B2B sales/1 to 2 weeks of development
Automated B2B lead generation
Prospecting took 15 to 30 minutes per lead. We built a pipeline that pulls companies from public registries, qualifies them on their actual filed accounts, and delivers over a hundred personalised leads in a spreadsheet.
- qualified leads per run
- 100+qualified leads per run
- of manual work saved per lead
- 15-30 minof manual work saved per lead
- from empty list to finished spreadsheet
- One clickfrom empty list to finished spreadsheet
Where the time went
Prospecting is a numbers game, and the numbers take time. For every cold email the client had to look the company up, check whether it was solvent, find an address somebody actually reads, and write something personal enough that the recipient would not delete it on sight. Fifteen to thirty minutes per lead.
The target was 20 to 30 emails a week. That is most of a working day disappearing into research before the first email goes out. This kind of work is also the first thing dropped when the week gets busy, so prospecting stops exactly when it is needed most.
What we built
We built a pipeline that does the whole groundwork on one command. It pulls companies from public registries, qualifies them on their filed accounts, finds contact details and drafts an email suited to the industry. Out comes a spreadsheet with over a hundred leads ready to read through.
The client keeps control where it matters. The system does the research and proposes the wording, a person reads it over and sends.
- 01
PullsThe public company registry
Companies filtered on industry code, municipality and company type, so the list is relevant from the first row.
- 02
QualifiesFiled accounts
Revenue, profit and equity are pulled in. Bankruptcies, liquidations and companies under the threshold drop out.
- 03
EnrichesThe company's own website
The domain is inferred and verified against the content, the contact address is taken from the page, and the lead is scored from 1 to 10.
- 04
DeliversGoogle Sheets
Each lead gets an email suited to its industry, and everything lands in the spreadsheet without overwriting the statuses you have set.
Out comes
| Company | Industry | Revenue (m) | Score | Status |
|---|---|---|---|---|
| Company name hidden | Audit | 31.4 | 10/10 | Sent |
| Company name hidden | Accounting | 18.2 | 9/10 | Replied |
| Company name hidden | Construction | 11.4 | 8/10 | Sent |
| Company name hidden | Transport | 9.8 | 6/10 | Queued |
How it works
Pulls the right audience
Companies are filtered on industry code, municipality and company type, so the list is relevant from the first row.
Qualifies on real figures
Revenue, profit and equity are pulled in. Bankruptcies, companies in liquidation and anything under the threshold drop out.
Finds a real address
The domain is inferred and verified against the site itself, and the contact address is taken from the page rather than guessed.
Writes the first draft
Each lead gets an email suited to its industry, and everything lands in the spreadsheet without overwriting the statuses you have set.
What they were left with
The groundwork that used to take 15 to 30 minutes per lead now takes one command. The client gets over a hundred qualified, personalised leads per run, and spends their time on the conversations instead of on the research.
Prospecting stopped being the thing that gets dropped when the week is busy.
Technology in this project
- Public company registries
- Filed accounts
- Automated enrichment
- Google Sheets
- Scheduled runs
The same recipe, other sectors
The same pipeline works for anyone selling to other businesses. What changes is the filter at the top and the wording at the end.
- Accounting and audit firms looking for companies of a given size in their own region.
- Suppliers who only want companies above a revenue threshold.
- Recruiters mapping companies in a particular industry.
- Anyone whose sales start with somebody looking up companies one at a time.