Evaluation Playbook: How To Choose A Data Provider For Volume

Struggling to find the right data provider?

If you’re focused on hitting ambitious growth targets, you need more than just a large database.

You need a data partner with real reach, strong coverage across your ideal customer profile, and the ability to consistently deliver pipeline, not just promises.

This playbook will help you evaluate providers based on what actually drives results: meaningful volume, high match rates, and data you can trust.

Because buying a big list without a clear strategy won’t move the needle.

What matters is quality beneath the surface, think bounce rates, coverage of the decision-makers you actually need, and how recently that data was verified.

Is your data volume holding back growth? 

Quantity in data is about finding the right fit at scale.

Data volume is the foundation of any scalable go-to-market motion. If you don’t have enough records in your CRM that match your ideal customer profile (ICP), your campaigns will stall before they start.

This becomes especially critical when:

• You’re launching a new outbound sales motion.
• You’re entering a new region and lack local contacts.
• You’re running account-based marketing (ABM) but missing key buying committee contacts.
• Leadership is asking for a bigger pipeline, faster.

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

"If your database doesn’t reflect your ICP, you’re not just missing opportunities - you’re handing them to competitors." 

But here’s the catch: volume without strategy leads to noise. You want to scale precision, not just numbers.

Key evaluation questions for assessing data volume 

How much data is enough?

It depends on your TAM and funnel model. But if you’re consistently struggling to hit volume goals, start by mapping your ICP coverage. Most vendors can help with this as part of a sample test.

What if I already have a provider?

If you’re happy with data quality but struggling on scale, consider layering a second provider focused on volume. Just make sure you have deduplication rules in place.

Should I choose a global provider or regional specialists?

For pure volume, global databases offer scale - but regional providers often outperform in specific markets (e.g. Germany, Benelux). If you’re targeting multiple regions, a hybrid approach may be best.

Volume vs. quality: Know what you’re trading off 

While this guide focuses on volume, you still need to keep quality in the picture. Here’s how volume-first stacks up:

“We always check: is Sales asking for volume, or are they just asking for better contacts? Sometimes what sounds like a quantity issue is really a quality issue.” 

What good looks like in a volume evaluation

In a volume-driven evaluation, your job is to build scale without trashing your database. These are the metrics that should drive your evaluation:

• Match rate against your CRM and ICP.
• Fill rate of net-new contacts (especially email + mobile).
• Volume of usable leads per region/persona.
• Recency of data (how often records are refreshed).
• Cost per usable contact (after bounce, duplicates, and gaps).

How to evaluate providers when volume is the priority

1. Prioritise unknown data testing

Run some blind dates with data, testing it out before you commit!

When you’re evaluating a data provider based on volume, your priority isn’t verifying what you already have - it’s discovering how well they can fill the gaps. That’s where unknown data testing becomes your most important tool.

What is unknown data testing? 

Unknown data testing is when you ask a vendor to deliver a sample of net-new contacts that match your ideal customer profile (ICP) - contacts you don’t already have in your CRM. This test helps you evaluate:

• The breadth of the vendor’s coverage in your key segments.
• The accuracy and freshness of their contact records.
• The relevance of the data to your go-to-market motion.

Unlike known data testing (where you enrich a list of verified contacts from your CRM to check accuracy), unknown testing gives you a real-world preview of how usable and scalable the vendor’s data actually is.

Jeff said:

"Unknown testing is your stress test. It’s the best way to find out if a vendor can really power your next campaign - or if they’re just good on paper."

How to run unknown data testing 

Here’s how to get the most value from an unknown data test:

Define your ICP segment clearly

Choose a sample segment that reflects your actual targeting priorities. For example:

•  SaaS companies in EMEA with 50–200 employees.
•  Finance or Ops leaders in North America.
•  Procurement managers in the manufacturing sector.

Request a net-new contact list from the vendor

•  Set expectations: 500–1,000 records minimum is ideal for analysis.
•  Ensure the sample includes a mix of geographies, industries, and job titles.
•  Ask the vendor to tag each record with source and last updated date, if available.

Ask for monthly delivery estimates

If you plan to scale, volume is not a one-off requirement. Ask:

•  How many new, ICP-aligned contacts can we expect every month?
•  Can you deliver consistently in each region we care about?
•  Are there delivery throttles tied to credits, tiers, or pricing plans?

Assess data completeness

Evaluate the sample for these key fields:

•  Business email (validated).
•  Mobile or direct dial.
•  Current job title and function.
•  Company name, industry, employee size, revenue band.
•  LinkedIn or social handles (optional but useful).

