| name | b2b-lead-qualification |
| description | Qualifies and scores B2B prospects against a supplied ideal customer profile. Use when the user provides a lead list, company records, prospect data, or qualification criteria and wants prioritization, fit analysis, or disqualification reasons. |
| license | MIT |
| metadata | {"author":"ProfileSpider","version":"1.0","category":"qualification","source":"https://profilespider.com/resources/b2b-lead-qualification"} |
B2B Lead Qualification
Purpose
Score and classify B2B prospects against a defined ideal customer profile, with reasoning and a recommended next action.
When to use this skill
- Qualifying exported prospect lists before outreach
- Prioritizing accounts when you have more leads than capacity
- Separating high-fit and low-fit companies
- Documenting why a prospect matches an ICP
When not to use this skill
- You have no defined ICP or qualification criteria yet
- You need verified contact details rather than fit scoring
- The dataset has no company or firmographic fields to score against
Required inputs
- An ICP definition
- A prospect or company dataset
- Qualification criteria
Optional inputs
- Exclusion criteria
- Weighted scoring rules
- Target locations
- Company size range
- Required technologies or industries
Rules
- Use only information present in the supplied dataset or explicitly provided by the user.
- Do not invent missing company, contact, revenue, employee, technology, or location information.
- Clearly distinguish known facts from assumptions.
- Flag missing information that materially affects the score.
- Apply the same scoring framework consistently to every prospect.
Process
- Parse the ideal customer profile.
- Extract positive qualification criteria.
- Extract disqualifying criteria.
- Evaluate each prospect against both sets.
- Assign a score from 0 to 100.
- Explain the score using available evidence.
- Recommend the next action.
Output format
Return one record per prospect with the following fields:
- fit_score
- fit_level
- qualification_reason
- supporting_evidence
- missing_information
- recommended_next_action
Validation
- Confirm every score is supported by evidence from the input.
- Confirm missing fields are listed rather than guessed.
- Confirm the same criteria were applied to every record.
Limitations
- Scores reflect fit, not intent or buying readiness.
- A high score is not a guarantee of a sale; verify before investing heavily.
