The context
B2B prospecting and lead generation agency, France. High-ticket offer, long sales cycle, targeting founders and decision-makers.
They were already prospecting. The problem was not the absence of prospecting, it was the way it was done.
One person half-time, four hours a day, looking for prospects one by one, qualifying them one by one, building campaigns in a tool, tracking them, following up by hand. Tools that did not talk to each other. Considerable time invested for a result that depended entirely on human consistency.
The setup
This case covers a single LinkedIn account, their main one.
| Item | Detail |
|---|---|
| LinkedIn accounts equipped | 1 (founder's account) |
| Personas built and tested on this account | 17 |
| Length of the engagement | 3 months |
The 17 personas are not 17 contact lists. They are 17 distinct targetings, each with its target job titles, sectors, company sizes, buying signals, blacklist, and above all the profiles not to contact.
Example of a real persona from this account: founder or CEO of a lead generation agency, 5 to 300 employees, France, Switzerland, Luxembourg. Exclude: solo freelancers without a team, SEO or Ads agencies, "open to work" profiles, and salaried sales directors, who do not decide on the investment.
This level of precision is what separates a 10% reply rate from a 42% reply rate.
Results over 3 months
| Stage | Volume | Rate |
|---|---|---|
| Prospects sourced, qualified and contacted | 2,050 | 100% |
| Invitations accepted | 1,250 | 61% |
| Prospects who replied | 861 | 42% |
| Meetings booked | 62 | 3% |
| Contracts signed | 18 | 0.9% (30% of meetings) |
| Revenue signed | €36,000 | average deal €2,000 |
42% reply rate. LinkedIn prospecting done without support runs between 5 and 10%.
30% of meetings turn into a contract. The filtering happens before the calendar, not during the call.
The ramp-up, month by month
The first month produces no signature. That is normal, and it is even the sign that the system is being built correctly: you fill the calendar before you fill the order book.
| Month 1 | Month 2 | Month 3 | |
|---|---|---|---|
| Prospects contacted | 600 | 650 | 800 |
| Invitations accepted | 312 (52%) | 390 (60%) | 548 (68%) |
| Prospects who replied | 187 (31%) | 273 (42%) | 401 (50%) |
| Meetings booked | 18 | 20 | 24 |
| Contracts signed | 0 | 6 | 12 |
| Meeting to contract rate | 0% | 30% | 50% |
| Revenue signed | €0 | €12,000 | €24,000 |
The 30% conversion shown above is an average. In month 1 it is zero. In month 3, one meeting in two signs.
Month 1, calibration
Personas, messages, tone. Meetings get booked, sales cycles start.
18 meetings, no signature. Volume was not the problem, the conversation was. As soon as a prospect replied, the agency talked about its offer. Too fast, too early. The prospect accepted a call out of curiosity, and the call led nowhere.
This is what we call setting: what happens between the prospect's reply and the moment they open their calendar. Most companies have no method at this stage, they pitch.
Month 2, the first contracts land
Messages had been rewritten two or three times, we now knew what made each persona reply.
The conversation sequence was rebuilt from scratch: no more offer presentation in the first exchanges, but two or three framing questions that bring out the need, the budget and the timing. The number of meetings barely moves, 20 versus 18. Six of them sign.
Month 3, cruising speed
The pipeline built in month 1 matures at the same time as new prospects come in.
The acceptance rate went from 52 to 68%, the reply rate from 31 to 50%. 24 meetings, 12 contracts.
At every stage of the funnel, we gain 15 to 20% per month. That is the result of weekly work on a single point: where are we losing prospects, and how do we keep more of them all the way through.
The prospects who came on their own
Outbound did not work alone. In parallel, we built the content strategy for the LinkedIn accounts: regular posts, taking a stand on the personas' topics, presence in comments.
- The reply rate goes up. A prospect who receives a message from an active profile, one that publishes and that they have already seen in their feed, replies far more than to an empty profile.
- Trust is already there at the meeting. The call no longer starts with "what exactly do you do?". That is one of the reasons behind the 30% conversion rate.
- From the second month, prospects come in on their own. Without having been contacted. They saw the posts, they write first. Those prospects are not in the figures above: they come on top.
This is the point prospects underestimate the most. Prospecting opens the conversations, content is why people reply to you.
Time recovered
| Before | After | |
|---|---|---|
| Prospecting time | 4 hours a day (a dedicated half-time) | 15 minutes a day |
| What gets done in that time | Sourcing, qualification, campaign building, manual follow-ups | Approving the replies proposed by the agent |
A half-time position dedicated to prospecting costs between €1,500 and €2,000 a month in salary. That time is now reinvested in meetings and closing.
Return on investment
€36,000 in signed revenue on this single account in three months, for a running cost under €200 per month per account. In month 3, €24,000 signed for €199 invested: every euro returned 120.
The agency's revenue tripled.
What about the other accounts? This agency now runs three LinkedIn accounts. The figures above only cover the main account, the founder's, naturally the best performing. The two other accounts, carried by less exposed profiles, produce less. But they produce. Across all three accounts, revenue generated is 2.2 times the single account presented here.
The three reasons they switched
- The inconsistency had become untenable. Selling prospecting to clients while prospecting by hand themselves, with a half-time position tied up and tools that do not communicate. They needed a system that runs without immobilising someone.
- What was missing was not a tool. They had already tried several. What was missing was someone to build the personas, read the real replies every week and rewrite the messages until they convert. Seventeen personas do not build themselves in an afternoon.
- The maths left no doubt. A freelance sales rep bills between €700 and €1,000 a day. Here, it is a system that runs for under €200 per month per account, and a half-time position given back to the company.
The essentials
- B2B lead generation agency, a single LinkedIn account equipped, 17 personas, 3 months.
- 2,050 prospects contacted, 61% acceptance, 42% reply rate, 62 meetings, 18 contracts, €36,000 signed.
- Month 1 without a signature, month 3: one meeting in two signs. The trigger: framing questions instead of a pitch.
- LinkedIn content in parallel raises the reply rate and brings inbound prospects not counted here.
- From 4 hours a day to 15 minutes a day. The agency's revenue tripled.
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Frequently asked questions about this case study
Are these numbers verifiable?
Yes. They are the real data of the agency's main account, taken from the Formula. dashboard over three months. Nothing is extrapolated or rounded up. The agency's name is not published at its request.
Why no signature in month 1?
Because the calendar fills up before the order book. 18 meetings were booked, but the conversation pitched too early. Once the sequence was rebuilt around framing questions, 6 contracts in month 2 and 12 in month 3.
What do 17 personas mean?
17 distinct targetings, each with its job titles, sectors, company sizes, buying signals and profiles to exclude. That precision is what takes a reply rate from 10% to 42%.