What is the difference between basic input and rich input?

Basic input means a provider only receives name and company context. Rich input means the provider also receives a LinkedIn profile, which usually improves match rates.

How is this benchmark scored?

On truth-backed datasets, the primary score is exact-match rate: the share of contacts where the returned email exactly matches the known work email.

OpenFunnel BenchWork Email Enrichment

Work email enrichment benchmark for GTM Agents Or Engineers

Evaluate email enrichment providers the way a GTM engineer or agent actually buys them: can this provider return the right work email, how often is it wrong, what does a correct result cost, and how fast does it respond in production workflows.

OpenFunnel Work Email Benchmark

Compare exact-match rate, wrong-email rate, cost per exact match, and tail latency.

Inputs: name + company

FullEnrich

Exact-match: 82.79%
Precision: 87.46%
Wrong-email: 11.87%
Cost / exact: $0.07

Inputs: name + company + LinkedIn

FullEnrich

Exact-match: 84.33%
Precision: 87.14%
Wrong-email: 12.44%
Cost / exact: $0.07

`name + company` means first name, last name, and company context. `name + company + LinkedIn` adds a LinkedIn profile input.

Inputs: name + company

Name and company input work email enrichment benchmark leaderboard
Rank	Provider	Exact-match rate	Precision on returned emails	Wrong-email rate	Any-email coverage	Cost per exact match	P95 latency
1	FullEnrich 337 of 342 contacts scored	82.79%	87.46%	11.87%	94.66%	$0.07	0ms

Inputs: name + company + LinkedIn

Name, company, and LinkedIn input work email enrichment benchmark leaderboard
Rank	Provider	Exact-match rate	Precision on returned emails	Wrong-email rate	Any-email coverage	Cost per exact match	P95 latency
1	FullEnrich 217 of 217 contacts scored	84.33%	87.14%	12.44%	96.77%	$0.07	0ms
2	Fiber Single 217 of 217 contacts scored	71.43%	76.35%	22.12%	93.55%	$0.05	14542ms
3	ContactOut 217 of 217 contacts scored	12.90%	70.00%	5.53%	18.43%	N/A	0ms

Methodology

Build the benchmark from real B2B users who are already associated with active customer or workspace usage, rather than from synthetic contacts or guessed email patterns.
Use only contacts where we have a trusted source of work-email truth, then compare provider output against that known work email.
Keep the benchmark public while keeping the underlying identities private: raw emails and person-level evidence are not exposed in the site output.
Give each provider the same inputs within each input set so the comparison stays fair.
Run each provider once per contact and store the returned work email candidate.
Score exact matches against known work emails, then track wrong-email rate, any-email coverage, cost, and latency.
Estimate cost from the cheapest public monthly plan and documented work-email credit usage where public pricing exists.

Metrics

Exact-match rate: the share of contacts where the provider returned the correct work email.
Precision on returned emails: when a provider does return something, how often it is right.
Wrong-email rate: the share of contacts where the provider returned the wrong work email.
Any-email coverage: the share of contacts where the provider returned any work email candidate.
Cost per exact match: total estimated spend divided by exact matches.
P95 latency: how slow the tail of provider responses gets in real workflows.

Current public cost assumptions use the cheapest monthly plans for FullEnrich and Fiber. ContactOut cost remains unavailable until public API pricing is published.