Event Lead Extractor

The event intelligence engine for sales, partnerships, sponsorship, and competitive-research teams.

Discover the sponsors, exhibitors, speakers, and partners at any conference website — then track sponsorship upgrades, competitor presence, repeat participation, and emerging vendors across entire event seasons. Paste in event URLs from Eventbrite, Lu.ma, Sched, Bizzabo, or any conference site; get back scored, classified, routed company intelligence.

Questions this actor answers

• Which companies are increasing their event investment (Bronze → Platinum upgrades)?
• Which events are worth sponsoring or attending?
• Which competitors are showing up at every conference?
• Which vendors appear across the entire industry circuit?
• Which sponsors are new entrants this season?
• Which companies should my team contact first?

Traditional event scrapers extract links. This is event participation intelligence — it tracks how companies invest in conferences over time.

One run across an event season

Point it at a season of industry events (scheduled under one watchlist) and the summary record reports, for example:

{
  "recordType": "summary",
  "coverage": { "eventsCrawled": 24, "domainsFound": 1387 },
  "insights": {
    "recommendedEvents": [ { "event": "RSA Conference", "authorityScore": 94 }, { "event": "Black Hat", "authorityScore": 90 } ],
    "newEntrants": ["openai.com", "anthropic.com"]
  },
  "watchlist": {
    "upgradedSponsors": ["mongodb.com", "datadog.com"],
    "seriesIntelligence": { "repeatSponsors": 94, "retentionRate": 0.81 }
  }
}

(Illustrative — field names are exactly what the actor returns.)

What makes this valuable

A sponsor appearing once is noise. A sponsor appearing at RSA, Black Hat, Infosecurity Europe, and the Gartner Security Summit in the same year is a signal — it reveals marketing budget, partnership activity, expansion plans, and industry focus.

This actor turns those signals into structured intelligence: repeat sponsors, sponsorship upgrades, competitor presence, emerging vendors, and high-authority events — so you focus on where money is moving. Most companies treat conferences as a marketing expense; this treats every sponsor list as a map of who is investing in your market.

The real output

Beyond the per-company leads, every run emits one summary record — the answers, not just the data:

{
  "recordType": "summary",
  "insights": {
    "topSponsors": [ { "domain": "datadog.com", "appearances": 7 } ],
    "recommendedEvents": [ { "event": "RSA Conference", "authorityScore": 92, "reason": "tier-1, 84 sponsors, large scale" } ],
    "newEntrants": ["openai.com", "anthropic.com"],
    "upgradedSponsors": ["mongodb.com"]
  },
  "shareOfVoice": { "crowdstrike.com": 41, "sentinelone.com": 33, "wiz.com": 26 }
}

Why this is different

Most event scrapers return a list of links:

{ "url": "https://www.datadog.com", "domain": "datadog.com" }

This returns a decision:

{
  "company": "datadog.com",
  "foundAs": "sponsor",
  "sponsorTier": "platinum",
  "appearanceCount": 7,
  "sponsorMomentum": "upgrading",
  "sponsorOpportunity": 88,
  "competitorMatch": false,
  "decision": "outreach-immediately"
}

The difference is intelligence, not extraction.

What you'll learn from a single run

• Event intelligence — which events matter (eventAuthorityScore, eventTier), which attract the most sponsors, how big each is
• Competitive intelligence — where your competitors are sponsoring (competitorMatch), their shareOfVoice, and new sponsor entrants
• Market intelligence — which vendors appear everywhere (appearanceCount, multiEvent), which are increasing investment (sponsorMomentum)
• Lead intelligence — who to contact (decision, accountReadiness), contact difficulty, and outreach priority

Before vs after

Before — open the sponsors page, copy company names, research each website, find contacts, check which are competitors, build a spreadsheet, repeat for 50 events.

After — one run returns topSponsors, recommendedEvents, newEntrants, upgradedSponsors, per-lead decision, and (on a schedule) what changed since last time.

Signals you can't get from a one-time scrape

A one-time scrape can only tell you what's on the page today:

{ "company": "mongodb.com", "sponsorTier": "gold" }

Set a watchlistName and run on a schedule, and the actor builds a proprietary event-participation history a single scrape can't reproduce:

{
  "company": "mongodb.com",
  "sponsorTier": "platinum",
  "changeFlag": "TIER_UPGRADED",
  "sponsorMomentum": "upgrading",
  "eventFootprint": { "runsSeen": 7, "sponsoredAppearances": 6 }
}

You see sponsorship upgrades, sponsor churn, repeat appearances, cross-event participation, and competitor share of voice accumulate over time. Competitors can clone a scraper; they can't clone your history.

