Campaign Results

What this PDF is

This PDF is four real B2B outbound campaigns, with the people reached, the reply count and what the client did with the replies next to each one. No pooling, no blended line across accounts that sell nothing alike. Four campaigns, four products, four markets, each one named by what the client sells and where they sell it.

Every number comes straight out of the sending accounts, read on 20 September 2026. Two of the four campaigns are strong. One sits closer to average. One turned into signed placement contracts rather than a reply rate worth quoting on its own, which is a reminder that a reply rate is not the only outcome worth measuring.

Almost every rate divides replies by people reached. People reached counts each person once, however many follow-ups they received, so it sits well below emails sent. Divide by emails sent instead and the denominator fills up with follow-ups to people already counted, which drags every rate down and says less about how the list answered. Ask any agency quoting you a reply rate which of the two it used.

One campaign is the exception, and it is the strongest one in the file. It ran on a second sending account whose reporting shows mail delivered rather than people reached, so its 24.2% divides replies by delivered mail. We publish the figure that account reports and name the denominator every time it appears, rather than inventing a people-reached number that nobody measured.

Client names stay out, with one exception. Maxima, Lithuania's largest retailer, appears by name because it is the client's customer, not the client itself, and the trial is a deal the client is comfortable naming. The other three are described by what they sell and where, never by who they are, because the numbers sit inside paying clients' accounts.

The layout is the same for each campaign: who the client sells to, what was sent, what came back, and what happened after. You can read the four in ten minutes or use one as a model for a campaign of your own.

The four campaigns

The strongest campaign in the file went out for a Lithuanian consultancy selling R&D funding, state-backed loans and AI project support. 1,855 emails. 425 people wrote back. 297 of them said yes. The 24.2% reply rate divides those 425 replies by the 1,756 emails that were delivered, which is 1,855 sent less 99 bounced, and 69.8% of the replies came back marked a lead worth a conversation. Close to one in four of the people we wrote to replied, and better than two in three of those replies were a lead worth a conversation.

A separate run of eight campaigns for the same client reached 6,924 people and got 341 replies, a 4.9% reply rate on people reached. The client marked 202 of those replies as worth a conversation, so 59% of everyone who wrote back asked to talk. The strongest campaign of that run pulled 63 replies from 497 people reached, one person in eight, and 54 of those 63 replies came back marked a lead, better than four in five. On the largest send in the same run, 3,147 emails, eleven bounced, 0.35%. That run does not contain the campaign above, so the two are separate sets rather than one account total.

A Polish HR company opening a Lithuanian arm paid under EUR 10,000 for the work. Maxima, with roughly 20,000 staff, took a trial. Five workers went in first. Two further warehouse contracts followed, and seven more are in negotiation. No reply rate on this one carries the story; the placements and the contracts do.

A Polish precast and facade manufacturer selling into Finland, Sweden and the Baltics reached 6,182 people across the full run, for 66 replies and 13 positive replies. Its best angle, aimed at precast manufacturers who buy the same elements for jobs they cannot pour themselves, reached 718 people for 20 replies, a 2.8% rate. Seven of those 20 replies were positive, better than a third of that campaign against 20% across the run.

Our own staffing run into Poland's blue collar market, July 2026: 337 people reached, 24 replies, a 7.1% rate, and 6 of them marked positive, a quarter of the replies. The staffing run around it covers fifteen campaigns, 12,812 emails to 8,659 people for 96 replies, so the Polish blue collar list answered at more than six times the rate of the run it sits in. Narrowing the list did that, not the copy.

The totals we can read end to end

The four cases sit inside a larger operation. Since the first campaign went out in April 2026 the reporting view we read end to end has sent 86,642 emails, reached 48,985 people, taken 844 replies and logged 264 positive replies, across 59 campaigns and 10 accounts, into roughly 17 countries. The country count comes from how the campaigns were named, so read it as about seventeen rather than exactly seventeen.

Those totals cover that one reporting view and nothing else. The 1,855-email campaign above ran on a second sending account outside it, so none of its 425 replies or 297 positive replies is counted in them. Read the totals as what that view holds rather than as everything we have ever sent.

They are counts, with no rate attached and no client named. People reached counts each campaign's own list, so a company written to on two campaigns for the same client appears on both counts. We publish no blended rate off these totals either: one number covering ten companies that sell different things into different markets would describe none of them.

The point of the total is what the machine has actually done. Three of the ten accounts appear in the PDF by what they sell and where they sell it. One of the ten is our own, which is where the staffing campaign in the PDF comes from.

What reply and positive reply mean

A reply is any answer the recipient sends back, interested or not. A positive reply is one the client marked, inside the sending tool, as worth a conversation. Neither number is a booked meeting or a signed deal; the PDF says that on the page where each metric first appears.

The gap between the two numbers is the real filter. The strongest campaign took 425 replies and 297 were positive, better than two in three. The run of eight campaigns for the same client took 341 replies and 202 were positive, close to six in ten. The precast run took 66 replies and 13 were positive, closer to one in five. That gap says more about how well the offer fits the list than the reply rate alone does, and it is the number worth watching before the headline rate.

People reached is the third definition and the one most often quoted loosely. It counts the people who received at least one email from the campaign. Follow-ups to the same person add nothing to it, which is why a rate on that basis is both higher and more meaningful than the same figure divided by emails sent.

Mail delivered is the fourth, and it carries one campaign in the PDF. It counts the emails a receiving server accepted, that is emails sent less bounces. The 24.2% on the strongest campaign is measured against it, because the account behind that campaign reports no people-reached count. Wherever that rate appears, the denominator appears with it.

Why four campaigns instead of one benchmark

Pooling accounts that sell different things into one benchmark line flattens the number that would actually tell you something: what happened when this offer met this market. A 20,000-employee retailer piloting five warehouse placements is not the same event as a consultancy replying to a state-funding pitch, and averaging them together erases both. This PDF keeps the four separate, in full, with the market and the offer named next to each result.

Read it as four data points rather than four stand-ins for a category. What moves a reply rate is the market, the offer and the list, in that order, and the PDF says which of the three did the work in each of the four. The precast manufacturer's narrow angle beat its own full-run rate by naming a buyer already active in the target market; the Lithuanian consultancy's best campaign did the same with a sharper funding angle rather than a bigger list.

None of that transfers directly to your market or your offer. What does transfer is the method: pick the narrowest angle that still has volume behind it, and measure it against the same campaign's own full-run number rather than against someone else's average.

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