Viktoria Rubble, Cognism’s Chief of Product, Data and Technology, said:

"The best unknown tests tell you not just if the vendor has data, but whether they have the right data for your GTM engine."

Bonus Tip:

Compare the unknown to your ICP heatmap. If you’ve mapped out your total addressable market (TAM) or ICP coverage by region and persona, overlay the vendor’s sample onto that. 

Ask:

• What % of our TAM can they actually reach?
• Are there any persona or regional blind spots?
• How fast can they refresh or expand on this list over time?

By running structured unknown data testing, you move beyond marketing promises and uncover the vendor’s true capacity to drive top-of-funnel growth.

It’s the single best way to avoid being underwhelmed after the contract is signed.

2. Score fill rate and deliverability

When evaluating for volume, raw contact numbers are meaningless unless those contacts are complete and usable.

That’s where fill rate and deliverability come in.

Fill rate refers to how many key data fields are actually populated for each record - especially the ones your teams rely on most, like verified email addresses and mobile phone numbers.

Without these, the record is just noise in your CRM.

Here’s what to aim for:

• 60–70% of records should include both a verified email and a mobile number, especially if you’re running outbound motions or automated workflows.
• For phone-based outreach (e.g., SDR teams), mobile coverage is critical. Some providers may claim strong volume, but deliver mostly desk numbers - or worse, no numbers at all.

Deliverability, meanwhile, determines whether that contact info actually works. A high fill rate is irrelevant if half the emails bounce.

What to test:

• Run a small email campaign to measure bounce rates. Your target is under 5%, ideally under 3%.
• Validate mobile numbers by sampling with call connect rates or using a phone validation tool.
• Check for field consistency and formatting - messy data creates headaches in routing and scoring.

Sandy said:

"We don’t just look at what’s filled in - we look at how many records are truly ready to use. Fill rate tells you what’s there. Deliverability tells you what works."

And don’t forget recency. Ask vendors:

• How often is your contact database validated and refreshed?
• Are updates made weekly, monthly, or quarterly?
• How do you handle job changes or role transitions?

Stale data means high bounce rates and wasted outreach, especially if the vendor isn’t flagging old records or detecting changes in job titles.

Viktoria said:

“About a third of your data will go bad every year. If a buying committee has eight people, you’re probably targeting two or three that are no longer relevant within 12 months.” 

3. Check regional and role-based strengths

When you’re evaluating a vendor for data volume, it’s easy to be impressed by the size of their overall database.

But here’s the catch:

Total contact count doesn’t mean total coverage for you. Especially if your GTM motion is global or persona-specific.

Not all data providers are built the same when it comes to regional depth or job function accuracy. Many will perform well in high-volume markets like the US or UK, but fall short in places like the DACH region, France, or Southeast Asia - where data collection, privacy laws, and language barriers create friction.

Viktoria said:

“Europe is not one thing. Even amongst the EU, data collection and compliance laws are unique from country to country.” 

And even within a market, some vendors might crush it for Sales and Marketing personas but lack depth in Product, Engineering, or Finance roles - often due to how they source their data (e.g., LinkedIn scraping, technographic signals, publisher partnerships).

Role-based blind spots are real 

Sales and marketing personas are often overrepresented in vendor datasets because they’re easier to track.

But for more niche or less externally visible roles (like Procurement, Legal, or Product Ops), coverage can be surprisingly thin.

If you’re running ABM campaigns or targeting a full buying committee, this can be a huge blocker.

Jeff said:

“Don’t wait until after you buy to realise the vendor can’t deliver for half your personas. Always test by job function, not just region.” 

A real-world vendor testing example

Let’s put this into practice with an example use case.

Imagine you’re a RevOps leader at a growth-stage SaaS company, and your outbound sales and demand gen teams are gearing up to expand across Europe. 

Your executive team has tasked you with increasing CRM coverage and lead volume for the UK and DACH regions to fuel Q3 pipeline targets.

Your ICP looks like this:

• Region: UK and DACH (Germany, Austria, Switzerland).
• Industry: B2B SaaS.
• Company size: 50–200 employees.
• Personas: Marketing, Sales, and Revenue Operations professionals.
• Seniority: Manager and above.

You’re evaluating three data vendors to see who can best deliver high-volume, usable, and relevant net-new contacts for this segment.

Step 1: Define the test brief 

Provide each vendor with a written request that includes:

• A short description of your ICP.
• The regions and job functions you’re targeting.
• A clear ask: “Please provide 500–1000 net-new contacts that match this criteria”.
• Field requirements: verified email, mobile number, job title, company name, industry, employee size, country.
• Request that they include source information and the last updated date if available.

