Date-a-vendor Evaluation Playbook #3 'We Need Data Volume & Quality!'

The playbook for SaaS teams who want scale and substance from their data provider.

You’ve dated around. One vendor wowed you with volume, but ghosted when it came to accuracy.

Another had great data - if only they knew your type and lived in your region.

But you’re not here for short-term thrills. You’re looking for someone who can show up consistently, scale with you, and help you grow.

This playbook is for marketers, RevOps, and GTM leaders who want the total package: reach and reliability, volume and value.

Because you shouldn’t have to choose between getting seen and getting results.

You deserve someone who’s got range and reliability 🙌

When you optimise only for volume, you risk bloat: bloated CRMs, bloated bounce rates, bloated budgets.

When you optimise only for data quality, you risk constraint: limited reach, slow campaign velocity, stagnant pipeline.

Modern GTM motions demand both.

• Sales teams need verified, direct dials and enough accounts to hit quota
• Marketing needs complete contact records and enough volume to feed automation
• RevOps needs CRM enrichment that’s accurate and comprehensive

This is especially critical when:

• You’re scaling into new regions or verticals.
• You’ve outgrown your initial data stack or outpaced your current provider.
• You’re consolidating vendors and need to balance cost with performance.

Your ideal match 😍

Use this blended scorecard when evaluating data vendors for both reach and reliability:

• ICP match rate: How well does the vendor cover your ideal personas and company profiles?
• Fill rate: What % of contacts come with verified phone, email, title, and company info?
• Email bounce rate: What % of email addresses are valid and deliverable?
• Mobile coverage: Especially for sales and SDR motions.
• Data recency: How frequently is the database refreshed?
• Regional strength: Can they go deep in your core markets (e.g., UK, DACH, US)?
• Monthly delivery capacity: Can they keep delivering fresh, usable contacts?
• Field-level enrichment: Is the data complete enough to use without additional work?

Common questions when your type on paper is quality and volume 😻

Is it possible to get both volume and quality from one provider?

Sometimes - but not always.

Many vendors lean heavily toward one strength. That’s why testing both known and unknown data is essential. If one provider can’t deliver both, you may need a dual-vendor strategy.

Which matters more - quality or coverage?

It depends on your motion.

For outbound SDR teams, connectability and completeness (quality) are crucial.

For ABM or territory expansion, scale and reach (coverage) may take the lead. Most teams need both.

How do I avoid paying for bad data in large volumes?

Track cost per usable contact - not per lead. Combine fill rate, bounce rate, and persona relevance to calculate your true ROI.

Volume is meaningless if 30% of the list is unusable.

Should I test both dimensions at the same time?

Yes. Run a two-part test: known data (for accuracy) and unknown data (for reach). Then score vendors on both performance and consistency across segments.

Jeff Ignacio, Head of GTM Operations at Keystone AI, said:

“The worst outcome is lots of data no one uses. The second worst? Great data, but not enough of it.” 

Coverage vs. quality: Who’s got the full package? 📦

When you’re evaluating for both reach and reliability, the question isn’t “which is better?” - it’s “who can deliver both?”

Not all vendors are equally balanced. Some will shine in volume but fall short on accuracy. Others might deliver pristine data, but in limited segments or geos.

The goal is to find a provider that offers scale you can trust.

Jeff said:

“Most teams don’t have the luxury of optimising just for one thing. You need the scale to grow, and the quality to convert. That’s why we test both known and unknown data every time.”

Green flags to look out for 💚

When coverage and quality matter, you’re aiming to grow your contact database without compromising on performance.

That means identifying vendors who can deliver usable volume, not just raw contacts, and accurate enrichment, not just pretty dashboards.

Here’s what your scorecard should include:

• Match rate (CRM & ICP): High overlap with your known accounts and target personas.
• Fill rate (email + mobile): At least 80% of contacts with usable contact fields.
• Mobile coverage: Especially for Sales and SDR personas; aim for 60%+.
• Data recency: Updated every 30–90 days, with visible timestamps.
• Email bounce rate: <3% from net-new and enriched samples.
• Persona & regional relevance: Can they go deep where it counts?
• Monthly volume capacity: Can they scale with your outbound or ABM motions?
• Cost per usable contact: Includes enrichment depth, QA time, and activation rate.

