Sales demo
Prospect discovery from a described profile
Describe the customer you want in words and get candidates with the reasoning for each match.
The challenge
Building a prospect list means assembling filters that approximate an idea nobody wrote down, then hoping the approximation was right.
The scenario
A sales leader wants accounts resembling their three best customers, and can describe what those have in common far more easily than they can express it as filters.
What goes in
- Profile description
- The customer you are looking for, in plain language.
What you can ask
Illustrative prompts. Results depend on your own data and are not deterministic.
- “Find mid-market manufacturers who recently opened a second site.”
- “Why did this account qualify?”
- “Which of these look most like our best customers?”
How Clearception approaches it
How the work is structured. Each step shows what its output is grounded in.
Read the profile
AI-inferredTurn the description into explicit, checkable criteria.
Search sources
ObservedFind candidates matching those criteria.
Explain each match
AI-inferredAttach the signals that qualified each candidate.
What you get
The shape of what comes back — not a promised result.
Candidate list
AI-inferredAccounts with the matched criteria shown per account.
Why it matters
- The profile is visible
- A wrong profile shows up immediately rather than after a quarter of outreach.
- Less list-building
- Description replaces filter assembly.
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Want to try this with your own work?
Open Sales and bring your own data. No signup is needed to read these demos.