Research & Web Scraping

Databases know what a company is. They rarely know what it is doing — whether they just changed pricing, whether their careers page mentions a new region, whether their docs list your competitor as an integration.

That gap is what research automation closes. This course covers both ways Sync GTM closes it: scraping pages directly, and pointing an AI agent at a question and letting it go find the answer.

About this course

Nine lessons in three blocks: scraping (deterministic, cheap, brittle), agents (flexible, more expensive, needs prompting), and scale (what changes when the same run goes from 50 rows to 5,000).

The two halves fail differently, and knowing which to reach for is most of the skill. A scraper returns nothing when a page changes; an agent returns something confident and wrong. Every lesson states which failure it is exposed to.

Who it is for. Anyone whose research today is a browser tab and a copy-paste: SDRs building a personalization layer, RevOps enriching an account list, founders sizing a segment. Works from the app or from an MCP client — the lessons show both surfaces.

What it costs. Around 80 credits at the suggested volumes. Scraping is the cheap half; agent calls carry the cost, which is why lesson 09 exists.

Skills you will gain

• Decide between a scraper and an agent for a given question — they fail differently
• Pull named facts off a specific URL, per row, without writing a selector by hand
• Recover emails and phones from a site when contact enrichment came up empty
• Write a research prompt that returns the same shape of answer every time
• Force free text into a value you can filter, sort and score on
• Build a competitor teardown from ads, traffic, keywords and posts in one pass
• Keep a research run inside budget at 5,000 rows instead of 50
• Handle the rows where the answer genuinely is not out there

In this course

Scraping

Deterministic extraction from pages you can name. Cheap, exact, and blind to anything outside the URL you gave it.

• 01What research automation actually replacesA clear rule for what to automate and what to leave manual7 min
• 02Scraping basics and limitsUnderstanding what a scraper can and cannot reach, including the legal boundaries8 min
• 03Scraping a single pageNamed facts pulled off a specific URL per row9 min
• 04Pulling emails and phones from a siteContact details recovered where enrichment came up empty9 min

Research agents

Open questions, answered per row. More expensive, far more flexible, and only as good as the prompt.

• 05Research agentsAn agent answering an open question per row11 min
• 06Writing research promptsPrompts that return consistent, checkable answers12 min
• 07Structuring the outputFree text turned into a field you can filter on10 min

Applied and at scale

• 08Competitor teardownOne competitor's ads, traffic, keywords and posts in one briefMCP: b2b_ads_search → meta_ads_analysis → semrush_insights → similarweb_insights → linkedin_page_posts · ~29 credits for 5 competitors11 min
• 09Research at scale and what it costsA run that stays inside budget at volume8 min

What you will have built

Two things that outlive the course:

• A research column on your own table that answers one specific, current question per account and returns it in a shape you can filter on — not a paragraph a human has to read.
• A competitor brief built from five sources in one run, repeatable against any competitor you name.

Both plug straight into Automated Outbound, where the research answer becomes the opening line.

Before you start

• A table with rows in it. Any rows — 20 companies is plenty. SyncGTM 101 lesson 06 builds one if you have none.
• A question you actually want answered per account. “Do they sell to enterprise?” beats “tell me about them” by a wide margin, and lesson 06 explains why.
• Optionally an MCP client, if you want to run lesson 08 by chat rather than by column.

The rule this course keeps coming back to

Research before you enrich, and filter between them. Research is cheap relative to contact enrichment. If a research step can disqualify a third of your rows, running it first means you never buy emails for those rows at all. Every lesson that spends credits states where the filter goes.

Reference behind this course

• Web Scrapers — the no-code extraction actions
• AI Agents — how research agents are configured
• How enrichment works — why filtering first saves money

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