Works With
Build an AI agent that scores every new HubSpot lead against your Ideal Customer Profile automatically — checking company fit, role seniority, and enrichment data — then assigns a score, updates the CRM record, and fires an instant Slack alert to the assigned rep. No manual review required.
Every new contact that enters HubSpot is automatically evaluated, scored, and routed — before a rep has even seen the notification.
New contact → ICP check → lead score → CRM update → Slack alert
Agent polls HubSpot for new contacts and retrieves full contact record with all properties
AI evaluates company size, industry, role seniority, and enrichment data against your ICP criteria
Lead score, fit tier (High/Medium/Low), and qualification notes written back to the HubSpot contact
High-fit leads automatically trigger a new deal in the right HubSpot pipeline stage — no rep action needed
Slack message sent to the assigned rep with lead summary, score, company context, and HubSpot link
The agent replaces the manual work of reviewing every inbound lead — checking fit, assigning scores, updating records, and routing to the right rep — so your team only engages leads worth their time.
Every lead evaluated against your defined ICP — industry, company size, job title, seniority, geography, and tech stack. Scoring weights configured in Google Sheets so ops can adjust without touching the agent.
Lead score, fit tier, and qualification reasoning written back to HubSpot contact properties immediately after scoring. Reps open the record and the work is already done — no manual review required.
High-fit leads skip the qualification queue entirely — a HubSpot deal is created at the right pipeline stage the moment the score is assigned. No rep action needed to move the lead forward.
High and medium-fit leads trigger a Slack message to the assigned rep with the lead's company, score, reasoning, and a direct HubSpot link. Rep arrives fully briefed — not cold.
Every qualification run logged to Google Sheets — contact name, company, raw score, tier, and the specific ICP criteria that drove the result. Full audit trail for ops review and model tuning.
Scoring weights and ICP criteria live in Google Sheets — update them any time without redeploying the agent. A/B test different scoring models against conversion data to sharpen qualification accuracy over time.
How the agent connects HubSpot's contact API, Google Sheets scoring data, and Slack's messaging to run a production-grade lead qualification pipeline at any volume.
Contact search via HubSpot fetches new contacts on a polling interval or webhook trigger. Full contact record retrieved — all standard and custom properties — for scoring evaluation.
Contact update and deal creation via HubSpot writes score, tier, and notes to contact properties. Deal created in the specified pipeline with correct stage, name, and associated contact — all in one operation.
ICP criteria and scoring weights read from Google Sheets at runtime. Ops team updates the sheet — agent picks up changes on the next run without any redeployment. Scoring history appended to a separate audit tab.
Rep alert via Slack posts to the assigned channel or DM with lead name, company, score, tier, key ICP matches, and HubSpot record link. Message formatted for quick scanning — no long reads required.
HubSpot API failures, missing contact properties, and Slack delivery errors handled gracefully. Failed operations retried with exponential backoff. Every error logged with full context — no silent qualification failures.
OAuth2 for HubSpot with automatic token refresh. Slack bot token scoped to specific channels. Google Sheets access limited to scoring configuration and audit log sheets only.
Build an AI agent that qualifies and scores every new HubSpot lead automatically: 1. Contact Detection — Poll HubSpot for new contacts on a defined interval (or trigger on webhook). Fetch the full contact record including company, job title, industry, employee count, and any custom enrichment fields. 2. ICP Scoring — Read scoring criteria and weights from a Google Sheet. Evaluate each contact against: - Company size fit (employee count range) - Industry match - Job title and seniority level - Geography - Any custom properties (tech stack, funding stage, etc.) Assign a numerical score (0–100) and a fit tier: High, Medium, or Low. 3. CRM Update — Write the lead score, fit tier, and qualification reasoning back to the HubSpot contact as custom properties. Update lifecycle stage for High-fit leads. 4. Deal Creation — For High-fit leads, automatically create a HubSpot deal in the specified pipeline at the correct stage. Associate the contact and set the deal name and estimated value. 5. Slack Alert — Post a Slack message to the assigned rep or #qualified-leads channel with: contact name, company, score, tier, the top ICP signals that drove the result, and a direct HubSpot link. 6. Audit Log — Append every qualification result to a Google Sheet: contact name, company, raw score, tier, ICP criteria breakdown, and timestamp. Integrations: HubSpot (contact search, CRM update, deal creation), Google Sheets (scoring config & audit log), Slack (rep notification).
No code. No credit card to start. Production-ready in under 10 minutes.