This gives each vendor the same conditions and lets you run a controlled side-by-side comparison.

Step 2: Receive the data samples 

Once you get the sample data from each provider, do a quick check for:

• File formatting and field consistency.
• Whether they included the required fields.
• Any red flags like missing job titles, blank regions, or obviously off-ICP records.

Bonus tip:

Have your sales team skim a portion of each list and flag any records that look like noise - this qualitative feedback is often just as telling as the metrics.

Step 3: Score the vendors 

Here’s what to measure once you’ve received the sample data:

Fill rate 

• % of records that include verified email and mobile.
• % with complete job title, seniority, and company info.
• Tip: Pay special attention to mobile number availability for SDR workflows.

Bounce rate 

• Run a small test campaign or validate emails through a deliverability tool like NeverBounce or ZeroBounce.
• Target <5% bounce rate.
• Ask: Were the emails valid, or did a concerning portion bounce back?

Title/job relevance 

• Are the job titles aligned with your ICP (e.g., not “Marketing Assistant” or “Sales Intern”)?
• Does the seniority level make sense for your outreach goals?
• Are the contacts clearly decision-makers or influencers?

Recency of updates 

• Are job titles current?
• Are company names and roles aligned with LinkedIn or other sources?
• When was the data last refreshed or verified?

Viktoria said:

"You’d be surprised how many vendors will hand you old job data. Always ask for the ‘last updated’ field - or check a few manually on LinkedIn."

How to present vendor test results internally

Build a simple comparison table that looks something like this:

This visual approach makes it easier to align with stakeholders and clearly see which vendor is the best fit - not just in theory, but in actual usability and relevance.

Key questions to ask a data provider when volume is the priority

Use this checklist in your vendor interviews:

When you’re selecting a data provider based on their ability to deliver high-volume, usable contact records, your vendor interviews need to go beyond the standard sales pitch.

You want to ask questions that help you uncover how scalable, reliable, and targeted their data really is - before you commit.

Use this list of volume-focused questions to guide your conversations. These aren’t just checkboxes - they’re designed to reveal limitations, gaps, and the vendor’s true operational strength.

1. What percentage of your database has been refreshed in the last 6 months?

High-volume vendors often tout the size of their database, but that number is meaningless if a significant portion is outdated.

Data decays fast - titles change, people leave roles, and contact details become invalid.

Aim for: At least 30–50% of their database refreshed in the past 6 months.

What to look for:

• Do they have an automated refresh cadence?
• Can they show timestamped updates?
• Is recency tracked by region or persona?

2. Can you provide contact volume breakdowns by region, industry, and job function?

You’re not just buying a database - you’re trying to reach specific people in specific places doing specific jobs.

If a vendor can’t slice their dataset by these dimensions, they likely can’t support your GTM strategy at scale.

What to look for:

• Total addressable volume for your ICP.
• Gaps in regional coverage (especially for EMEA/APAC).
• Persona-specific counts (e.g., how many verified CMOs in SaaS in DACH?)

Pro tip:

Ask for a CSV export of these breakdowns to cross-reference against your ICP map.

3. How many net-new ICP-matching contacts can you deliver monthly?

Your volume needs are ongoing, not a one-and-done upload. This question checks the sustainability of the vendor’s data pipeline.

What to look for:

• Monthly or quarterly delivery commitments.
• Variation by geo or persona.
• Whether volume scales with credits/seats or is truly flexible.

Jeff said:

"We’re not just testing what you can give us now. We’re testing what you can give us every month for the next year."

4. What is your historical bounce rate across net-new records?

A vendor that can deliver 10,000 leads but with a 15% bounce rate isn’t delivering value.

High bounce = wasted budget, hurt deliverability, and lost credibility with Sales.

What to look for:

• Average bounce rate (email) for new data samples.
• Comparison by region or job function.
• Internal validation practices (e.g., SMTP ping, AI verification, manual checks).

Target: Consistent bounce rates under 5% and under 3% for high-performing vendors.

5. Do you cap enrichment or list pulls by credit, seat, or region?

Many vendors promote flexibility but hide usage limits behind complex pricing models.

This question uncovers friction that might block scale.

What to look for:

• Are credits used per record, per field, or per contact?
• Are there regional caps (e.g., different pricing for EU vs. US contacts)?
• Does pricing scale with team size, record volume, or platform usage?

Be wary of plans where you “run out of credits” too quickly or can’t export data freely.

