Buying Stage Classifier
Use when the user wants to know where a buyer actually is in their journey: "what stage is this buyer in", "how serious is this visitor", "is this account decision-ready or just researching". Classifies a prospect, visitor, or account into one buying stage from whatever evidence is available: session trails, threads, transcripts, CRM context, or pasted notes. Judgment-only, nothing required to connect; Account Signal Radar and Website Intent Account Detector call it for stage reads.
Sample result
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Classify buyer stage| Criterion / Signal | Observed Evidence | Stage Fit | Signal Strength | |
|---|---|---|---|---|
| 1 | Commercial Intent | Requested custom pricing for 14-location veterinary practice rollout | Decision-Ready | High (Email) |
| 2 | Stakeholder Involvement | Elodie Andersson CC'd Chief Financial Officer Dr. Marcus Thorne on terms | Decision-Ready | High (Email) |
| 3 | Technical Evaluation | Reviewed Cornerstone EHR data migration guide and API documentation | Implementation | Medium (Web Session) |
| 4 | CRM Account History | Existing subscriber for 2 urban clinics expanding across acquired network | Customer Expansion | High (HubSpot CRM) |
Example run
“What buying stage is Bramble Instruments currently in? Please analyze recent email exchanges with Elodie Andersson, web visitor sessions, and our HubSpot CRM data to classify their decision readiness.”
Bramble Instruments is an existing subscriber across 2 urban clinics. Open opportunity recorded for $68,000 ARR 14-location practice expansion.
Elodie Andersson requested custom pricing for 14-location rollout and CC'd Chief Financial Officer Dr. Marcus Thorne to review terms.
Visitor session shows repeated hits on Cornerstone EHR data migration guide and API documentation.
Buying Stage Verdict: Bramble Instruments — Decision-Ready
More in Intent Conversion
- Sample result
Draft a LinkedIn DM replyTo:Imani SilvaThanks for sharing that, Imani. Managing temperature excursions across your multi-node pharma routes is tough without live telemetry. We helped Apex Cold Storage cut excursion investigation time by 70% using real-time BLE sensors—are you currently tracking pallet temps at the unit level or just ambient trailer temps?
Use when a user pastes a LinkedIn DM or sales conversation and asks what to say next, wants a reply drafted, needs to re-engage a quiet prospect, assess qualification, decide whether to ask for a call, or review a DM thread. It produces one copy-paste-ready reply with the qualification read behind it. Do not use for social posts, content writing, or cold outreach lists.
- Sample resultDaily approval batch of reply drafts
Prospect & Account Detected Intent Signal Summary Malik Nakamura VP Operations, Dovetail Dynamics Pricing Inquiry Asked about enterprise seat licensing for 45 field technicians Elena Vance Director of Fleet Ops, Apex HVAC Bad Timing Mentioned Q3 budget freeze until start of next month Marcus Thorne Owner, Blue Ridge Plumbing Closed-Lost Reactivation No response to proposal sent 90 days ago Handle everything that happens after a cold email or LinkedIn message is sent, as a drafts-only AI responder with a human approving every send. Detect new replies, classify each into one of eight intents, draft a response in the user's voice, run a three-touch follow-up when there is silence, and run a ninety-day reactivation on closed-lost and no-reply threads, all assembled into one daily approval batch. Tool-agnostic across HeyReach, Email Bison, Instantly, Smartlead, Outreach, Lemlist, Apollo, and orchestrated with n8n, Zapier, or Make. Carries hard veto rules so it never touches existing customers, partners, do-not-contact, or warm intros. Trigger when the user wants to handle inbound replies, auto-draft responses, manage follow-ups, run a reactivation or re-engagement campaign, build an AI SDR reply flow, or move prospects through pipeline stages with human approval.
- Sample resultCampaign reply audit
Sequence Step Human Replies Sentiment Yield Step 1: Public Works Hook 12 replies (14% human) 67% Positive (8 positive, 2 later) Step 2: Case Study Deep-Dive 3 replies (3% human) 0% Positive (3 unsubscribes) Step 3: Integration FAQ 11 replies (13% human) 91% Positive (7 positive, 3 later) Step 4: Breakup Email 5 replies (6% human) 20% Positive (1 positive, 4 opt-outs) Analyze cold-email campaign replies to identify what is working. Pull every reply from a sending tool or export, remove automated and unrelated noise, keep real human campaign replies, link each reply to its triggering email and sequence step, classify sentiment, compare variants, and surface winning steps, dead steps, recurring objections, referrals, and segment patterns. Use when the user wants a campaign reply deep-dive, reply sentiment analysis, sequence-step or message-variant performance, before-and-after campaign comparison, or reply data turned into insight. Read-only and tool-agnostic. Not for screening a new list or writing outreach emails.
