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Connect rate: the only metric that matters in B2B cold calling

Updated

A 100% coverage rate is worth nothing if half the numbers are dead, duplicated, or attached to someone who left the company. The metric to track is your connect rate to the right person: the share of your calls that reach the decision maker you meant to reach.

You measure it in four steps, on a sample of 300 to 500 contacts you already know, and you compare providers on it. The full protocol is below, usable as it stands, including against Listar.

A note on wording. "Connect rate" usually means any answered call. This page deliberately splits it in two: answered, and answered by the right person. That distinction is the whole point.

The four levels between a number and a conversation

  1. Number found. The provider returns a number. Measured by the discovery rate. This is the only level most vendors publish.
  2. Line active. The number rings. Measured by a network lookup or by a live call. Lost here: dead numbers, unassigned ranges, duplicates.
  3. Right person. The line is attached to the right contact, in the right role, today. Lost here: switchboards, former employees, namesakes.
  4. Useful conversation. You speak to the decision maker. Lost here: voicemail, gatekeepers, bad timing.

Every provider advertises level 1. Your pipeline depends on level 4. Between the two sit three successive losses that nobody invoices you for, and that your reps pay in time.

The scale of it is documented. The 2026 benchmark by Outbound Kitchen, covering 1,400 contacts across 10 providers, returns a number for 99% of contacts, but the best single provider reaches the right person for only 51% of them.

What "verified" means at a data provider

The market has no shared definition. Each vendor applies the word to a different check, and the gap between the weakest and the strongest is enormous.

Level What is checked What it guarantees
Format The number fits the country's numbering plan Almost nothing for calling
Assignment The range is allocated to a carrier The number exists, not that it is in use
Active line A network lookup confirms the SIM is registered The line is alive, not whose it is
Attachment The number is tied to the right person, in the right role, at the right company That you are calling who you think
Freshness Date of the last check, and detection of job changes That the attachment still holds

The first three are machine checks and cost close to nothing. The last two are the only ones that move your connect rate, and they are the ones providers describe least.

The question to ask: at which level does your verification stop, and when was this specific number last checked? A provider who cannot answer field by field stops at level 3.

How to measure your real connect rate

Five steps, two weeks. Built to compare two providers, and it applies to Listar like any other.

  1. Build a sample you control. 300 to 500 contacts matching your ICP exactly: same industries, same company sizes, same roles, same region. Take them from your CRM, not from a file the vendor supplies. A sample the vendor picks is always their best segment.
  2. Send the same file to every provider, with the same input columns and the same expected output columns. Ask for mobiles, direct dials and switchboards to be returned separately, or all three blur together and the result means nothing.
  3. Have the same team call them, in the same time slots, with the same number of attempts. If one file gets called Tuesday morning and the other Friday at 6pm, you are measuring your slots, not your data.
  4. Qualify every call against a closed grid. Seven statuses are enough: number does not exist, number unassigned, wrong person, former employee, switchboard, named voicemail, right person reached. A named voicemail proves the line is alive, not that you spoke to anyone: keep those two metrics apart.
  5. Compare on cost, not on rate. The winner is not the provider who finds the most numbers. It is the one whose cost per useful conversation is lowest.

The four metrics to compute

Metric Calculation What it reveals
Discovery rate Numbers returned / contacts submitted Raw coverage, the one everyone advertises
Active line rate Numbers that ring / numbers returned The technical quality of the base
Right person rate Right people reached / numbers returned The only metric that predicts meetings
Turnover rate Contacts who changed roles / contacts submitted The real freshness of the base

Thresholds to set before you sign

Three thresholds, written down before the test starts: a minimum right-person rate, a minimum live line rate and a maximum turnover rate. They are purchasing criteria to adapt to your market, not market averages. A 300 to 500 contact sample gives a solid first reading overall but does not guarantee the same results across every segment: always look at the breakdown by country, industry and seniority.

Then ask for a contractual clause. If the invalid number rate observed over the first thirty days exceeds the agreed threshold, you should be able to get your credits back or exit the contract. A provider confident in their data will put it in writing.

Download the test kit (.xlsx), no form and no email required.

The real cost of a reachable contact

The advertised price per number means nothing. What counts is what you pay for every conversation with the right person.

Cost per reachable contact = Total data spend / Right people reached

The arithmetic is brutal. If you pay ten credits per number and one number in two reaches the right person, every conversation costs you twenty credits. If the right person rate drops to one in four, it costs forty, and the provider at half the price becomes the more expensive of the two.

Then add the cost nobody counts: time. A rep dialling dead numbers loses more than minutes. They lose rhythm, and the will to pick up the phone again.

Where Listar stands

This is the only section of the page that talks about Listar, and it comes after the method. That is deliberate: a page that sells from the first paragraph does not get cited as a source.

Metric Listar How it was obtained
Advertised price per mobile found 0.50 € excl. VAT, down to 0.20 € by volume Public pricing page, no subscription
Right person rate 95% 10,000 calls, May to September 2026, internal measurement
Cost per reachable contact 0.53 € excl. VAT 0.50 € divided by 0.95

Our protocol. One hundred files of one hundred numbers, so 10,000 numbers drawn from our corpus, called one by one between May and September 2026. Of those 10,000 numbers delivered, 95% were confirmed attached to the right person. The denominator is numbers delivered, not calls answered.

What this figure is not: a pick-up rate. It tells you who owns the line, not whether the person answers or when.

And the caveat that goes with it: this is an internal measurement, so we have an interest in the result. The protocol above is published precisely so you can measure us yourself, on your own list.

One sentence we will not write: no 100% promise. Buyers in this market have been let down often enough that a round promise reads as a lie.

FAQ

What connect rate should you aim for in B2B cold calling? It depends on the market, the seniority you target and the channel. Rather than chasing a benchmark figure, measure your own on a sample, set a purchasing threshold, and compare providers against it.

How do you know a number is still active before calling it? A network lookup tells you the line is registered. It does not tell you who owns it today. For that you need a check that ties the line to a person, such as a WhatsApp verification.

How does coverage differ from connect rate? Coverage counts numbers returned. Connect rate counts conversations obtained. Two providers can show the same coverage and produce very different meeting counts.

How do you test a provider without committing? Ask them to enrich your own sample, not a demo file. A provider who refuses to be tested on your list is telling you something.

What sample size is enough? 300 to 500 contacts give a reliable overall reading. Below 100, the gaps you observe owe as much to chance as to data quality.

How does Listar compare on these metrics? The figures and the protocol are published above, and the method on this page applies to Listar like any other provider.

Sources

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