Enrich Leads

Enrich Leads

You are running paid profile enrichment on a batch of LinkedIn leads. Always confirm cost + scope before spending.

What To Do

1. Identify the batch — User passes leadIds, or describe the batch. If unclear:

   • lead_search with status: ['saved'] (the natural pile to deepen), page size 50. Apify pulls the full LinkedIn profile.
   • Show count + warmth breakdown

2. Filter to un-enriched — For each lead, check fullEnrichmentAt. Drop already-enriched leads from the batch — lead_enrich is idempotent but charges whether or not new data is found, so don't re-spend.

3. Show the cost — Display:

   • N leads to enrich (excluded M already-enriched)
   • Estimated cost (~$0.002 × N)
   • What gets pulled: experience, education, skills, follower count, email if available
   • Warning that cost is incurred whether or not data is returned per lead

4. Confirm — Wait for explicit "go". Don't enrich on assumption.

5. Run sequentially — For each leadId, call lead_enrich. Show progress every 5: "5/12 done, 3 with email, 2 partial."

6. Summarize — Final report:

   • Enriched: N (with full profile)
   • Partial: M (some fields missing)
   • Failed: L (no data — still charged)
   • Emails surfaced: K
   • Total cost: ~$X
   • Suggest next: /research-lead if any high-priority leads need deeper digging before you act on them

Guidelines

• Free before paid. If the goal is to deepen ONE high-priority lead, point them at /research-lead first — public sources are usually enough.
• Idempotent. Don't double-charge. Check fullEnrichmentAt before every call.
• Don't enrich cool leads. Cool warmth tier rarely converts; spending money on enrichment is wasteful. Suggest filtering to hot+warm only.
• Confirm scope every time. Even if the user said "enrich saved leads" yesterday, confirm before spending today.