Watch sponsorship changes over time

Run 1 — MongoDB is a Gold sponsor:

{ "company": "mongodb.com", "sponsorTier": "gold" }

Run 2 (same watchlist, next quarter) — it upgraded:

{ "company": "mongodb.com", "sponsorTier": "platinum", "changeFlag": "TIER_UPGRADED", "sponsorMomentum": "upgrading" }

The summary surfaces it automatically:

{ "watchlist": { "upgradedSponsors": ["mongodb.com"], "newSponsors": ["openai.com"], "lostSponsors": ["legacyvendor.com"] } }

A tier upgrade is a budget-increase signal — the moment to reach out.

Example workflow: find companies increasing event spend

1. Run in recon mode across 20 industry events under one watchlistName (fast, no enrichment cost).
2. On the next scheduled run, set the intelligence filters: requireMomentum: "upgrading", minAppearanceCount: 3, minSponsorOpportunity: 75.
3. Export the dataset — only companies actively escalating their event investment land in it (you're not charged for the rest).

The result is a shortlist of vendors putting money into the market right now.

Event Lead Extractor vs generic event scrapers

Capability	Generic scraper	Event Lead Extractor
Sponsor / speaker extraction	✅	✅
Sponsorship tier detection	❌	✅
Competitor tracking	❌	✅
Cross-event activity	❌	✅
Sponsor momentum (cross-run)	❌	✅
Event authority scoring	❌	✅
Event recommendations	❌	✅
Lead routing decisions	❌	✅

Who it's for

• SDRs / AEs — find sponsors attending 5+ events and prioritise outreach by sponsorOpportunity and decision.
• Partnership managers — track which competitors are sponsoring which industry events.
• Sponsorship / event teams — spot companies upgrading sponsorship levels and the highest-authority events to target.
• Competitive-intelligence / investors — see which vendors are appearing across the whole industry circuit and who's expanding into your market.

Modes

Pick a mode to match the job — each presets the right filters and enrichment:

Mode	What it does
full (default)	Crawl + full contact/score enrichment on every company
recon	Fast event scan — domains, sponsor tiers, and event authority only. No enrichment, no sub-actor cost. For scanning many events before committing budget
sponsor-hunter	Keep only sponsors (with tiers). For sponsorship-focused prospecting
competitive-intel	Keep sponsors, partners & exhibitors, no enrichment — who's at the event, not their contacts

Features

Discover

• Multi-source event crawling — handles Eventbrite, Lu.ma, Sched, Bizzabo, conference microsites, and any HTML event page with sponsor or speaker listings
• Automatic browser fallback — static HTML first for speed; JavaScript-heavy sponsor pages (React/Next/Swapcard/Hubilo/ExpoFP) that come back empty are re-rendered in a real browser automatically (renderMode: "auto") — paste a URL and the actor figures out how to read it
• Automatic subpage discovery — follows links to /sponsors, /speakers, /exhibitors, /partners, /agenda, and similar subpages without manual configuration
• Smart domain filtering — blocks 100+ noise domains (social networks, CDNs, analytics, payment processors, event platforms) so your results contain only real business leads

Analyse

• Intelligent role classification — tags every company as sponsor, exhibitor, partner, speaker, organizer, or linked from surrounding HTML context and section headings
• Sponsorship tier extraction — reads the section heading to tag each sponsor title / diamond / platinum / gold / silver / bronze (+ sponsorRank prestige order). A Diamond sponsor is a very different prospect than a Bronze one
• JSON-LD and meta tag parsing — reads structured data (Schema.org Event, OpenGraph, __NEXT_DATA__) for event title, date, and location

Intelligence

• Event authority scoring — a 0-100 eventAuthorityScore + tier-1/2/3 + estimatedScale per event, so you can decide whether an event is worth your budget before enrichment
• Competitor watchlist — flag your competitors' presence with watchDomains; every matching lead gets competitorMatch: true
• Cross-event activity — appearanceCount + multiEvent show which companies appear across multiple events in the run; the summary lists repeatCompanies[]
• Cross-run sponsor momentum (opt-in) — set a watchlistName and re-run the same events on a schedule; each company then carries changeFlag (NEW / UNCHANGED / TIER_UPGRADED / TIER_DOWNGRADED) and sponsorMomentum, and the summary surfaces new vs lost sponsors + a changeFeed[] since last time. A sponsor upgrading Bronze → Platinum is a budget signal you can't get from a one-shot scrape
• Company event footprint (opt-in) — eventFootprint accumulates each company's participation across every run on the watchlist (runsSeen, eventAppearances, sponsoredAppearances, first/last seen). The proprietary history competitors can't backfill
• Competitive share of voice — with a watchDomains watchlist, the summary's shareOfVoice shows who owns more of the circuit among your tracked competitors
• Industry rollup — when enrichment runs, the summary's industryBreakdown counts companies per vertical
• Canonical domain resolution — a clean registrable-root dedup/join key across events

