From exhibitor directoryto lead radar.
This report is the odd one out: it tests the same method on a different data problem — sales data rather than engineering knowledge. 3,707 exhibitors become 35 solid leads in a single day, each with a hook and a source. You come from engineering? Then test report 01 is the more direct way in.
- Public sources, no customer data
- Every assessment with a source
- Reclassifications checked by a human
The same method in the quotation process is on Sheet 5 · Technical Distribution. Where your data sits is your decision — three deployment models are set out on Sheet 1.
IFAT Munich 2026, the entire exhibitor directory.
The world's leading trade fair for water and environmental technology. We take the complete directory as the data basis and build a lead radar for a clearly defined ideal customer.
Reduction by a factor of 105.
Seven stages, each with a checkable criterion. No stage throws anything away without it being traceable why — the intermediate sets are kept and can be reopened at any time.
Classic cold-call lists reach 5 to 10 per cent relevance. The difference is not the volume but that every deletion has a reason and can be undone.
Six stages, human and machine in turn.
The human defines the ideal customer and checks the borderline cases, the machine does the volume research. At two stages a human explicitly decides alongside.
This is what an A-lead looks like.
Anonymised example from the real lead radar. Every trigger has a source — otherwise it would just be another claim.
Southern Germany · Hall B1 · pumps and valves cluster
A new plant at 18 % growth plus product development with 3D printing means design and engineering are running at full stretch in parallel. An ideal moment for external engineering capacity as a peak buffer.
The derivation is a proposal, not a finding — it stands or falls with the four triggers above, and those are evidenced.
- All 35 A-leads at the same depth, sorted by priority
- The 149 excluded with the criterion they fell out on
- Intermediate sets for every stage, reopenable at any time
- Location and hall, for planning the route around the fair
- Contacts from public sources, no purchased data
- Timestamps per trigger: how current the hook is
- Reclassifications a human overrode, with the reason
- What the pipeline could not do and where it was unsure
Everything from public sources, nothing purchased. Every assessment traces back to the page it came from — and every deletion is reversible.
What the pipeline can do. And what it deliberately does not.
What the pipeline does
- data acquisition and structuring at scale
- multi-stage filtering along formal criteria
- trigger research from public sources
- prioritisation and conversation hooks as a draft
What sales does
- reclassification and refining the ideal customer
- contact qualification and personal research
- the sales conversation, needs analysis, handling objections
- negotiation, closing, relationship
All of it as a PDF.
With the pipeline architecture, the complete lead example and the impact analysis. You get the PDF straight after submitting.
Four more process chains, same method.
We build this engine on your target group.
This sales engine is an internal tool at Getze and an offering at the same time. On request we build it for your sales team on your own target group data.
Arrange a 30-minute call →