From 79 rows of data to five
named prospects. In one day.
A real case from mechanical engineering, anonymised: a supplier of fluid connections in the Nordics market. No invented customer, every number from their own data.
Open the CRM, scroll the list, guess who to call, google, find a name on LinkedIn, email from scratch.
One page. Three existing accounts with a reason, five prospects with evidence, timing and an opening question.
- 09:00
Step 1 — understand the base
79 order rows become 62 real companies (one appeared five times, others twice). EUR 3.84M of existing revenue becomes visible per customer, six customers carry 80 percent of it. Against an addressable potential of EUR 293.9M that is 1.31 percent. The concentration is not the problem, it is the symptom.
Along the way: twelve data-quality findings, each with a source — one company dissolved, one sold, one with a 45 percent headcount cut, flagged as risk instead of growth.
- 11:00
Step 2 — find & qualify
The fingerprint of the best customers becomes the search pattern. Five companies fall out, none previously in the file. Before the first call, boostpilot.ai checks each against its own catalogue: one of the five sells exactly what the customer sells, worth knowing before dialling. For one company a window is dated and open, for another it honestly cannot be derived. And that is exactly what it says.
- 12:00
Step 3 — walk in prepared
Two machines are taken apart from the manufacturer's own datasheets, around 400 fluid connection points, no named competitor in the field. The rep knows where a connection has to sit before walking into the room, and gets an action plan per account with the opening question already written.
What changed between
this morning and tonight.
A day like this, on your data.
A customer list is enough. In 30 minutes we play through the start of this day with your numbers.
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