Build · Create · Analysis & Finance
Scored BD partner pipeline with a warm-intro focus set
You get an exhaustive, consistently structured pipeline of candidate BD partners for your space, scored and narrowed to a focus set with warm-intro targets flagged.
You receive: A structured JSON pipeline: one row per candidate partner with company, partner type, contact, size, relevance, ease of use, and a priority score, plus a focus flag and a warm-intro flag per row.
Part of Distribution, Grow Partnerships
What you receive
The shape of your delivered file. Your result is generated for your inputs.
Your deliverable is a structured document carrying these fields:
- Company
- Contact
- Ease Of Use
- Focus
- Partner Type
- Partners
- Priority Score
- Relevance
- Size
- Warm Intro Target
Some fields carry set values, drawn from:
company, partnerType, contact, size, relevance, easeOfUse
Opens soon
STUD opens runs for everyone soon, on every play at once.
Scope of the check
What's verified: STUD verifies the structural shell of the pipeline: the row count meets the buyer's floor, every row carries the full O'Donnell column set with well-typed values, partner types stay inside the buyer's declared taxonomy, scores sit on one declared scale, companies are not double-counted, the focus set is narrowed to the buyer's band, and warm-intro flags are internally consistent with the focus set. STUD does NOT verify that the listed companies exist, that contacts are current or reachable, that size/relevance/ease assessments are accurate, or that the priority scoring judgment is wise (the source itself calls the score 'subjective'). The source's '50 potential partners, maybe 100' is a practitioner rule of thumb, not a law, and the same is true of the 10-20 focus range; both are exposed as buyer-adjustable params. The 1-to-N score scale and the boolean flag mechanics are this contract's operationalization: the book names the columns and the warm-intro step but prescribes no scale and no flag format. companyDescription and space are context for the operator, not machine-checked. no_duplicate_companies is an integrity guard on the exhaustive count, not a claim the book states verbatim.
Get early access to STUD the day it goes live.