Use Case · RevOps Operators
Structured LinkedIn data that goes straight into your CRM — no cleanup
RevOps teams waste hours normalizing messy LinkedIn exports. seoprospector captures pre-structured leads with consistent field names, SEO scores, and action labels — ready to import into HubSpot, Salesforce, or any CRM.
What RevOps operators get from seoprospector
Clean data, consistent schema, and a pipeline signal — all without building a custom integration.
Structured capture from day one
Every lead is saved with consistent fields: name, headline, role type, company, website, SEO badge, action label. No column mapping, no cleanup on import.
SEO enrichment included
Every lead comes with an automatic SEO badge (CRITICAL / WEAK / OK / NO_WEBSITE / SITE_UNREACHABLE) and specific issues — data you'd normally pay for separately.
Action label for routing
CONTACT_NOW / CONTACT_SOFT / FIND_DECISION_MAKER / IGNORE — pre-assigned on every lead. Use them in CRM workflows to route to the right sequence automatically.
Quality score for reporting
STRONG / STEADY / EARLY signal shows whether the team's outbound is hitting the right accounts — combining actionable rate, decider rate, and HOT rate into one ops metric.
Clean data in, clean CRM out
The biggest RevOps tax on LinkedIn outbound is data normalization. Inconsistent job titles, missing domains, unknown SEO context — all of it needs manual cleanup before it's CRM-ready. seoprospector outputs a schema that imports directly.
- name — full name, always present
- website — normalized, validated domain URL
- seo_badge — CRITICAL / WEAK / OK / NO_WEBSITE / SITE_UNREACHABLE
- ui_action — CONTACT_NOW / CONTACT_SOFT / FIND_DECISION_MAKER / IGNORE
- ui_role — DECISION_MAKER / OTHER, detected from title
- All fields consistent across every export, every operator
LinkedIn outbound data that doesn't need cleaning
seoprospector captures, scores, and exports structured leads — ready for your CRM, your workflows, your reporting.