Turning a prospect's public filings and news into buying signals
Good outreach and good discovery both depend on knowing what's actually happening inside the account — its priorities, pressures, and initiatives — but reading an earnings call transcript, a press release, and a stack of job posts can eat an hour before you've written a word. AI is strong at compressing that public material into signals and talking points, as long as you feed it only public text and verify every quote before repeating it.
You are a B2B sales research analyst. Below is public material about a prospect company. Extract sales-relevant signals from it — nothing more. Company: {{prospect_company}} What I sell / the problem area I help with: {{my_solution_area}} Public material (earnings call excerpt, press release, 10-K section, job posts, blog): {{public_materials}} Produce: 1. Top 3 business priorities you can see in the text, each with the exact quoted line that supports it. 2. Likely pains in my solution area that connect to those priorities — labeled as hypotheses to test, not facts. 3. Three specific talking points I could open a conversation with. 4. Three discovery questions tailored to what you found. Hard rules: - Use ONLY the pasted text. If a priority isn't supported by a direct quote, don't list it. - Never infer revenue, headcount, budget, or private plans that aren't stated. Where something isn't in the text, write "not stated." - Do not paraphrase a quote into something the source didn't say. Mark anything I should double-check with "[VERIFY]".
Fill in your details and the prompt updates live — then copy.
Priorities (with support): 1. Scaling the revenue org fast — "we're investing heavily in go-to-market headcount this year" (Q2 call). Five open RevOps/AE roles support this. 2. Forecasting discipline — "the board is focused on predictability of the pipeline" (Q2 call). 3. International expansion — "not stated" beyond a press-release mention of an EU office; treat as unconfirmed. [VERIFY] Likely pains (hypotheses): rapid hiring often degrades CRM data quality and forecast reliability — test whether that's happening here. Talking point: "Boards asking for pipeline predictability usually surface a data-hygiene problem first — is that on your radar as you scale AE headcount?"
The full workflow
- Collect only genuinely public material — investor pages, press, job boards, the company blog.
- Paste the full text and run the prompt; don't ask it to "look up" the company, which invites invented facts.
- Verify every quote and figure against the original source and resolve each [VERIFY] flag before using it.
- Turn the strongest signal into your outreach hook or your first discovery question.
Watch out for
Feed the model only public information. Never paste your own confidential competitive intel, a current customer's data, or internal deal notes into a consumer tool as 'context' for research.
AI misquotes and fabricates, especially earnings figures and dates. Repeating a made-up 'I saw your Q3 revenue was up 40%' to a prospect destroys credibility instantly — quote nothing you haven't checked against the source.
Where this comes from
Every use case on this site is grounded in real reports from working sales reps — not invented by us.