Recommend

• "Where should I focus?" insights — the summary's insights block ranks topSponsors, recommendedEvents (highest-authority events to target, with a reason), and (on a watchlist) newEntrants + upgradedSponsors — the decision layer, synthesised from the run, no extra config
• Series retention analytics — on a watchlist, seriesIntelligence reports retentionRate, repeatSponsors and yearsTracked: which conferences keep their sponsors vs which are churning

Enrich & decide

• Full contact enrichment — calls Website Contact Scraper, Email Pattern Finder, and B2B Lead Qualifier to append emails, phones, social links, email patterns, industry, and a lead score
• Routed lead decision — every lead carries a decision (outreach-immediately / add-to-nurture / enrich-then-revisit / archive / manual-review) your CRM or cadence tool branches on directly
• Job modes & batch — recon / sponsor-hunter / competitive-intel / full presets; process an entire conference season in one run (domains deduped across events)

Use Cases

Pre-event outreach

Event marketers preparing outreach campaigns who need a structured list of every sponsor and exhibitor with direct contact information. Run the actor on the event page two weeks before the conference and import leads into your CRM.

Trade show prospecting

Sales development reps (SDRs) mining trade show sponsor lists to build targeted account lists enriched with decision-maker emails and company quality scores. Filter by foundAs: "sponsor" to focus on companies with marketing budget.

Competitive sponsorship tracking

Business development managers tracking competitor sponsorship activity across industry events to identify partnership opportunities and understand market positioning.

Event audit

Conference organizers auditing their own events to understand which sponsors and speakers are most visible and how their contact information appears online.

Investor and partner discovery

Startup founders scanning accelerator demo days, pitch events, and investor conferences to identify potential partners, mentors, or customers exhibiting at those events.

Industry ecosystem mapping

Market researchers aggregating company participation data across multiple events to map industry ecosystems and identify trending vendors.

How to Use

1. Gather event URLs. Copy the main event page URL from Eventbrite, Lu.ma, or any conference website. For best results, also include direct links to pages like /sponsors or /speakers if they exist.
2. Configure the input. Paste the URLs into the Event URLs field. Leave Discover Subpages enabled so the actor automatically finds sponsor and speaker listing pages. Set Max Leads Per Event to control output size.
3. Choose enrichment level. Keep Skip Enrichment unchecked for full pipeline output (emails, phones, lead scores). Enable it if you only need a quick domain list without the extra cost of sub-actor calls.
4. Run the actor. Click Start and wait for the pipeline to complete. The actor first crawls all event pages, then sequentially runs the Contact Scraper, Email Pattern Finder, and Lead Qualifier on every extracted domain.
5. Export your leads. Download results as JSON, CSV, or Excel from the dataset tab.

Input Parameters

Field	Type	Required	Default	Description
eventUrls	string[]	Yes	—	URLs of event or conference pages. Include main page and optionally direct /sponsors, /speakers, or /exhibitors links
mode	string	No	full	Run preset: full (crawl + enrichment), recon (fast scan, no enrichment), sponsor-hunter (sponsors only), competitive-intel (sponsors/partners/exhibitors, no enrichment). See Modes above
renderMode	string	No	auto	auto = static HTML first, browser-render JS-heavy pages that came back empty; http = static only (cheapest); browser = render every event page. Browser rendering needs ≥2 GB memory (the default)
watchDomains	string[]	No	[]	Competitor watchlist. Domains to flag when present (e.g. hubspot.com). Matching leads get competitorMatch: true; www/subdomain variants matched automatically
watchlistName	string	No	—	Name a watchlist to turn on cross-run tracking. Re-run the same events under the same name and each company gets changeFlag + sponsorMomentum; the summary lists new/lost sponsors. Blank = stateless one-shot run
discoverSubpages	boolean	No	true	Automatically find and crawl subpages like /sponsors, /speakers, /exhibitors, and /partners linked from the event URL
maxLeadsPerEvent	integer	No	50	Maximum number of unique company domains to extract per event URL. Range: 1–500
skipEnrichment	boolean	No	false	When enabled, only extracts domains and skips enrichment sub-actors. Much faster and cheaper
scoringProfile	string	No	sales	How the lead qualifier weights its categories: default, sales (contact-heavy), marketing (presence-heavy), or recruiting (team-heavy). Only applies when enrichment is on
outputProfile	string	No	full	How much per-lead detail to write: full (every field), standard (drop agent diagnostics), minimal (decision surface only), or llm (decision surface + summary). All analysis runs internally regardless
proxyConfiguration	object	No	—	Proxy settings for crawling event pages. Recommended for Eventbrite and other sites that block datacenter IPs

Input Examples

Single conference, full enrichment:

{
  "eventUrls": ["https://www.tech-week.com/"],
  "discoverSubpages": true,
  "maxLeadsPerEvent": 100,
  "skipEnrichment": false
}

Multiple events, quick domain scan:

