We extract schedules, speaker directories, sponsor tiers, and ticketing data from public Hopin events. Delivered as clean JSON, CSV, or Parquet to S3, BigQuery, or Snowflake on your cadence.
Structured, schema-consistent data across all major object types — delivered clean, typed, and ready to query.
Complete list of extractable fields for Event Metadata objects from hopin.com. All fields typed and schema-versioned.
"event_id": "evt_98421abc", "name": "Global SaaS Summit 2026", "organiser_name": "TechConnect Media", "start_time": "2026-09-14T09:00:00Z", "timezone": "America/New_York", "format_type": "Virtual", "status": "upcoming"
| # | event_id | name | organiser_name | start_time | end_time | timezone |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Schedules & Sessions objects from hopin.com. All fields typed and schema-versioned.
"session_id": "sess_4021", "event_id": "evt_98421abc", "title": "Scaling Kubernetes in Production", "start_time": "2026-09-14T10:30:00Z", "stage_name": "Main Stage", "session_format": "Keynote", "speaker_ids": "['spk_881', 'spk_882']"
| # | session_id | event_id | title | start_time | end_time | stage_name |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Speakers objects from hopin.com. All fields typed and schema-versioned.
"speaker_id": "spk_881", "name": "Jane Doe", "headline": "VP Engineering at CloudScale", "company": "CloudScale", "role": "VP Engineering", "linkedin_url": "https://linkedin.com/in/janedoe-example", "event_id": "evt_98421abc"
| # | speaker_id | event_id | name | headline | bio | company |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Sponsors & Exhibitors objects from hopin.com. All fields typed and schema-versioned.
"sponsor_id": "spn_102", "name": "DataFlirt", "tier": "Platinum", "website": "https://dataflirt.com", "booth_size": "Large", "contact_email": "hello@dataflirt.com", "event_id": "evt_98421abc"
| # | sponsor_id | event_id | name | tier | booth_size | description |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Tickets & Pricing objects from hopin.com. All fields typed and schema-versioned.
"ticket_id": "tkt_551", "name": "Early Bird VIP", "price": 299.0, "currency": "USD", "availability": "sold_out", "sales_end": "2026-08-01T23:59:59Z", "event_id": "evt_98421abc"
| # | ticket_id | event_id | name | price | currency | availability |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Our Hopin scraper targets every public module of the virtual venue: reception metadata, stage schedules, session details, networking parameters, and expo booth directories.
Extract core event details including start times, timezones, organiser identities, format types, and descriptive copy.
Map complex multi-track agendas. Capture session start times, stage assignments, and format types across the entire event duration.
Extract speaker names, professional headlines, company affiliations, biographies, and social links from event rosters.
Capture exhibitor details, sponsorship tiers, booth descriptions, outbound links, and promotional offers.
Monitor pricing tiers, currency, availability status, and sales windows for public registration pages.
All session times and event boundaries are parsed and normalised to UTC, eliminating timezone conversion errors in your warehouse.
Virtual event schedules change frequently. We run continuous diffs leading up to the event to capture late additions and cancellations.
Track specific organisers to capture their entire portfolio of upcoming and past public events automatically.
Extract thousands of speaker profiles and session details concurrently without hitting Hopin application rate limits.
Brief in. Clean data out.
Provide event URLs, organiser profiles, or keyword sets. We design the extraction schema together.
We configure Playwright crawlers, state management, and API interception for Hopin's frontend.
Schema validation, timezone normalisation checks, and schedule completeness testing before full launch.
JSON, CSV, or Parquet pushed to your S3 bucket, BigQuery dataset, or Snowflake stage on agreed cadence.
Hopin is a heavy single page application built for real time interaction. Standard HTTP clients fail. We run managed browser infrastructure to capture hydrated state.
Hopin relies heavily on client-side rendering. We run full Playwright browser sessions to execute JavaScript, hydrate the DOM, and extract data that headless HTTP clients miss entirely.
Instead of parsing complex DOM structures for schedules, we intercept the underlying GraphQL and REST network requests, extracting clean, structured JSON directly from the wire.
Major conferences feature hundreds of speakers and sessions. We manage complex pagination states and infinite scrolls to ensure zero record truncation.
Event times are displayed in the user's local timezone. We intercept the raw UNIX timestamps from the application state and normalise all outputs to UTC for reliable downstream querying.
We distribute requests across residential proxy pools to avoid IP bans and rate limits when extracting large volumes of speaker and sponsor profiles concurrently.
Sales teams extract sponsor directories and speaker lists to build highly targeted account lists based on event participation.
Organisers track rival events to monitor ticket pricing strategies, speaker line-ups, and sponsorship tiers.
Analysts parse session topics and descriptions at scale to identify emerging themes and technologies in specific verticals.
Recruiters source high-profile speakers and panellists based on their participation in niche technical or leadership events.
Marketing teams analyse webinar schedules to identify saturated topics and find whitespace for their own content strategies.
Brands evaluate event scale, co-sponsors, and tier pricing to determine the ROI of exhibiting at specific virtual conferences.
"Hopin hosts the most concentrated directory of B2B speakers, sponsors, and industry schedules, but the data is locked inside ephemeral virtual venues."
Extracting data from Hopin requires executing heavy JavaScript payloads and managing complex pagination across session tracks. DataFlirt absorbs that complexity. We handle the rendering, state management, and schema normalisation so your engineers can focus on analysis.
Everything supported by our hopin.com scraper — rendered SPA elements, auth walls, rate-limit evasion and beyond.
Open-source tooling on proven cloud infra — no vendor lock-in, full observability.
We use Playwright to execute full browser sessions, handling Hopin's heavy client-side rendering and dynamic routing.
Instead of brittle DOM parsing, our middleware intercepts Hopin's internal API responses, extracting clean data directly from the network layer.
Pipelines run on Kubernetes. Airflow handles scheduling and dependency management. All state is stored in managed Postgres.
Data delivered to where your team already works — no new tooling required.
About hopin.com scraping, legality, and pipeline operations.
Ask us directly →Scraping publicly available event metadata, schedules, and speaker directories is generally permissible. DataFlirt targets only public, non-authenticated data. We do not extract private attendee lists, bypass registration walls, or extract gated content. Clients should review Hopin's ToS and consult legal counsel for specific use cases.
No. We only extract data that is publicly visible on the event registration and reception pages without requiring authentication or payment.
Hopin displays times based on the user's browser locale or the event's configured timezone. We intercept the raw UNIX timestamps from the application state and normalise all output to UTC.
Yes. We can configure continuous pipelines that poll the event schedule daily or hourly, emitting diffs when speakers are added, sessions are moved, or stages change.
Yes, provided the expo directory is public. We extract sponsor names, tier levels, booth descriptions, and outbound website links.
Our smallest packages start at a defined list of target organisers or a specific volume of event URLs with weekly delivery. Contact us with your use case for a scoped quote.
Yes. We provide a sample run of up to 50 public events as part of the pre-engagement scoping process so you can validate schema fit and data quality.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a one off scrape of a major tech conference or a continuous feed of B2B webinars, we scope, build, and operate the pipeline. Tell us what you need.
