How CapitalBox filled its loan pipeline with automated B2B lead generation
CapitalBox filled its Lithuanian loan pipeline with 82 interested companies in 10 weeks, 4x its target, from 3,700 decision makers reached by email.
Written byVytas MikulėnasFounder, Lean Sales Systems- Published
- Updated
- Reading time
- 7 min read
TL;DR
- CapitalBox, a European fintech lender for small and medium-sized businesses, wanted more Lithuanian companies asking about business loans.
- In 10 weeks of automated email outreach, 3,700 decision makers were reached, 416 replied and 82 asked about a loan: 4x the target of 20.
- The best list was built from a public signal: companies that had received small state aid (de minimis), with a 7.6% interested rate.
On this page
CapitalBox is a European fintech lender that gives fast business loans to small and medium-sized companies. In Lithuania, its sales team wanted a steady flow of business owners asking about financing. In 10 weeks, automated lead generation reached 3,700 decision makers and brought 82 interested companies, 4x the target CapitalBox set.
| Client | Industry | Service | Market | Period |
|---|---|---|---|---|
| CapitalBox | Finance, business loans | Managed lead generation | Lithuania | May 2025 to July 2025 |
Key results
| Decision makers reached | Replies | Opportunities | Hours of manual work saved |
|---|---|---|---|
| 3,700 | 435 (416 email, 19 LinkedIn) | 82 | about 620 (estimate) |
Opportunities are replies tagged Interested in Reply.io, after removing clear mis-tags. Hours saved is an estimate; see the estimates section.
About the client
CapitalBox is a fintech lender founded in 2015 and based in Stockholm. It offers working capital loans and credit lines to small and medium-sized businesses in several European countries, with its own sales team in Vilnius.
The challenge
CapitalBox had clear loan products and its own sales team in Lithuania. It lacked a reliable way to start conversations with business owners who need financing right now.
| Challenge | Why it hurt |
|---|---|
| Crowded market | Banks, credit unions and more than 10 alternative lenders and lending platforms compete for the same Lithuanian companies. Owners get loan offers all the time. |
| Need is invisible from outside | A company needs a loan at a specific moment: fast growth, a drop in sales, a new project. You cannot see that moment on a website. |
| Senior, busy buyers | The decision is made by the CEO, owner or finance lead. They do not answer generic offers. |
| No decision-maker data | Company registers show companies, not the right person or a checked email address. |
| A clear bar for success | CapitalBox wanted 20 seriously interested companies from about 4,000 contacts before deciding to continue. |
Markets and focus
Lithuania was the only market. We split it into 4 lists, each built around a reason a company might need a loan now.
| Market | Who we reached | Companies | Volume | Result |
|---|---|---|---|---|
| Lithuania, growing companies | CEOs and owners | Companies whose revenue grew in 2024 | 1,850 emailed | 31 interested |
| Lithuania, companies with lower revenue | CEOs and owners | Companies whose revenue fell in 2024 | 1,268 emailed | 27 interested |
| Lithuania, state aid recipients | CEOs, or the general company inbox | Companies that received small state aid (de minimis) | 397 emailed | 30 interested |
| Lithuania, competitor followers | C-level people picked out by AI | Followers of a competing lender's LinkedIn page | 185 emailed, 76 LinkedIn requests | 6 interested |
The solution
We built 1 outreach system that found companies with a likely financing need, reached the decision maker and sent every reply to the CapitalBox country manager.
