Define fit in writing
We build the ideal-customer profile from your closed-won history and your sales team's instincts, then write it down as criteria a machine can apply.
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Pattern P04 · engagement pattern
Thousands of contacts, and a sales team that does not trust any of them.
The problem
Buying volume is easy and mostly worthless. The work is in defining fit, then filtering hard enough that the list gets much smaller and much more useful — which feels like getting less for your money until the first month of calls.
The second half of the problem is delivery. Data that lands in a spreadsheet is data that does not get used; it has to arrive in the tool the team already works in, at the stage it belongs.
The approach
In order: each step informs the next.
We build the ideal-customer profile from your closed-won history and your sales team's instincts, then write it down as criteria a machine can apply.
Contacts gathered against that profile and verified before delivery, because an unverified list damages the sending reputation covered in P03.
Matching on domain and normalised company name rather than exact string equality, which is why the same account keeps appearing three times.
Enriched records pushed to the right stage with their source attached, so the team can see why a contact is in front of them.
The outcome
A written, testable definition of a good-fit account
Verified contacts, deduplicated against what you already hold
Records in your CRM rather than a spreadsheet
Provenance on every contact, so the team can trust it
Deliberately no percentages. What a change is worth depends on your volumes and costs; we work that out with you against your own numbers.
Practices involved
Also
Tell us how this shows up in your business. The first conversation is free, and we will say so if it is not worth fixing.