{
  "eventUrls": [
    "https://www.tech-week.com/",
    "https://websummit.com/",
    "https://www.ces.tech/"
  ],
  "discoverSubpages": true,
  "maxLeadsPerEvent": 50,
  "skipEnrichment": true
}

Direct sponsor page with proxy:

{
  "eventUrls": [
    "https://www.eventbrite.com/e/my-event-12345",
    "https://www.eventbrite.com/e/my-event-12345/sponsors"
  ],
  "discoverSubpages": false,
  "maxLeadsPerEvent": 200,
  "skipEnrichment": false,
  "proxyConfiguration": { "useApifyProxy": true }
}

Input Tips

• Include direct subpage URLs for guaranteed coverage. Auto-discovery handles most cases, but explicit URLs ensure nothing is missed.
• Use Skip Enrichment for reconnaissance. Run with enrichment off first to preview lead counts, then re-run with enrichment on for high-value events only.
• Set Max Leads thoughtfully. Large trade shows (CES, Web Summit) may have 500+ exhibitors. Small meetups rarely exceed 20.
• Enable proxy for Eventbrite. Eventbrite serves limited HTML to bots — residential or auto proxy ensures the full sponsor list renders.

Output Example

Each item in the output dataset represents one company found at one event, enriched with contact data and a lead quality score:

{
  "recordType": "lead",
  "schemaVersion": "2.1.0",
  "eventId": "lead_3f8a1c9e7b2d4a06",
  "eventUrl": "https://www.tech-week.com/",
  "eventTitle": "London Tech Week 2025",
  "eventDate": "2025-06-09",
  "eventLocation": "ExCeL London, London",
  "domain": "datadog.com",
  "canonicalDomain": "datadog.com",
  "companyUrl": "https://www.datadog.com",
  "foundAs": "sponsor",
  "linkText": "Datadog",
  "sponsorTier": "platinum",
  "sponsorRank": 2,
  "sectionTitle": "Platinum Sponsors",
  "appearanceCount": 3,
  "eventRoles": ["sponsor", "speaker"],
  "multiEvent": true,
  "competitorMatch": false,
  "industry": "saas",
  "sponsorOpportunity": 88,
  "changeFlag": "TIER_UPGRADED",
  "sponsorMomentum": "upgrading",
  "firstSeenAt": "2024-06-10T09:00:00.000Z",
  "eventFootprint": { "runsSeen": 3, "eventAppearances": 9, "sponsoredAppearances": 7, "firstSeen": "2024-06-10T09:00:00.000Z", "lastSeen": "2025-06-09T09:00:00.000Z" },
  "emails": ["info@datadog.com", "events@datadog.com"],
  "phones": ["+1-866-329-4466"],
  "contacts": [
    { "name": "Sarah Chen", "title": "VP of Marketing", "email": "sarah.chen@datadog.com" }
  ],
  "socialLinks": {
    "linkedin": "https://www.linkedin.com/company/datadog",
    "twitter": "https://twitter.com/datadoghq"
  },
  "emailPattern": "{first}.{last}@datadog.com",
  "emailPatternConfidence": 0.92,
  "generatedEmails": [
    { "name": "Sarah Chen", "email": "sarah.chen@datadog.com" }
  ],
  "decision": "outreach-immediately",
  "shouldOutreach": true,
  "score": 87,
  "grade": "A",
  "confidence": { "score": 0.91, "level": "high", "components": [] },
  "accountReadiness": { "score": 84, "band": "hot", "reasons": ["verified personal email", "decision-maker contact found"] },
  "contactDifficulty": "easy",
  "whyNow": { "type": "partnership", "score": 72, "signals": ["partner-program"], "recommendedPersona": "VP of Marketing", "summary": "Active partner program — lead with co-marketing." },
  "painSignals": [
    { "signal": "actively-hiring", "evidence": ["12 open marketing roles"], "likelyPain": "scaling demand-gen capacity" }
  ],
  "summary": "Datadog — sponsor at London Tech Week. Grade A, verified VP-level contact, ready to outreach.",
  "agentContract": { "decision": "qualified-A", "confidence": 0.91, "nextAction": "outreach-immediately", "costToAct": 0 },
  "pipelineState": { "eventCrawled": true, "contactScraped": true, "patternFound": true, "qualified": true },
  "dataGaps": [],
  "nextActions": [],
  "pipelineSteps": ["event-crawl", "contact-scraper", "email-pattern-finder", "lead-qualifier"],
  "extractedAt": "2025-06-15T14:32:18.000Z"
}

Every run also pushes one recordType: "summary" record carrying a coverage block (events crawled, domains found / enriched / scored), run totals, matchedCompetitors[], shareOfVoice (each watched competitor's % of appearances among watched competitors present), repeatCompanies[] (companies appearing at ≥2 events this run), industryBreakdown[] (companies per vertical when enriched), an insights block (topSponsors / recommendedEvents / newEntrants / upgradedSponsors — the "where should I focus?" layer), a watchlist block (newSponsors[] / lostSponsors[] / tier-change counts / a consolidated changeFeed[] of "company: gold → platinum" / "removed" lines / seriesIntelligence retention analytics, when watchlistName is set), and a per-event rollup (… sponsorDensity …) (events[] with companies found, sponsor/exhibitor/speaker counts, average score, hot leads, ready-to-outreach, eventAuthorityScore 0-100, eventTier tier-1/2/3, estimatedScale small/medium/large, plus eventYear and eventSeries). Read the authority block to decide which events are worth enrichment budget before you spend it. The same object is mirrored to the run's key-value store under the SUMMARY key.

