sales-research

Automate prospect research by providing a company name or profile URL to aggregate company data, contact profiles, and buying signals into structured sales preparation insights. The workflow uses company-enricher and linkedin-parser scripts to assemble actionable lead profiles.

Buying signals for sales call preparation include recent company developments, competitive context, and engagement opportunities. The signal detection workflow surfaces these indicators from aggregated data to identify outreach timing and relevance for B2B prospects.

CRM synchronization is supported through the crm-sync.py script, which updates CRM records with structured contact profiles and company data gathered during the prospect research workflow. This streamlines data collection and CRM updates automatically.

Build structured contact profiles from LinkedIn using the linkedin-parser script to extract professional backgrounds, roles, and connections. This structures the raw data into formats suitable for personalized outreach and lead profiling.

The prospect research approach applies to researching new prospects across B2B contexts by standardizing company analysis and signal detection. It uses research checklists and automation scripts to maintain consistent data gathering regardless of scale.

A company research checklist for sales preparation includes essential company data, recent developments, buying signals, and competitive context. The research-checklist resource provides the methodology to quickly gather these elements for structured sales insights.