInfo, advertised as 95% accurate with premium verification, typical results include: 4.7% connect rates producing 2,350 conversations and ultimately 235 meetings booked.

After validation, only 18,000 of those 50,000 numbers would typically be marked as high-connectivity. This seems like a loss—"throwing away" 32,000 paid-for numbers. But the results on those 18,000 validated numbers tell a different story: 16.8% connect rates, more than triple the previous performance.

The impact cascades through the funnel. Those 18,000 numbers could produce 3,024 conversations—29% more than calling all 50,000. The higher quality conversations convert better too, potentially yielding 378 meetings, a 61% increase. Companies could make 60% fewer dials but generate 61% more meetings. This isn't optimization; it's transformation.

The Questions to Ask Your Data Provider

Stop asking about accuracy and start asking questions that reveal whether your provider understands what you actually need. Ask what the actual connect rate is when SDRs call these numbers. Watch them squirm as they admit they don't track this fundamental metric. They'll deflect to accuracy rates and verification processes, but they won't answer your simple question.

Ask how they verify someone will answer the phone. They'll describe their format validation and carrier checks, but they'll admit they never actually verify answerability. The most important characteristic of a phone number—whether a human will answer it—is the one thing they never test.

Inquire about the percentage split between mobile and landline numbers. They probably don't know, despite this being crucial for connection strategy. Ask when these numbers were last verified by human calling. The answer is never—it's too expensive and would reveal the truth about their connectivity rates.

Finally, ask if they'll guarantee a minimum connect rate. Watch them recoil at the suggestion. They'll guarantee data freshness, format accuracy, and update frequency, but never the one metric that matters: whether you'll actually reach prospects.

Your Action Plan for Better Data

Week 1 requires a brutal audit of your current data reality. Test 1,000 numbers from your provider—not their cherry-picked samples, but random selections from your actual working lists. Track the real connect rate, not successful dials or valid formats. Calculate your true cost per connection by dividing total data spend by actual conversations. Document the hours your SDRs waste on bad numbers, making the hidden costs visible.

Week 2 shifts to demanding better from your providers. Ask them directly for connect rate data and watch them struggle to provide it. Request connectivity guarantees—if they're confident in their quality, they should back it up. Negotiate credits for numbers that don't connect, not just those that are disconnected. Consider switching providers if they can't meet basic connectivity standards.

Week 3 implements validation as your new standard. Run your existing database through ConnectRate to identify which numbers actually work. Remove unconnectable numbers from your sequences entirely—they're not assets, they're liabilities. Focus your SDRs exclusively on validated numbers and measure the immediate improvement in both metrics and morale.

Week 4 optimizes your process for the long term. Commit to only buying data that includes connectivity metrics, not just accuracy claims. Validate every new batch before your SDRs dial a single number. Track connect rates by source to identify which providers deliver real value. Hold providers accountable for connectivity, not just accuracy, and watch your entire sales operation transform.

The Future of B2B Data

The market is slowly waking up to this problem. Forward-thinking providers are starting to measure what matters:

We validate connectivity rates to show which numbers actually work. We analyze answer patterns to predict who's likely to pick up. We identify the best time to call specific numbers based on historical data. We provide line quality scores that indicate the probability of human connection.

But most are still selling "accuracy" while you need connectivity.

The Bottom Line

Your data provider isn't lying when they say their data is 95% accurate. They're just measuring the wrong thing.

A perfectly accurate phone number that never connects is worthless. A slightly outdated number that consistently reaches the right person is gold.

Stop buying accuracy. Start demanding connectivity.

Your SDRs don't need more accurate data. They need data that connects.

Tired of "accurate" data that doesn't connect? See how ConnectRate turns your 95% accurate data into 15%+ connect rates and transforms your SDR productivity.