| Building block | What it did for CapitalBox | Why we used it | Tools |
|---|---|---|---|
| Lead research | We pulled Lithuanian companies by 2024 revenue change from public company data, and from the public state aid register. An AI research assistant read the job titles of a competitor's LinkedIn followers and kept only the about 800 senior people. | The need for a loan is invisible from outside, so we used public signals that point to it. | Public company data, LinkedIn |
| Email finder and verifier | Found work emails and checked each one exists before sending. Only 8 emails out of 3,700 could not be delivered. | Bad addresses send emails to spam and burn the sending domain. | Email verifier |
| Automated email and LinkedIn outreach | An automated outreach tool (a "sequencer") sent short emails and 1 follow-up in Lithuanian, signed by the CapitalBox country manager, and stopped when someone replied. 1 LinkedIn account ran a small test on competitor followers. New sending inboxes were used gently for 2 weeks first so email providers trusted them. | The team had no time to write to thousands of companies by hand, and the main CapitalBox domain stayed safe. | Reply.io |
| Replies to the sales team | CapitalBox chose not to connect its CRM (customer database) at the start. Every reply landed straight in the country manager's inbox, and we sent the full list of contacted and interested companies at the end. | The team could follow up with interested owners quickly. | Reply.io inbox |
What made the difference. The message named the reason for writing. The state aid list opened with the fact that the company had received small state aid, and the revenue lists named the 2024 growth or drop. The state aid list was the smallest, but 7.6% of the people reached asked about a loan, about 4x the rate of the revenue lists.
What changed
| Metric | Result | Tracked in |
|---|---|---|
| Companies and decision makers reached by email | 3,700 | Reply.io |
| LinkedIn connection requests | 76 (63 accepted) | Reply.io |
| Email delivery | 99.8% (8 bounces) | Reply.io |
| Replies | 435 (416 email, 19 LinkedIn) | Reply.io |
| Email reply rate | 11.2% overall, 15.3% on the best list | Reply.io |
| Opportunities | 82 replies tagged Interested (94 before removing mis-tags) | Reply.io inbox |
| Time to first interested replies | Within the first week after launch, May 2025 | Reply.io inbox |
| CapitalBox team time on prospecting | None; the team only answered replies | Campaign setup |
Many interested replies were concrete questions: the amount and term a company needed, the rates for a working capital loan, or whether CapitalBox also offers other types of financing. CapitalBox did not share how many loans it issued from these leads, so we do not count them here. LinkedIn replies are not in the tagged count.
Extra benefits
- 4x the target CapitalBox set for interested companies, in the first campaign.
- The main CapitalBox domain was never used for cold email, so its reputation stayed safe.
- A clear lesson on targeting: a public signal of need (state aid, a revenue change) beats a general list of companies.
- Clean lists of Lithuanian companies and decision makers that CapitalBox can reuse.
- Tested Lithuanian messages for each list, ready for the next round.
What this could be worth (estimates)
The numbers below are estimates, not results reported by CapitalBox.
Work the system did
| Item | Estimate |
|---|---|
| Value of outreach work done (activity value, not return) | about €16,700 |
| Hours of manual work saved | about 620 hours |
| Full-time months saved | about 4 months |
Projected deals within 12 months
| Scenario | Close rate | Projected deals |
|---|---|---|
| Pessimistic | 5% | 4 |
| Average | 10% | 8 |
| Optimistic | 15% | 12 |
Assumptions: 3,700 decision makers reached by email, €4.50 and 10 minutes of manual work per contact, 160 working hours a month, 82 opportunities, and 5% to 15% of opportunities closed within 12 months, typical for mid-market B2B. CapitalBox does not share deal sizes, so we do not estimate revenue.
What happened next
After the Lithuanian round, the local team did not have the capacity for a second round at the quality it wanted. CapitalBox renewed the cooperation and moved the next round to 2 other European markets.
Most companies treat this as a hiring problem
It is a system problem. A lender does not need more salespeople to find businesses that need financing. It needs a system that spots the signals of need and starts the conversation with the owner. Lean Sales Systems builds and runs that system. See more results in our case studies.
FAQ
How fast did the first interested companies reply?
Lists and messages were ready about 1 week after onboarding. After 2 weeks of inbox warm-up, the first campaign started in the second half of May 2025, and the first replies tagged Interested came within the first week. Most interested replies came in June.
How much time did the CapitalBox team spend?
The team answered onboarding questions, checked the lists for existing clients and approved the messages. Lean Sales Systems built the lists, wrote the messages and ran the campaigns. The country manager only answered replies and followed up with interested owners.
Who did the campaigns target?
CEOs and owners of Lithuanian small and medium-sized companies with a visible reason to need financing: fast growth or a drop in 2024 revenue, recent small state aid, or interest in a competing lender. For 1 list, emails went to the general company inbox.