When enrichment is skipped (skipEnrichment: true), the contact, pattern, and decision-layer fields are empty arrays, empty objects, or null, and nextActions points at the sibling actors that would fill them.

Output Fields

Event Context Fields

Field	Type	Description
eventUrl	string	The input URL this lead was found on
eventTitle	string/null	Event name extracted from page title, OpenGraph, JSON-LD, or __NEXT_DATA__
eventDate	string/null	Event start date (ISO 8601 or free text, depending on source)
eventLocation	string/null	Venue name and/or city extracted from structured data

Company Fields

Field	Type	Description
domain	string	Company domain as found (may include a subdomain)
canonicalDomain	string	Registrable root domain (careers.microsoft.com → microsoft.com) — the dedup/join key
companyUrl	string	Full URL as found on the event page
foundAs	string	Classification: sponsor, exhibitor, partner, speaker, organizer, or linked
linkText	string/null	Anchor text of the link on the event page

Sponsorship & Event Intelligence

Field	Type	Description
sponsorTier	string/null	Tier from the section heading: title, diamond, platinum, gold, silver, bronze, startup, community, media. null when no tier language was present
sponsorRank	integer/null	Prestige rank among tiered sponsors at this event (1 = most prestigious)
sectionTitle	string/null	The page section heading the link sat under (e.g. "Platinum Sponsors")
appearanceCount	integer	How many of this run's events the company appeared at (within-run only)
eventRoles	string[]	Distinct roles the company held across this run's events
multiEvent	boolean	True when the company appeared at >1 event in this run
competitorMatch	boolean	True when canonicalDomain is in your watchDomains watchlist
industry	string/null	Company industry from the qualifier's company intelligence (populated only when enrichment runs)

Cross-Run Intelligence (only when watchlistName is set)

Field	Type	Description
changeFlag	string/null	Change vs the prior run on this watchlist: NEW, UNCHANGED, TIER_UPGRADED, TIER_DOWNGRADED
sponsorMomentum	string/null	Tier trajectory: new, upgrading, downgrading, stable — the budget signal
firstSeenAt	string/null	ISO timestamp the company was first seen on this watchlist
eventFootprint	object/null	Accumulated participation across all runs on this watchlist: { runsSeen, eventAppearances, sponsoredAppearances, firstSeen, lastSeen }. The proprietary history a one-shot scrape can't reproduce

How cross-run tracking behaves:

• Run 1 (baseline): every company gets changeFlag: "NEW" and sponsorMomentum: "new"; the snapshot is saved. No new/lost lists yet.
• Run 2+: companies are compared against the previous run — changeFlag/sponsorMomentum populate, and the summary's watchlist block lists newSponsors[] and lostSponsors[] (present last run, gone now).
• State lives in a named key-value store (event-lead-<watchlistName>), so it survives dataset purges. Use the same watchlistName across scheduled runs. State is bounded (50k companies, oldest dropped first). On restricted-permission tokens the actor degrades to a stateless run and logs a warning.

Contact Scraper Fields (from sub-actor)

Field	Type	Description
emails	string[]	Email addresses found on the company website
phones	string[]	Phone numbers found on the company website
contacts	array	Named contacts with name, title, and email
socialLinks	object	Social media profile URLs (LinkedIn, Twitter, etc.)

Email Pattern Fields (from sub-actor)

Field	Type	Description
emailPattern	string/null	Detected email format (e.g., {first}.{last}@domain.com)
emailPatternConfidence	number/null	Confidence score (0–1) for the detected pattern
generatedEmails	array	Emails generated using the pattern for discovered contacts

Decision Layer

The decision fields are surfaced from the qualifier and contact scraper so you can route leads without re-reading the raw data. Branch your cadence tool / Zapier rule on decision or shouldOutreach; sort the list on accountReadiness.score.

