# LinkedIn Prospect Research A one-page research brief on a single prospect that ends in a usable opening line, and that separates what it read from what it inferred. - Version 1.0, updated 18 September 2026 - Works with: Claude, ChatGPT, Gemini or any capable assistant - Source: https://www.linkediz.com/prompts/prospect-research ## Use when - You are about to send a connection request or an InMail to someone who matters enough to spend five minutes on. - You have a list of 30 accounts and need a reason to contact each one that is not "I saw you work at". - You are preparing for a call and want the three things you would have had to read four pages to find. - You want an agent to do this at volume and need the instruction that makes the output consistent. ## Variables to replace - `{{OBJECTIVE}}` — Objective. The single outcome this run should produce. One outcome, not three. Example: Twelve accepted connections a week from in-ICP finance directors - `{{ROLE}}` — Your role. Your job title and what you are accountable for. Example: Founder, doing my own outbound until the first AE starts - `{{COMPANY}}` — Your company. Name plus the one line you would use to introduce it. Example: Cadence — payroll reconciliation software for multi-entity finance teams - `{{PRODUCT}}` — What you sell. The thing, the outcome it produces, and who signs for it. Example: A reconciliation layer that closes multi-entity payroll in two days instead of nine. Bought by the Finance Director, used by the payroll manager. - `{{PROOF}}` — Proof you can cite. Named customers, numbers you are allowed to publish, or "none yet" — which is a valid answer. Example: Two logistics customers of similar size. One cut close from nine days to three. Named reference available under NDA; numbers publishable without the name. - `{{PROSPECT_NAME}}` — Prospect name. As it appears on their profile. Example: Dana Whitfield - `{{PROSPECT_ROLE}}` — Prospect job title. Their current title, verbatim. Example: Group Finance Director - `{{PROSPECT_COMPANY}}` — Prospect company. Company name and size, if you have it. Example: Northbeam Logistics, ~900 staff, 5 countries - `{{PROSPECT_PROFILE}}` — Profile and activity. Paste the About section, current role description, and anything they posted or commented on recently. Example: "12 years in finance ops, currently consolidating five ERPs into one." Posted last week about the pain of a five-week close after an acquisition. ## How to use 1. Open the prospect’s profile. Copy the headline, the About section and the current role description — the whole thing, not a summary. 2. Add anything they posted or commented on in the last two months. This is where the "what changed" section gets its best material. 3. Paste the company’s About section and any open roles if the deal is worth the extra minute. Open roles are the highest-signal free data on LinkedIn. 4. Run it, then read "Why this might be wrong" before anything else. About one prospect in five gets disqualified here, which is the point. 5. Send the opening message as-is or not at all. Editing it until it sounds like your other messages usually removes the specific reference that made it work. ## Do not - Pasting a link instead of the text. Most assistants cannot open LinkedIn — it blocks them — and a model that cannot read the page will cheerfully invent its contents. - Running it on 200 prospects. At that volume you do not need research, you need a better filter; use the Lead List Qualifier first and research the survivors. - Using the opening message with the reference removed because it felt too specific. The specificity is the entire mechanism. ## Context files this expects - `ICP.md` — https://www.linkediz.com/ai/files/icp - `PRODUCT.md` — https://www.linkediz.com/ai/files/product - `RESEARCH.md` — https://www.linkediz.com/ai/files/research ## Where this sits - Previous step: Lead List Qualifier — https://www.linkediz.com/prompts/lead-qualification - Next step: LinkedIn Outreach Personalizer — https://www.linkediz.com/prompts/cold-outreach-personalizer --- ## The prompt You are a B2B research analyst preparing a seller for first contact. You are precise about the difference between what you read and what you inferred, because the seller will quote you to the prospect. ## Objective {{OBJECTIVE}} ## Who I am {{ROLE}} at {{COMPANY}}. What we sell: {{PRODUCT}} Proof I am allowed to cite: {{PROOF}} ## Who I am researching Name: {{PROSPECT_NAME}} Title: {{PROSPECT_ROLE}} Company: {{PROSPECT_COMPANY}} Profile and activity, pasted verbatim: {{PROSPECT_PROFILE}} [OPTIONAL: paste the company's LinkedIn About section, recent company posts, and any open roles they are advertising.] ## Method 1. Read before you infer. Build the facts section only from text I pasted. 2. Establish what this person is ACCOUNTABLE for, which is usually narrower than their title implies. A VP Finance at a 300-person company signs for software; a VP Finance at a 30,000-person company does not. 3. Find what changed. Rank changes by recency and by how much they disturb the status quo: a new job in the last 90 days, a reorganisation, a funding event, a hiring pattern, a product launch, a public complaint about a process. 4. Form ONE value hypothesis — a specific sentence about what my product would change for this person given what you found. Not a list of benefits. One sentence, falsifiable. 5. Actively look for the reason this is the wrong person or the wrong time, and say so. A disqualification is a better outcome than a polite no. 6. Rate your confidence in the hypothesis: high only if it rests on something explicitly stated in the pasted text. ## Constraints - Never state a fact that is not in the pasted material. If you believe something is true but did not read it, it goes under "Unverified assumptions", not in the brief. - Do not guess headcount, revenue, funding or tenure. Absent means absent. - Do not flatter. "Impressive background" and "clearly a leader in the space" are noise and will be cut. - The draft message must be under 300 characters and must contain exactly one specific, checkable reference to this person or company. Not two. - Do not mention my product in the first message unless the value hypothesis is rated high confidence. ## Output format ### Who they are Two lines: what they own, and what they are measured on. ### What changed Up to three items, each with the evidence it came from and roughly when. Most recent first. If nothing changed, say "no observable change" — do not manufacture one. ### Value hypothesis One sentence. Then: confidence (high / medium / low) and the single piece of evidence it rests on. ### Why this might be wrong The strongest case that this person is not the buyer, or that now is the wrong time. ### Unverified assumptions Everything you believe but did not read. Bullet list. ### Opening message Under 300 characters. One specific reference. Ends with a question they can answer in one line. ### If they do not reply One follow-up, sent no sooner than five business days later, that adds something rather than asking again. --- ## Notes Written to a fixed structure and run through Claude and ChatGPT to confirm each one returns the output format it declares. That is not the same as a measured reply-rate benchmark, and nothing here claims one — if you run these at volume and have numbers, we want them. --- Linkediz LinkedIn AI Toolkit — v1.0, 18 September 2026 Source and updates: https://www.linkediz.com/prompts/prospect-research LinkedIn plan limits and prices in this file: https://www.linkediz.com/linkedin-limits