6. Can you enrich leads at the point of creation, or only in batch?

This reveals how well the vendor integrates into your workflow.

If you need real-time enrichment (e.g., as new leads enter your funnel), batch-only processes may slow you down.

What to look for:

• Native integrations with your CRM, MAP, or sales engagement platform.
• API access or webhook support for lead creation.
• Whether real-time enrichment costs extra.

Ideal vendors allow auto-enrichment at the point of entry, reducing manual effort and improving time-to-lead.

Warning signals to watch for

Volume-focused buying can be dangerous when short-term goals override long-term quality.

Watch out for:

• Bounce rates over 10% on unknown data samples - this signals decay or poor verification.
• Vendors with email-only records - mobile numbers are critical for SDR and BDR productivity.
• Databases that claim millions of contacts but can’t deliver for your ICP or region.
• Lack of transparency on data sourcing, update cycles, or compliance.
• Vague answers to persona-specific breakdowns.

Viktoria said:

“Anyone can give you 10,000 contacts. But if 2,000 bounce, 3,000 don’t match your ICP, and 2,000 are missing fields, you’re not buying data - you’re buying cleanup work.” 

What makes a successful data vendor partnership?

Buying a high-volume data solution is only the beginning.

Real success comes when your contact volume directly supports pipeline generation, drives conversion, and actually gets used by your GTM teams.

Here’s how to know your volume-first strategy is paying off:

CRM coverage grows by 30%+ in the first 90 days 

One of the clearest indicators of success is how quickly your database grows in meaningful ways.

It’s not just about total records - it’s about how much of your target market is now reachable.

• Run a before-and-after audit of your CRM: what percentage of ICP accounts now have associated contacts?
• Pay special attention to previously underrepresented personas or regions.
• Look for lift in key verticals or territories you’re expanding into.

Email bounce rate stays under 5% on net-new data 

High bounce rates kill email deliverability, credibility, and SDR morale. If you’re buying in volume, keeping bounce under control is essential.

• Use tools to validate new data before sending campaigns.
• Track bounce rates not just at the list level, but also by vendor if you’re using more than one.
• A consistently low bounce rate means your vendor isn’t just delivering in bulk - they’re delivering data you can trust.

Viktoria said: 

“Bounce rate is the canary in the coal mine. If it spikes, it’s a sign something’s off in your sourcing or recency.”

Mobile field fill rate is over 60% for outbound-focused personas 

In a high-volume motion - especially one driven by SDRs or BDRs - mobile numbers are gold.

If most of your records are email-only, your dial-to-connect ratio will suffer, and so will productivity.

• Track the % of net-new contacts that include a mobile number (not just a desk line).
• Break it down by persona: Sales personas typically have higher mobile visibility than Product or Finance roles.
• Use this metric to spot vendor strengths or gaps.

Cost per usable contact is decreasing over time 

This is where quality and scale intersect.

You might start with a higher cost per usable contact if you’re testing multiple vendors, but over time, that number should go down, not up.

• Track how many records you’re discarding (bounced, duplicate, or incomplete).
• Calculate: (Total Spend) / (Usable, Valid Contacts).
• As you optimise vendors and refine your ICP, you should see better ROI with each new batch of data.

Pro tip:

Include internal time costs in your calculation. If you’re spending hours cleaning up bad data, your cost per contact is higher than it looks.

Sales and marketing adoption increases 

It’s not a success if the data sits unused.

One of the most telling success indicators? Your GTM teams trust and rely on the data you’re buying.

• Are SDRs using enriched data for outreach?
• Is marketing launching campaigns based on new segments now available in your CRM?
• Is sales pushing back less on lead quality?
• Are usage rates up in the CRM or sales engagement tool?

Jeff said:

“We see success when Sales stops asking, ‘Where did this lead come from?’ and starts saying, ‘Send me more like this.’” 

Measurement scorecard

To maintain momentum (and secure budget for renewals), track these core KPIs monthly or quarterly:

You can also pull in qualitative feedback:

• Are reps reporting more productive outreach?
• Is marketing able to run new campaigns that were previously blocked due to data gaps?
• Are lead scoring models improving with richer data fields?

Final takeaways: Your data partnership stars here

If you’re shopping for data to scale fast:

• Make sure you’re testing unknown data that mirrors your actual targeting needs.
• Score vendors not on how much data they have, but how much usable data they can provide.
• Don’t ignore red flags like high bounce rates or lack of regional/persona insight.
• Involve your sales, marketing, and ops teams in the testing and decision process.

With the right approach, you can transform a shallow CRM into a well-segmented, high-performing database that powers outbound success.