Signals
Research and intelligence
Read the whole account as a set of signals. You are not gathering facts to recite. You are gathering evidence to reason from.
Enterprise sellers prepare, and preparation starts with intelligence. This is where AI earns its place fastest, because it will read more, faster, than you ever could. Your job is not to read less. It is to point a tireless research analyst at the right sources and ask it the right questions.
When Meridian pointed its teammate at Coastline Mutual, the useful signal wasn’t any single fact. It was the overlap: a new Chief Customer Officer, active hiring for data engineers, and “fragmented member data” mentioned on the results call. One of those is noise. Together they are a pattern.
- Read and structure large volumes of public information
- Extract signals from noise
- Summarise into a usable profile
- Flag what is uncertain or out of date
- Choose the account and the sources
- Judge what matters commercially
- Verify anything you will act on
- Decide what the intelligence means
Where to look
Direct your teammate across the full public estate of an account. No single source tells the story. The signal is usually in the overlap.
| Source | What it reveals |
|---|---|
| Company website & product pages | How they describe themselves and their priorities |
| LinkedIn (company and people) | Structure, hiring, who is new, what leaders post |
| ZoomInfo and Apollo | Org data, contacts, technologies, intent signals |
| Annual reports and investor presentations | Stated strategy, in their own words |
| Public financial results and earnings calls | Pressure, priorities, what leadership is measured on |
| Executive interviews and news | Priorities, language, recent change |
| Technology stack and partner ecosystem | What they run, who they work with, where you fit |
Ask specifically for the signals that matter in enterprise selling, not a generic summary. A good intelligence pass surfaces trigger events, buying signals, strategic initiatives, risks, competitive threats and probable business challenges. The next stage turns these into hypotheses, so gather them cleanly here.
Curiosity is a discipline, not a mood. The best researchers keep asking “and what would that mean?” one level further than feels necessary. Instruct your teammate to do the same, for every signal, ask what it implies and what would confirm it. This is how you avoid the confirmation bias of only noticing signals that suit the pitch you already wanted to make.
Monday morning: a new enterprise account lands in your territory
Frame it. Open the Foundation project. Tell the teammate the account name, sector, and that you’re running a Signals pass. Ask what public sources it would prioritise for this type of company.
Feed it. Paste in the latest results summary, the “about” and strategy pages, two recent executive interviews, and the LinkedIn snapshots of the function you sell into.
Extract signals. Ask for trigger events, strategic initiatives, likely pressures and competitive threats, each labelled by how well the source supports it.
Interrogate. Push back: “What are you inferring rather than reading? What would you want to verify before I act on it?” Note the gaps to close yourself.
Bank it. Save the profile in the project. You now know more about this account before your first coffee than most sellers will before their first meeting.
Example ladder: the intelligence request
“Tell me about Acme Corporation.” Invites a generic, possibly invented summary with no commercial edge.
“Summarise Acme’s strategy and recent priorities from the material I’ve pasted.” Grounded in real sources, but stops at description rather than signals.
“From the pasted sources, extract Acme’s trigger events, strategic initiatives and likely pressures. Label each by evidence strength, and flag anything you’re inferring rather than reading.” Grounded, signal-focused, and honest about confidence. Ready to reason from.
Do not act on a fact you have not verified, and never repeat an AI-generated “insight” to a customer without checking the source. A confident invention repeated in a meeting costs you the credibility this whole method is built on. The teammate gathers; you confirm. Read the full discipline in Where AI Stops →
Build it: your first Signals pass
Once your Foundation is live, come back here and run a Signals pass on a real account. Capture the three signals you’d stake a hypothesis on. Don’t complete this on a first read, read the full method first.
Want every stage’s worksheet in one document?The complete field guide has all six build exercises, ready to print or fill in on screen, plus the full appendix of prompts.
Download the Field GuideYou’ve now produced a SIGNAL Research Brief. Next, you’ll test whether those signals actually support a commercial hypothesis, which is the distinction most sellers get wrong.