What success looks like:

• Enough volume to hit outreach goals.
• Clean, complete records that actually drive connects and conversions.
• Sales and Marketing trust the data, and use it.

Antoine Cornet, Cognism’s Head of Revenue Operations, said:

“Buying for both coverage and quality isn’t easy. But if you get it right, it becomes a RevOps flywheel - not a friction point.” 

How to date when you’re prioritising quality and volume 💓

When your business is scaling fast but also demands accuracy, a blended evaluation approach is essential. You can’t afford to buy bloated lists full of junk, nor can you succeed with pristine data that doesn’t cover enough of your ICP.

To get both, you need to combine the rigour of a quality-focused evaluation with the stress tests used to assess volume and coverage.

That means using both known and unknown data testing, and scoring vendors across a balanced set of metrics.

1. Run both known and unknown data testing ✅

This is the gold standard approach. It helps you understand:

• How accurately the vendor can enrich what you already know.
• How well they can expand your reach into new, net-new territory.

Jeff said:

“Known testing gives you a baseline for trust. Unknown testing shows you what scale looks like in your ICP.” 

Here’s how to set it up:

Known data testing - Your accuracy benchmark

• Export 500–1,000 trusted contacts from your CRM (recently engaged leads, converted opps, or SDR-qualified contacts).
• Include a representative sample across geos, verticals, and job functions.
• Ask each vendor to enrich the list with:
  • Verified business email.
  • Mobile or direct dial.
  • Job title and seniority.
  • Updated company information.

What to measure:

• Match rate: % of your records the vendor can enrich.
• Field-level accuracy: Are the enriched fields correct? Check manually or against LinkedIn.
• Fill rate: Are all key fields populated? Any blank or “filler” records?

Unknown data testing – Your scale and coverage stress test

• Give vendors your ICP criteria by region, industry, and persona.
• Ask for 500–1,000 net-new contacts that are not already in your CRM.
• Request delivery of full profiles, including contact and company data.

What to measure:

• Relevance: Do the contacts match your persona and ICP?
• Volume: How many usable contacts can they return at your desired monthly cadence?
• Bounce rate: Test deliverability with a small campaign (<5% is acceptable; <3% is ideal).
• Mobile coverage: % of records with working direct dial or mobile numbers.
• Recency: How recently was the data verified?

2. Score for both completeness and reach ✅

Once you’ve collected the results, use a blended lead scoring model that values both field-level quality and net-new potential.

Top tip:

If a vendor scores well in known testing but low in unknown, they might be strong at enrichment but weak on coverage.

If they do well in unknown testing but struggle to enrich known records accurately, the data may be outdated or inconsistently verified.

What you want:

Consistency across both tests. A provider that can enrich reliably and scale with you over time.

Taking the date out of the DMs: A real-world testing example (balancing quality and coverage) ❣️

Let’s walk through how a real RevOps or Marketing Ops leader might evaluate a data vendor when both coverage and quality are non-negotiables.

You’re leading GTM operations at a mid-market SaaS company. Your SDR team is ramping outbound in North America, your Marketing team is launching ABM campaigns in the UK and DACH, and you’ve just been asked to consolidate data providers without losing scale.

Your ICP includes:

• Regions: United Kingdom, DACH (Germany, Austria, Switzerland), and North America.
• Industries: B2B SaaS and Fintech.
• Personas: Revenue Operations, Demand Generation, and GTM Leadership.
• Seniority: Manager level and above (ideally Director+).

You need to validate who can deliver the volume to scale, and the accuracy to convert.

Step 1: Run a known data test ✅

This is your data trust check. You’re testing vendors on their ability to enrich contacts you already know are accurate.

How to run it:

• Export 750 known-good contacts from your CRM: recent MQLs, closed-won opportunities, or high-intent leads where you’ve manually verified the contact info.
• Make sure to include a mix across:
  • Regions (UK, Germany, North America).
  • Job functions (RevOps, Demand Gen, GTM).
  • Seniority levels (Manager, Director, VP).
• Send this list to each vendor and ask them to enrich with:
  • Verified business email.
  • Mobile/direct dial.
  • Job title and department.
  • Company information (industry, employee size, revenue).
  • Optional: LinkedIn/social URLs, last verification timestamp.