Field	Type	Description
decision	string/null	Routing primitive: outreach-immediately, add-to-nurture, enrich-then-revisit, archive, or manual-review
shouldOutreach	boolean/null	Send-now gate — true when the lead is ready to contact
score	number/null	Lead quality score (0–100)
grade	string/null	Letter grade (A through F)
confidence	object/null	{ score (0–1), level, components[] } — calibrated confidence in the score
accountReadiness	object/null	{ score (0–100), band (hot/warm/cool/cold), reasons[] } — the "contact this week?" headline; sort on .score
contactDifficulty	string/null	Reachability band: easy, medium, hard, unreachable
whyNow	object/null	Timing axis: { type, score, signals[], recommendedPersona, summary }
painSignals	array/null	Inferred outreach hooks: [{ signal, evidence[], likelyPain }] (heuristic, evidence-backed)
summary	string/null	Plain-English one-line lead summary an LLM can quote
agentContract	object/null	Compact agent surface: { decision, confidence, nextAction, costToAct }
sponsorOpportunity	integer	Participation-propensity signal (0-100): how active/escalating the company is as an event sponsor (frequency + tier + contactability + momentum). A distinct axis from the lead score — sort by it to find the most event-active companies. Not measured spend

Suite Navigation

Field	Type	Description
pipelineState	object	What enrichment has been done: { eventCrawled, contactScraped, patternFound, qualified }
dataGaps	array	[{ field, reason, suggestedFix }] — each suggestedFix names the sibling actor that closes the gap
nextActions	string[]	Ordered sibling-actor slugs to run next to make the lead actionable

Meta Fields

Field	Type	Description
recordType	string	lead, summary, or error — filter on this in SQL / Sheets / automation
schemaVersion	string	Output-contract version (additive within a major version)
eventId	string	Stable hash of (event URL + domain) — re-runs dedupe cleanly on this
pipelineSteps	string[]	Which pipeline steps completed
extractedAt	string	ISO 8601 timestamp of extraction

Programmatic Access (API)

Python

from apify_client import ApifyClient

client = ApifyClient("YOUR_API_TOKEN")

run = client.actor("ryanclinton/event-lead-extractor").call(run_input={
    "eventUrls": ["https://www.tech-week.com/"],
    "discoverSubpages": True,
    "maxLeadsPerEvent": 100,
    "skipEnrichment": False,
})

for lead in client.dataset(run["defaultDatasetId"]).iterate_items():
    print(f"{lead['domain']} ({lead['foundAs']}) — "
          f"Score: {lead['score']}, Grade: {lead['grade']}")
    if lead["emails"]:
        print(f"  Emails: {', '.join(lead['emails'])}")

JavaScript

import { ApifyClient } from "apify-client";

const client = new ApifyClient({ token: "YOUR_API_TOKEN" });

const run = await client.actor("ryanclinton/event-lead-extractor").call({
  eventUrls: ["https://www.tech-week.com/"],
  discoverSubpages: true,
  maxLeadsPerEvent: 100,
  skipEnrichment: false,
});

const { items } = await client.dataset(run.defaultDatasetId).listItems();
items
  .filter((lead) => lead.foundAs === "sponsor")
  .forEach((lead) => {
    console.log(`${lead.domain}: Score ${lead.score} (${lead.grade})`);
    console.log(`  Emails: ${lead.emails.join(", ")}`);
  });

cURL

# Start the actor run
curl -X POST "https://api.apify.com/v2/acts/ryanclinton~event-lead-extractor/runs?token=YOUR_API_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{
    "eventUrls": ["https://www.tech-week.com/"],
    "discoverSubpages": true,
    "maxLeadsPerEvent": 100,
    "skipEnrichment": false
  }'

# Fetch results (replace DATASET_ID from the run response)
curl "https://api.apify.com/v2/datasets/DATASET_ID/items?token=YOUR_API_TOKEN&format=json"

How It Works

1. Discover — crawl each event page (static HTML first, browser fallback for JS-heavy pages) and follow /sponsors, /speakers, /exhibitors, /partners subpages; filter out 100+ noise domains so only real business domains remain.
2. Classify — tag each company's role (sponsor / exhibitor / partner / speaker / organizer) and sponsorship tier from the section it sits under.
3. Enrich — call the contact scraper, email-pattern finder, and lead qualifier on the unique domains to append contacts, email patterns, industry, and a 0–100 lead score.
4. Track — score event authority, flag competitors, compute cross-event activity and (on a watchlist) cross-run momentum, new/lost sponsors, and footprint.
5. Decide — route each lead to a decision, and emit a summary record with the insights recommendation layer.

Resilience: each enrichment sub-actor runs independently — if one fails the pipeline continues and those fields are empty rather than crashing the run. Deduplication: domains are deduped globally across events (a company at three events is enriched once, but appears per event it was found at).

