I needed a clean enrichment test because our outbound motion kept hitting two problems: bad email deliverability eating our sender reputation, and near-zero direct dial coverage for US SaaS VP-level contacts. I ran Apollo, RocketReach, and People Data Labs against the same 500-contact list and measured what each one returned, what was actually deliverable, and what the cost per valid contact worked out to.
The list was 500 VP-level contacts — VP of Sales, VP Engineering, VP Product — at US SaaS companies with 50–500 employees, Series A through Series C. I verified each contact's current employer and title through LinkedIn manually before the test, so job-change decay wasn't a variable. Every email returned was then run through ZeroBounce before counting it as valid.
What each tool was built to do
This framing matters before the numbers, because these tools are built around different use cases and optimizing for different things.
Apollo is a full sales intelligence platform. The email finder is embedded in a broader workflow tool that includes sequences, CRM sync, and intent signals. You're paying for the workflow; the data is the raw material feeding it. This shapes how Apollo prioritizes accuracy — it's good enough for the workflow it serves, but it wasn't designed to be a precision data layer.
RocketReach is a standalone lookup tool. Give it a name and company, get email and phone. No sequences, no CRM integration by default. It competes on depth for individual lookups, especially for executives. The credit model reflects that positioning — you pay per lookup, not per seat.
People Data Labs is an API for engineering teams, not a sales UI. You query it with a LinkedIn URL, email, or name-company combination; it returns everything it has — current and historical emails, phone numbers, job history, education, skills. You own verification, deduplication, and cleanup. This distinction between raw coverage and verified coverage is critical, and it's where most PDL comparisons go wrong by treating the two numbers as equivalent.
Email coverage: Apollo finds more, RocketReach misses less
On the 500-contact test list:
Apollo returned an email for 441 contacts (88.2% coverage). After ZeroBounce validation, 81.3% of those cleared deliverability checks — putting valid, verified emails at roughly 358 contacts out of 500, a 71.6% end-to-end hit rate.
RocketReach returned an email for 411 contacts (82.1% coverage). 79.4% passed ZeroBounce — giving 326 valid contacts, a 65.2% end-to-end rate.
People Data Labs returned at least one email for 412 contacts (82.4%) — but this is before any verification. After ZeroBounce, about 78% held up. That's 321 contacts with verified email. PDL returns multiple historical addresses per person, so I counted any match that passed validation. Worth noting: not all of those were current-employer addresses. After filtering to current employer only, coverage dropped to closer to 350 contacts before verification, or roughly 280 verified — a 56% end-to-end rate for current-employer email specifically.
Apollo's coverage edge is real. The gap between finding an email and having a deliverable email is larger than their marketing emphasizes.
Bounce rates: the number Apollo doesn't put in the headline
The numbers above came from ZeroBounce validation, not live sends. When I sampled 150 of the Apollo-returned addresses on an actual send sequence, the measured bounce rate was 9.1%. ZeroBounce caught most hard bounces but missed catch-all domains and several role-based addresses that appeared valid but weren't delivered.
RocketReach was cleaner on catch-alls. It returned fewer addresses on ambiguous domains and skipped more catch-all MX configurations. This likely explains its lower bounce rate in live sends despite lower raw coverage. For sender reputation management, fewer high-confidence returns beats more variable returns — especially when you're sending at volume and one bad day can dent your domain score.
People Data Labs requires you to handle catch-all filtering yourself. The API returns what it has; determining whether an address is catch-all or role-based is your problem. That's not a criticism — it's the trade-off you accept for programmatic access and lower per-record cost.
Phone numbers: where all three underperform
Direct dial coverage was poor across the board for this segment. VP+ contacts at growth-stage SaaS companies are among the hardest to reach via direct dial in any database.
Apollo returned a direct dial or mobile number for 118 contacts (23.6%). A test batch of 30 calls confirmed about 60% were active and reached the right person — an effective verified direct dial rate of roughly 14% across the full list.
RocketReach returned phone for 97 contacts (19.4%). These are mobile and direct combined; RocketReach doesn't consistently separate them in the standard export. Accuracy on a test subset was comparable to Apollo at about 58%, putting effective coverage at roughly 11%.
People Data Labs returned at least one phone field for 40% of contacts — matching their documented coverage rates. That's 198 contacts with a phone entry. A manual check on 25 of them showed 44% were still active and matched the right person. Unverified historical phone numbers are common in PDL's output, especially mobile numbers that followed a person across job changes.
For US SaaS VP contacts, none of these three gives you enough verified direct dial to build a phone-first outbound motion. Lusha and Cognism tested significantly better in a parallel run on the same segment — particularly for North American mobile numbers at VP level.
Cost per valid contact
| Tool | Email Coverage | End-to-End Valid | Phone Coverage | Est. Cost/Email | Cost/Valid Email |
|---|---|---|---|---|---|
| Apollo | 88.2% | 71.6% | ~14% verified | $0.02–0.04 | ~$0.03–0.06 |
| RocketReach | 82.1% | 65.2% | ~11% verified | $0.06–0.12 | ~$0.09–0.18 |
| People Data Labs | 82.4% raw / ~56% current-employer | ~45–56% | ~18% raw | $0.02–0.08 | ~$0.04–0.14 |
Apollo's credit pricing is cheaper per email than RocketReach's lookup model at most tiers. People Data Labs's range is wide because cost depends on field selection and contracted volume — at 50K+ records monthly, per-record cost drops substantially, which changes the calculus entirely.
When PDL actually makes sense
People Data Labs is not the right tool if you need a sales rep to click through profiles and pull contacts one at a time. It's an API that returns raw JSON — you query it programmatically, get back everything the platform has on a person, then you score, verify, and filter. There's no UI, no sequence builder, no credit model that maps to "I need 300 leads this month."
Where PDL wins: scale and breadth of signal. If you're enriching 50,000+ contacts and want to pull multiple data signals — current role, previous companies, skills, education, seniority — at a per-record cost that doesn't scale with feature count, PDL is the right layer. It also returns data that Apollo and RocketReach don't expose — job history depth, skills normalization, and education fields that are useful for segmentation and persona modeling.
The architecture decision is real: if you're building your own enrichment pipeline and want to control match strictness and verification logic, People Data Labs gives you that. If you want pre-verified results with a UI, use Apollo or Hunter.io.
What I actually use
For US SaaS outbound on VP+ contacts, Apollo handles primary email enrichment. I run a secondary pass through Hunter.io to catch the contacts Apollo missed on well-known corporate domains — Hunter.io's domain-level search fills a specific gap when you know the company but not the email pattern. Together they cover around 80% of the list with verified email.
For phone, Lusha is the only tool I've found worth running on North American SaaS VP contacts. The coverage isn't great anywhere, but it's less bad there than Apollo or RocketReach on direct dial specifically.
People Data Labs runs as the enrichment layer behind our product's own contact features — programmatic access to job history and skills at volume, not single-record lookups for outbound.
For Twitter/X and Facebook profile enrichment specifically, Ziwa has been faster than hitting PDL's API directly — particularly when starting from a social handle rather than a corporate email. RocketReach stays in the stack for targeted executive lookups at named accounts where I want a second data point on someone Apollo couldn't find. The higher per-lookup cost is acceptable when you're running 20–30 queries, not 500.
If I could only use one tool for cold outbound email enrichment at the scale I described — 500 US SaaS VP contacts — it would be Apollo, with ZeroBounce validation before any send. The bounce rates aren't good enough to skip that step.
Top comments (0)