What to evaluate:

• Match rate – how many records can they enrich?
• Accuracy – does the data match your trusted CRM record?
• Fill rate – how many records include all core fields?
• Staleness – are any titles or companies outdated?

Top tip:

Have someone manually review a 10–15% sample across vendors using LinkedIn to confirm accuracy and detect role changes.

Step 2: Run an unknown data test ✅

This is your scalability check. You’re testing whether vendors can deliver net-new contacts that match your ICP and fill your pipeline.

How to run it:

• Define a precise ICP segment. For example:
  • Fintech CMOs in Germany.
  • Demand Gen Directors in UK-based SaaS companies.
  • RevOps leaders at US-based startups with 50–500 employees.
• Ask each vendor to deliver 1,000 net-new contacts across your defined segments.
• Request:
  • Full contact profiles (email, mobile, title, company, LinkedIn).
  • Breakdown by persona and region.
  • Data freshness (when was it last validated?).

What to evaluate:

• Relevance - do the job titles and companies align with your ICP?
• Volume - can they deliver at scale, across multiple geos and personas?
• Fill rate - are contacts complete and usable?
• Bounce rate - run a small test email campaign or use validation tools (e.g., NeverBounce) to check deliverability.
• Mobile accuracy - have SDRs dial a sample of records to check connectability.

Step 3: Scorecard comparison: Can you see a future with them? ✅

Once both tests are complete, it’s time to compare vendors side-by-side using a structured scorecard.

This helps ensure your decision is data-driven, not gut-driven.

Build your scorecard:

Also gather subjective input:

• Ask your SDRs: “Would you actually call these leads?”
• Ask Marketing: “Would you launch a campaign to this list tomorrow?”
• Overlay the results with your ICP heatmap:
  • Which vendor had the best reach in DACH?
  • Who delivered the most mobile numbers for RevOps leaders?
  • Which records were most complete and relevant?

This mixed-method approach gives you both quantitative and qualitative insight into which provider can support your GTM motion effectively.

Adam Thompson, CPO at Cognism said:

“Testing for both known and unknown gives you a full picture—what vendors say and what they can actually deliver are rarely the same.” 

First date questions (when balancing quality and volume is the goal) 💗

When your evaluation hinges on getting both accurate and scalable data, surface-level answers won’t cut it.

These questions are designed to test a vendor’s operational maturity, transparency, and ability to meet your real-world GTM demands.

1. Can you support both net-new contact delivery and enrichment of existing records?

Why it matters:

Some vendors excel at adding new contacts, others at enriching what you already have - but few can do both well.

You need a partner who can scale your reach and improve your existing CRM data.

What to look for:

• Ability to enrich existing contacts with updated job titles, phone numbers, etc.
• Dedicated enrichment workflows (real-time and batch).
• Net-new delivery capacity tailored to your ICP (by persona, region, vertical).
• Support for CRM integrations to streamline both motions.

🔎 Top tip:

You can also ask, “Can you provide examples of customers using you for both net-new pipeline generation and CRM hygiene?”

2. What percentage of your database has been updated in the last 90 days?

Why it matters:

Volume without recency = bounce rates, misfires, and wasted reps’ time.

Data decays quickly - especially in fast-moving industries or senior roles. You want a vendor who’s actively refreshing, not just accumulating stale records.

What to look for:

• 30–50%+ of records updated quarterly is a good benchmark.
• Transparency on refresh cycles (daily, weekly, monthly?).
• Timestamped “last verified” fields or confidence scoring on records.
• Automation or signals for job changes, company moves, or role shifts.

3. Can you break down your contact volume by persona, geo, and seniority?

Why it matters:

Most databases are heavily weighted toward generic job titles or popular geos (like the US or UK).

If you’re expanding into EMEA or targeting niche buyers (e.g. RevOps in Fintech), you need specific depth, not just bulk.

