Conference Speaker Scraper
Extract speaker names, titles, companies, and bios from conference websites. Supports direct HTML scraping and Apify web scraper fallback for JS-heavy sites. Use for pre-event research and outreach targeting.
by Athina AInpx gooseworks install --all # then, in Claude Code, Cursor, or Codex: /gooseworks use the conference-speaker-scraper skill
Conference Speaker Scraper
Extract speaker names, titles, companies, and bios from conference website /speakers pages. Supports direct HTML scraping with multiple extraction strategies, plus Apify fallback for JS-heavy sites.
Quick Start
No API key needed for direct scraping mode.
# Scrape speakers from a conference page
python3 skills/conference-speaker-scraper/scripts/scrape_speakers.py \
--url "https://example.com/speakers"
# Use Apify for JS-heavy sites
python3 skills/conference-speaker-scraper/scripts/scrape_speakers.py \
--url "https://example.com/speakers" --mode apify
# Custom conference name (otherwise inferred from URL)
python3 skills/conference-speaker-scraper/scripts/scrape_speakers.py \
--url "https://example.com/speakers" --conference "Sage Future 2026"
# Output formats
python3 skills/conference-speaker-scraper/scripts/scrape_speakers.py --url URL --output json # default
python3 skills/conference-speaker-scraper/scripts/scrape_speakers.py --url URL --output csv
python3 skills/conference-speaker-scraper/scripts/scrape_speakers.py --url URL --output summaryHow It Works
Direct Mode (default)
Fetches the page HTML and tries multiple extraction strategies in order, using whichever returns the most results:
- Strategy A -- CSS class hints: Looks for speaker cards with class names containing "speaker", "presenter", "faculty", "panelist", "team-member"
- Strategy B -- Heading + paragraph patterns: Looks for repeated
<h2>/<h3>+<p>structures - Strategy C -- JSON-LD structured data: Checks for
<script type="application/ld+json">with speaker data - Strategy D -- Platform embeds: Detects Sched.com/Sessionize patterns used by many conferences
Apify Mode
Uses apify/cheerio-scraper actor with a custom page function that targets common speaker card selectors. Standard POST/poll/GET dataset pattern.
CLI Reference
| Flag | Default | Description |
|---|---|---|
--url | required | Conference speakers page URL |
--conference | inferred | Conference name (otherwise inferred from URL domain) |
--mode | direct | direct (HTML scraping) or apify (Apify cheerio scraper) |
--output | json | Output format: json, csv, or summary |
--token | env var | Apify token (only needed for apify mode) |
--timeout | 300 | Max seconds for Apify run |
Output Schema
{
"name": "Jane Smith",
"title": "VP of Finance",
"company": "Acme Corp",
"bio": "Jane leads the finance transformation at...",
"linkedin_url": "https://linkedin.com/in/janesmith",
"image_url": "https://...",
"conference": "Sage Future 2026",
"source_url": "https://sagefuture2026.com/speakers"
}Cost
- Direct mode: Free (no API, no tokens)
- Apify mode: Uses
apify/cheerio-scraper-- minimal Apify credits
Testing Notes
HTML scraping is inherently fragile across conference sites. The multi-strategy approach maximizes coverage, but JS-heavy sites will require Apify mode. When direct scraping returns 0 results, try --mode apify.
What's included
apify/cheerio-scraper -- minimal Apify creditsTrend Discovery
Discover rising category conversations, formats, sounds, questions, and creator patterns across social platforms, then separate durable demand signals from short-lived noise.
Transcript Intelligence
Turn TikTok, Instagram, YouTube, Facebook, X, LinkedIn, Reddit, or Rumble transcripts into timestamped hooks, claims, objections, proof, calls to action, sponsorship signals, and reusable content atoms. Use directly for transcript analysis or as support for creator, competitor, trend, demand, and repurposing work.
Social Listening Brief
Produce a decision-ready brief of current brand, product, category, and competitor conversations across social platforms, including sentiment drivers, questions, risks, and growth opportunities.