exa-lead-gen

You can generate enriched lead lists by providing an ideal customer profile to infer sub-verticals and buying signals, which the system uses to find, score, and deduplicate matching companies into a structured CSV-ready output.

Finding companies that match your ideal customer profile is best handled by applying deep search queries to discover niche targets, then adding website, location, and funding stage signals for structured lead enrichment and prioritization.

Yes, you can export company discovery results to a CSV file. The process generates deduplicated, structured lead data with fit scores and enrichment signals specifically organized for outbound sales pipeline-building workflows.

Lead scoring for market segmentation works by applying fixed query parameters and schema-limited structured results to evaluate company fit, adding enrichment data like recent signals and funding stage to calculate prioritization scores.

Yes, you need to define a specific niche or target ideal customer profile to start researching leads. The system analyzes this input to infer your customer profile, identify sub-verticals, and apply relevant enrichment signals for accurate company discovery.

Limitations of automated prospecting include reliance on fixed query parameters and schema-limited structured results, meaning you must provide a clearly defined ideal customer profile upfront to ensure reliable batch search orchestration and accurate lead enrichment.