Vertical Lead Pack — Named Decision-Makers + Send-Readiness

Turns raw, multi-source business data for a single vertical (real estate / clinic) into a decision-maker-ready lead pack. Generic scrapers hand you a flat contact list; this actor finds the named decision-maker, adds vertical-specific attributes, and tells you who to email first.

What it does

Connect the output of a Maps/web/directory scraper (or your own record list). For each business the actor:

• Merges multi-source data into one rich record (cross-source dedup) — split fragments from Maps + web + social become a single lead
• Extracts the named decision-maker — surfaces the clinic's chief physician or the agency's broker by name, instead of a generic info@
• Adds vertical-specific attributes — real estate: brokerage · license no · office-or-agent; clinic: specialty · booking channel
• Scores send-readiness — a deterministic READY / REVIEW / WEAK verdict + reason for every lead
• Ranks priority (0–100) + a "reach these first" shortlist so the salesperson starts with the best leads

Why it's different

Most lead scrapers stop at a raw contact dump. This actor behaves like a sales researcher: it decides who the real decision-maker is, enriches each lead with attributes that drive segmentation and personalization, and flags which leads are actually worth contacting. No LLM, fully deterministic → no hallucination, low cost, predictable output.

Input

Field	Description
vertical	The vertical: Real Estate or Healthcare / Clinic (decision-maker rules + attribute fields change accordingly)
records	Raw records to merge (output of a Maps/web/directory scraper). contacts[{name,title,email}] powers decision-maker extraction
datasetId	OR the ID of a connected Apify dataset
searchTerms	OR, when you have no data, terms used to call an upstream Maps scraper
maxPlaces	Max places per search in scrape mode

Output

Delivered in two layers:

• Dataset (table view): one row per lead with flat, scannable columns — priority · business · decision_maker_name · decision_maker_title · decision_maker_email · vertical_attributes · send_readiness. Sort, filter, and export directly.
• Full record (per lead): business, website, phone, address, vertical, decision_maker (name / title / email / source / role-account flag), vertical_fields (real estate: brokerage / license_no / office_or_agent · clinic: specialty / booking_channel), socials, all_emails, send_readiness (READY / REVIEW / WEAK) + reason. A final _summary row carries totals, verdict distribution, and the priority-ranked reach-first list.

Why this actor

1. Multi-source merge → one rich record per business (cross-source dedup, multi-key bridging, false-merge shield).
2. Decision-maker extraction → a named broker / chief physician instead of info@.
3. Vertical-specific attributes → real estate brokerage/license · clinic specialty (for segmentation + personalization).
4. Send-readiness verdict → niche leads are expensive; hit the best ones first.

Niche focus = lower competition + higher margin + a clear buyer.

How to use

1. Collect your business data with a Maps/web/directory scraper (or paste your own list).
2. Connect the output to this actor as records (or datasetId).
3. Pick the vertical (real estate / clinic) → Start.
4. Grab your prioritized lead pack from the Dataset tab.

Pricing (Pay-Per-Event)

You only pay for what you use: per run + per 100 records processed + per enriched lead. No monthly subscription.