How to Extract Sponsors and Exhibitors From Conference Websites

If you sell anything to B2B buyers, the sponsor and exhibitor lists for upcoming conferences are the single highest-signal prospecting list you can get. Companies paying $5,000 to $50,000 for a booth have an active budget, a named vertical, and a reason to take a call in the month before the show. The pre-event window is worth more than the show itself if you run outreach right.

The fastest general-purpose method is to point a cloud browser agent at the conference's partners or sponsors URL with a tier-aware extraction prompt, and let it emit rows of name, domain, tier, and category. Per-platform scrapers work for mid-tier shows on Map Your Show or 10times; manual copy-paste works for a one-off. Below is the full walkthrough, using Web Summit's own partners page as the example (partner roster current as of April 2026).

The problem is that conference organizers publish these lists as browsable web pages, not as CSVs. There's no export button, no public API, and the shape of the page changes every year. Web Summit is the hardest-mode version of this class of page, which makes it a useful teacher.

What Web Summit's partners page actually looks like

Web Summit Lisbon 2026 runs 9-12 November at the MEO Arena. The 2022 event drew around 70,000 attendees; the partner roster for 2026 runs to roughly fifty named companies. You can load the page in your browser right now and count them.

Here is a trimmed sample of what the page renders, category by category:

AI & Machine Learning: IBM, Groq, Qualcomm, Alibaba Cloud, Plaud Inc., Globant, Toptal, Artificial Superintelligence (ASI) Alliance. SaaS: Replit, LinkedIn, Datadog, Atlassian, 1Password, Vercel, Pluralsight, ManageEngine, Contentful, SendPulse. Fintech & Financial Services: Visa, Sumup, Itaú Unibanco S.A., Qatar Insurance. Telecommunications & IT: Huawei, Akamai Technologies, VOIS, Foundever, Ookla, Concentrix. [...] Venture Capital/Private Equity: PitchBook.

Every one of those names is important. So is the category label above it - "AI & Machine Learning" vs "SaaS" vs "Fintech" tells you how Web Summit sold the sponsorship and what vertical the sponsor self-identifies as. A flat list of fifty company names without the tier/category context is half as useful for prospecting.

The page also has the design choices that break naive scrapers: the logos are images without alt text on some tiers, the categories are H2s rather than a structured data attribute, and the partner blocks render client-side. View-source on the page returns almost nothing; the content arrives after the browser runs the JavaScript.

How to extract a conference sponsor or exhibitor list: three approaches

I'll take the three live options in the order a reasonable operator encounters them.

Manual copy-paste. Open the page, select text, paste into a sheet, walk down the rows retyping tier labels. For Web Summit's ~50 partners this takes maybe 25 minutes. For an event with 400 exhibitors, the cost is real:

"Manual copying and pasting into spreadsheets consumes 4-8 hours per event while introducing errors and formatting inconsistencies." - Sunder, MarketBetter, February 2026

That's the honest baseline - it works, it scales terribly, and it is what most sales teams actually do the week before a conference. The error rate is real because the logos-as-images tiers force you to read the alt text (or worse, infer the name from the image).

Per-platform scrapers. A meaningful share of mid-tier conferences run on one of four or five white-label event platforms: Map Your Show, 10times, Xporience, Cvent. For those, there are ready-made extractors on Apify and similar marketplaces. Point them at the URL, get a CSV, move on. The catch (and it is a big one) is that the top-tier shows - Web Summit, CES, Dreamforce, Money20/20 - don't use off-the-shelf platforms. They roll their own sites, and the Apify actor for "Map Your Show" silently returns zero rows when pointed at one. You can't tell whether a conference is on a supported platform until you try, and the discovery step is its own small project.

Browser-agent extraction with a tier-aware prompt. This is what we do, and it's the only approach that works uniformly across the long tail. A cloud browser agent visits the partners page, waits for JavaScript to render, and extracts structured rows using a prompt that names the exact columns you want: name, domain, tier, category. The agent does the work of reading the page visually (including logos) and emits a CSV. For Web Summit's page, one agent run produces fifty rows with tier labels intact, and it costs cents, not hundreds of dollars.