What to look for:

• Granular breakdowns: e.g., “We have 14,000 Demand Gen Directors in the UK fintech sector”.
• Insights by seniority: % of records Director+ vs. entry-level.
• Regional strengths and blind spots—are they strong in DACH? APAC?
• Persona mapping to your ICP roles (Sales, Product, Finance, Ops, etc.).

4. How do you verify mobile numbers and job title data?

Why it matters:

Mobile numbers and job titles are make-or-break for outbound campaigns and lead scoring.

Poor verification leads to failed connects, bad segmentation, and frustrated reps.

What to look for:

• Verification methods (carrier ping, call validation, LinkedIn matching, third-party signals).
• Confidence scores per field (e.g., “verified”, “likely”, “guessed”).
• Detail on title taxonomy—can they enrich with role level and department?
• Accuracy stats: historical connect rates, job title precision benchmarks.

5. What’s your monthly delivery capacity by region, industry, and persona?

Why it matters:

You need to know if the vendor can consistently deliver fresh, usable contacts at the pace your team needs - not just a one-time bulk drop.

What to look for:

• Monthly delivery potential across your target regions (e.g., “We can deliver 1,000 net-new C-level contacts in DACH every month”),
• Segmentation capabilities—can they scale by vertical or job function?
• Flexibility with delivery formats: API, CSV, platform sync,
• Whether delivery is capped by credits, seats, or volume tiers,

Red flags to watch for 🚩

• Vendor performs well on net-new samples but struggles to enrich known records.
• Email-only records dominate the dataset with low mobile match.
• No timestamps or transparency around data refresh cadence.
• Weak performance in key ICP segments or regions.
• High bounce rates (>5%) and vague answers about source validation.

What does a successful relationship look like? (and how to measure it) 💕

When you’ve chosen a vendor that delivers both coverage and quality, you’ll start seeing impact across the sales funnel - not just in the number of contacts added, but in how effectively your teams use that data to generate pipeline.

In a balanced evaluation, success = scalable reach without sacrificing usability.

Here’s how to spot the signs that your provider is actually delivering - and how to prove it with real metrics.

Signs of a potential match 👨‍❤️‍👨

Your CRM is meaningfully enriched

The number of ICP contacts increases, and those contacts are complete and accurate - emails are verified, mobile numbers work, and job titles align with your targeting models.

Bounce rates fall across campaigns

Your outbound and nurture sequences experience fewer delivery issues, which improves email reputation and reduces the time SDRS spend chasing ghosts.

Your team can dial and connect

Sales reps see more mobile numbers in the CRM and, more importantly, those numbers connect. Connect rates go up, and rep morale improves.

You’re hitting volume goals without quality drop-off

The vendor is delivering enough net-new contacts every month to sustain your GTM cadence - without data decay, field gaps, or growing bounce rates.

Conversion metrics improve downstream

Better contact data = better targeting.

Campaigns become more personalised, outreach becomes more relevant, and lead → opportunity conversion rates improve.

Manual cleanup slows down

RevOps and Marketing Ops teams report fewer junk leads, less time spent deduping or rerouting, and less friction between sales and marketing.

Antoine said:

“The biggest indicator of success isn’t just what gets delivered—it’s what stops happening. Fewer bounced campaigns, fewer complaints, fewer data fire drills.” 

KPIs to track over time (to see if you’ve found ‘the one’) 💝

Monitoring the right KPIs - on a monthly or quarterly cadence - helps you validate performance and hold vendors accountable.

Don’t just look at output - look at impact

It’s not just about how much data you got - it’s about what changed:

• Did campaigns that previously underperformed start generating pipeline?
• Are SDRs booking more meetings without asking for manual fixes?
• Is sales pushing back less on lead quality?
• Are fewer records getting tagged as “junk” or bounced back to marketing?

These questions help you measure adoption, trust, and business impact - the true signs that your data partner is delivering on both sides of the equation.

Final takeaways: Have you found your perfect match? ❣️

If you need both reach and reliability:

• Don’t choose between known and unknown testing - do both.
• Score vendors on real-world usability, not database size.
• Involve Marketing, Sales, and Ops in testing and feedback.
• Use side-by-side comparisons and an ICP heatmap to guide the decision.

With the right partner, you won’t have to choose between quality and scale - you’ll get both.