Classification Reference

The actor classifies each extracted company based on keywords found in surrounding HTML:

Classification	Trigger Keywords
sponsor	sponsor, sponsored, sponsorship, presented by, brought to you by, platinum, gold, silver, bronze, diamond, title sponsor
exhibitor	exhibitor, exhibit, booth, exhibition, expo
partner	partner, partnership, community partner, media partner, technology partner
speaker	speaker, keynote, panelist, presenter, moderator, fireside
organizer	organizer, organiser, hosted by, organized by, organised by
linked	No matching keywords found — generic external link

Blocked Domain Categories

The domain filter blocks 100+ domains across these categories to ensure only real business leads appear in results:

Category	Examples
Social media	facebook.com, twitter.com, linkedin.com, instagram.com, tiktok.com
Event platforms	eventbrite.com, lu.ma, meetup.com, hopin.com, bizzabo.com, cvent.com
CDNs / Infrastructure	cloudflare.com, googleapis.com, cloudfront.net, fastly.net
Analytics / Ads	google-analytics.com, doubleclick.net, hotjar.com, mixpanel.com
Big tech (too generic)	google.com, apple.com, microsoft.com, amazon.com
Email providers	gmail.com, outlook.com, yahoo.com
URL shorteners	bit.ly, t.co, tinyurl.com
CMS / Website builders	wordpress.com, squarespace.com, wix.com, medium.com
Payment processors	paypal.com, stripe.com

Subdomains of blocked domains (e.g., cdn.example.com, static.example.com) are also filtered.

How Much Does It Cost?

Cost depends on how many events you process, how many company domains are found, and whether enrichment is enabled.

Scenario	Events	Leads Found	Enrichment	Estimated Cost
Quick domain scan	1	~30	Skipped	~$0.01
Single event, full pipeline	1	~50	Full	~$0.50
5 events, full pipeline	5	~200	Full	~$2.00
Conference season (20 events)	20	~800	Full	~$8.00

Free plan users can process approximately 1–2 small events with enrichment per month. Skipping enrichment dramatically reduces cost since no sub-actors are called.

The enrichment phase accounts for most of the cost because it invokes three separate sub-actors once per unique domain. To reduce cost, enable Skip Enrichment for initial exploration and run the full pipeline only on high-value events.

Tips

• Include direct subpage URLs for best coverage. If the conference site has a dedicated /sponsors or /exhibitors page, add it alongside the main event URL.
• Use Skip Enrichment for quick reconnaissance. Run with enrichment off first to preview how many leads an event yields. Then re-run with enrichment on only if the domain list looks promising.
• Set Max Leads Per Event thoughtfully. For large trade shows with hundreds of exhibitors, increase the limit to 200–500. For small meetups, the default of 50 is more than enough.
• Enable proxy for Eventbrite and gated sites. Some event platforms serve limited HTML to bots. Using a residential or auto proxy ensures the full sponsor list is rendered.
• Batch related events together. Process an entire conference series or industry vertical in a single run. The actor deduplicates domains across events, so companies appearing at multiple events are enriched only once.
• Filter by foundAs field after export. If you only want sponsors, filter the CSV or JSON output by foundAs === "sponsor" to exclude speakers, organizers, and generic links.

Use in Dify

Drop this actor into Dify workflows via the Apify plugin's Run Actor node. Each lead returns scored, classified, and routed as structured JSON — outreach-immediately / add-to-nurture / enrich-then-revisit / archive / manual-review plus the accountReadiness.band (hot/warm/cool/cold) and contactDifficulty (easy/medium/hard/unreachable) enums your downstream node branches on. A plain event-page scraper pointed at the same URL returns a list of links; this returns the decision of whether to work each lead, and how.

• Actor ID: ryanclinton/event-lead-extractor
• Sample input (full pipeline, decision-surface output for routing):

{
    "eventUrls": ["https://www.tech-week.com/"],
    "discoverSubpages": true,
    "maxLeadsPerEvent": 100,
    "skipEnrichment": false,
    "scoringProfile": "sales",
    "outputProfile": "minimal"
}

Branching example. Add an If/Else node after the Run Actor node and route on the decision field's equality match — no prose parsing:

• decision == "outreach-immediately" → push to your cadence tool / Salesloft / Instantly sequence
• decision == "add-to-nurture" → add to a marketing drip list
• decision == "enrich-then-revisit" → loop back through the actors named in nextActions[]
• decision == "archive" → drop
• recordType == "summary" → read coverage + events[] for the run-level rollup

For an automation gate, branch on the shouldOutreach boolean (true = send-now queue). For finer triage, sort or threshold on accountReadiness.score (0-100) and route phone-first vs email-first on contactDifficulty.

The nextActions[] array is usable verbatim — it lists the sibling actor slugs (website-contact-scraper, email-pattern-finder, b2b-lead-qualifier) to run next to make an incomplete lead actionable, in order. No LLM rewriting needed; a Dify iteration node can call each slug directly. Opt-in modes the workflow can leverage: scoringProfile (sales / marketing / recruiting weighting) and outputProfile (minimal returns only the decision surface for clean branching; llm adds the plain-English summary for an LLM node to quote).