The last approach is the one worth spending the rest of the post on, because it generalizes.

The pattern: discovery step, then per-page extraction

At Leadex we split conference extraction into two plan steps. The first step is discovery: given "web3 conferences in Q3 2026" or just "Web Summit partners page," find the URL that actually renders the list. The second step is extraction: open that URL and emit rows.

Discovery uses a semantic web-search tool with the company or news category and a natural-language query. Extraction is a cloud browser agent given a single atomic task: visit the URL, extract sponsors, return name/domain/tier/category. The two-step split is not cosmetic - it's the difference between a brittle site-specific scraper and a pattern that handles any conference page.

The subtlety is the loop. If the user's goal is "sponsors across all 2026 web3 conferences in Europe," discovery returns a list of conference URLs and the extraction step runs once per URL. The task prompt is written for a single event ("visit this conference site and extract the sponsor list with tier labels"), and the orchestrator chunks the URL list and iterates. Rows are merged, deduplicated by domain, and the tier/category labels are preserved as columns.

Here is the skeleton of what the plan looks like in practice:

Step 1 (search): Find official 2026 web3 conference websites in Europe. Returns: conference name, URL, date, city.

Step 2 (browser-agent, loop): For each conference URL, visit the sponsors/partners page and extract every sponsor. For each sponsor, collect company name, domain, sponsorship tier (if shown), and category/vertical (if shown). Emit one row per sponsor.

That is the whole trick. It looks trivial, and it is - once you accept that the right abstraction is "a generalist agent with a specific prompt," not "a scraper for this site."

Why sponsor-page scrapers fail (and how to handle each case)

A few things that aren't obvious until you've run this pattern across a hundred conferences:

Tier labels are the hard part, not company names. Every agent will extract company names reliably. Fewer will consistently pick up the category heading above a block of logos and propagate it onto each row. Your prompt has to say "the category/tier is the H2 or section label above the logo block" explicitly, or you'll get fifty rows with blank tier columns.

Pagination and "load more" buttons. Large exhibitor lists (1,400+ for Web Summit, 900 startups for the Pitch competition in 2019) paginate. The agent needs instructions to scroll, click "load more" until the count stops growing, and only then extract. Without that, you get the first page of 20 and think you're done.

Logos as images without alt text. Some pages render the sponsor name only as an image. A text-only scraper returns nothing. The agent reads the image visually, which mostly works but is not free - expect a small error rate and plan to spot-check.

The page you're told to scrape is not the page with the data. Conferences often have a separate "exhibitors" page vs "sponsors" page vs "partners" page, and sometimes a third page lists only the keynote tier. Discovery step should pull all of them; extraction should run on each.

Where the point-tools break down

Vendelux and Landbase sell enriched attendee lists for the big conferences. They're good products, but they cover a bounded set of shows and they're priced per lookup. If you want sponsors for regional events, industry-specific summits, or anything below the top hundred conferences, you're back to extracting it yourself.

MarketBetter's free tool and Apify's platform scrapers are closer to the right shape - general-purpose extractors that take a URL - but they're each coupled to specific rendering patterns. The day Web Summit changes its CSS class names, the Apify actor needs a developer update; the day the event platform switches from Map Your Show to Xporience, the actor returns zero rows silently. A browser-agent extraction pattern doesn't care about CSS classes or platform choice - it reads the page the way you do.

None of this is complicated once you see it. The point is that the right unit of abstraction is the pattern (discover conference URLs, extract tier-aware rows per URL), not the scraper (a custom extractor for each site). Once you've written the prompt once, every new conference is a URL change, not a code change.

If you want this running end-to-end without writing the plumbing, that is exactly what Leadex does - chat-driven lead research with a plan-then-execute flow. Type "get me all sponsors from Web Summit Lisbon 2026 with their vertical tier," approve the plan, get a CSV. The piece above is the shape of the plan it will run.