Combine with Other Actors

Actor	How to combine
Website Contact Scraper	Used internally by this actor for enrichment. Run standalone for deeper crawls (more pages per domain)
Email Pattern Finder	Used internally. Run standalone to test patterns for specific domains
B2B Lead Qualifier	Used internally. Run standalone for detailed score breakdowns with signal-level detail
B2B Lead Gen Suite	Full-pipeline B2B lead gen from any domain list — use when you already have domains and don't need event context
HubSpot Lead Pusher	Push event leads directly to HubSpot CRM with automatic field mapping
Company Deep Research	Deep-dive research on high-scoring event leads before outreach
Brand Protection Monitor	Monitor competitor event sponsorship activity over time
Lead Enrichment Pipeline	All-in-one Clay alternative: email discovery, verification, company research, and scoring in one run ($0.12/lead)
AI Outreach Personalizer	Generate personalized cold emails using your own OpenAI/Anthropic key — zero AI markup ($0.01/lead)
Intent Signal Tracker	Track buying signals: hiring, tech changes, funding, content updates. Prioritize outreach by intent score ($0.05/company)
Lead Data Quality Auditor	Audit lead data quality before outreach — email verification, phone validation, domain freshness ($0.005/record)

Limitations

• JavaScript rendering is a fallback, not the default path — pages are read as fast static HTML first; only JS-heavy event pages (React/Next/Swapcard/Hubilo/ExpoFP) that return nothing are re-rendered in a real browser (renderMode: "auto", default). Browser rendering needs ≥2 GB memory; on a leaner run those pages are read static-only with a warning.
• No login/CAPTCHA support — only crawls publicly accessible pages. Cannot handle password-protected, login-gated, or CAPTCHA-protected event pages.
• No attendee data — only extracts company-level data from public sponsor, exhibitor, and speaker listings. Does not scrape attendee lists, registration forms, or personal profiles.
• Classification is heuristic — link classification depends on surrounding HTML context (headings, class names, text). Unconventional page structures may result in linked instead of a specific role.
• Sub-actor availability — enrichment depends on three sub-actors running successfully. If any sub-actor is temporarily unavailable or has a bug, those fields will be empty.
• Timeout for large events — events with 500+ exhibitors and full enrichment may exceed the default 2-hour actor timeout. Increase the timeout in settings or split across runs.

Responsible Use

• This actor only accesses publicly visible event pages and company websites.
• Extracted contact information (emails, phone numbers, names) should be used in compliance with applicable data protection laws (GDPR, CAN-SPAM, CCPA).
• Do not use this actor for unsolicited bulk email campaigns without proper opt-in consent.
• Respect rate limits and terms of service for event platforms.
• See Apify's guide on web scraping legality for general guidance.

FAQ

What event platforms are supported? Any event website that renders sponsor, exhibitor, or speaker links in HTML. Tested on Eventbrite, Lu.ma, Sched, Bizzabo, Swapcard, and hundreds of custom conference microsites.

How does the actor classify companies as sponsor vs. speaker vs. exhibitor? It analyzes the HTML context around each external link — section headings, parent element class names, and nearby text. Keywords like "sponsor," "platinum," "exhibitor," "booth," "speaker," and "keynote" trigger the appropriate classification. Links without clear context are tagged as linked.

What happens if enrichment sub-actors fail? Each enrichment step runs independently. If one fails, the pipeline continues with the remaining steps. Failed steps produce empty fields in the output rather than crashing the entire run. The pipelineSteps array shows which steps completed.

Can I process password-protected or login-gated event pages? No. The actor crawls publicly accessible HTML pages only.

How many events can I process in a single run? No hard limit on input URLs. In practice, runs with 20–50 event URLs complete within the default 2-hour timeout. For larger batches, increase the actor timeout or split across multiple runs.

Does the actor find individual attendee data? No. The actor only extracts company-level data from public sponsor, exhibitor, and speaker listings.

What does the lead score mean? The score (0–100) and letter grade (A through F) come from the B2B Lead Qualifier sub-actor. It evaluates contact reachability, business legitimacy, online presence, website quality, and team transparency. Higher scores indicate companies that are easier to reach and more likely to be legitimate business targets.

Can I use the output with my CRM? Yes. Export as CSV or JSON and import directly into HubSpot, Salesforce, Pipedrive, or any CRM that accepts flat file imports. Or use the HubSpot Lead Pusher actor for automated CRM sync.

Integrations

• Zapier — trigger a Zap when the run finishes and push leads to HubSpot, Salesforce, Slack, or 5,000+ other apps
• Make — use the Apify module to watch for completed runs and route leads through multi-step workflows
• Google Sheets — export directly to a spreadsheet for team collaboration and filtering
• Apify API — call the actor programmatically and fetch results as JSON for custom integrations
• Webhooks — receive a POST notification with the dataset ID when the run completes