Crawl / Market Intelligence Corpora

Create a research corpus from the sites that define your market

Crawl approved company and industry sites to give analysts a comparable body of source-linked material for recurring research.

  • Select the companies and research scope
  • Crawl relevant public site sections
  • Normalize coverage and organize the research corpus

Scope

Define the website boundary

Recursive

Collect connected pages

Formats

Choose supported outputs

Sources

Keep page-level provenance

Who uses Market Intelligence Corpora

Crawl approved company and industry sites to give analysts a comparable body of source-linked material for recurring research.

01

Strategy analysts

Define the business question and review the collected evidence.

02

Competitive intelligence

Use a repeatable process to compare the observations that matter.

03

Industry research teams

Connect reliable inputs to the product or research workflow.

04

Integration owners

Map the source output into your existing application and validate required fields.

05

Workflow operators

Monitor exceptions, maintain collection context and review incomplete runs.

Why this workflow breaks at scale

Design around the failure modes that affect a usable business outcome.

Failure 01

The context gets lost

Large sites can dominate a corpus while smaller competitors are underrepresented. Track coverage by company and section before comparison.

Keep comparable observations
Failure 02

A run ends without a usable result

A completed crawl can still omit important paths or include irrelevant ones. Reconcile discovered pages with scope and coverage expectations.

Validate the actual outcome
Failure 03

The next team cannot verify the result

Preserve source context and reviewable evidence alongside the result. Define who handles incomplete records before production collection.

Make the handoff traceable

The data your workflow can use

Keep the collection layer and the normalized business record clearly defined.

company
Observed organization name, normalized by your application.
source_url
Source or destination reference retained for traceability.
topic
Topic assigned by your content organization process.
capture_date
Relevant timestamp or date; retain the source timezone where applicable.

NORMALIZED RECORD · ILLUSTRATIVE

{
  "company": "Example Company",
  "source_url": "https://example.com/public-source",
  "topic": "Getting started",
  "capture_date": "2026-10-08T08:00:00Z"
}

Suggested downstream record, not a literal Scrapeless API response. Field extraction and normalization belong in your application.

Recursive website collection with supported content formats such as Markdown, HTML, links and screenshots.

Example in practice. Assemble public product and documentation content for a fixed enterprise software cohort.

How this workflow runs

A focused sequence from approved input to a verified result.

  1. 01

    Select the companies and research scope

    Start with: A company cohort, topic scope and collection window. Define the minimum usable result before collection.

  2. 02

    Crawl relevant public site sections

    Recursive website collection with supported content formats such as Markdown, HTML, links and screenshots. Record failures and partial results separately.

  3. 03

    Normalize coverage and organize the research corpus

    In-scope coverage, duplicate rate and retained document quality. Retain evidence for records that enter the next stage.

Built for the way your team works

Product capabilities support the workflow; your application defines what success means.

  • Seed → scope → pages

    Collect within a defined scope

    Use recursive collection for selected website areas. Start with a small scope and review discovered pages before expanding the crawl.

  • Markdown · HTML · links

    Choose useful output formats

    Crawl supports content formats including Markdown, HTML, links and screenshots. Select the formats required by your consuming application.

  • Page → document → source

    Keep source identity

    Associate each retained document with its URL and capture context. Your pipeline can then maintain versioning and source-linked citations.

  • Filter → deduplicate → publish

    Prepare content downstream

    Apply your own deduplication, content filters and quality checks before indexing or training. Collecting a page is the beginning of dataset preparation.

Plan the cost of your workflow

Crawl documentation describes browser runtime and proxy traffic as cost drivers. Scope, rendering needs and output formats affect consumption.

Pilot

Validate one workflow

Run a representative source sample and inspect both usable results and exceptions. Agree on acceptance criteria before expanding.

Try for Free

Production

Measure real consumption

In-scope coverage, duplicate rate and retained document quality.

Review pricing

Scale

Scope the next stage

Bring your workload mix, operating window and observed consumption to discuss the setup that fits your requirements.

These are workload stages, not named subscription plans. Current rates and account limits apply.

Choose how to run the workflow

Compare responsibilities and operating effort using your own representative workload.

Workflow responsibility

With Crawl

Self-managed stack

Manual process

Execution

Scoped website collection

Your team runs and maintains the execution layer.

An operator repeats each collection or browser step.

Business rules

Source permissions, scope, content filtering, versioning, indexing and downstream model use.

Implemented in your application.

Applied by the researcher or operator.

Acceptance

Keep outcome and content checks in your workflow.

Build validation and exception handling.

Review the captured evidence.

Cost planning

Measure product consumption plus downstream processing.

Measure infrastructure and maintenance effort.

Account for time spent per completed task.

Connect it to the stack you already run

Keep business logic and analysis close to the systems that consume the result.

  • Python

  • Node.js

  • Go

  • Your search or RAG pipeline

Source permissions, scope, content filtering, versioning, indexing and downstream model use. Open the product documentation for current setup and supported options.

Explore more Crawl workflows

Related workflows using the same product, each with its own inputs and acceptance criteria.

Questions teams ask before they build

Scope the first run with clear expectations.

What do we need to get started?

A company cohort, topic scope and collection window. Begin with a representative sample and agree on the acceptance criteria before increasing volume.

What does Crawl provide?

Recursive website collection with supported content formats such as Markdown, HTML, links and screenshots. Page-level content and source context for your corpus or knowledge pipeline.

Which parts do we build ourselves?

Source permissions, scope, content filtering, versioning, indexing and downstream model use.

What can make this workflow misleading?

Large sites can dominate a corpus while smaller competitors are underrepresented. Track coverage by company and section before comparison.

What boundaries should we plan around?

Entity mapping, topic classification and competitive interpretation belong in your analysis layer.

How should we evaluate a pilot?

In-scope coverage, duplicate rate and retained document quality. Review a sample of accepted records and exceptions before deciding whether to expand.

Put Crawl to work for your team

Bring your sources, expected crawl jobs and acceptance criteria. Start with a focused pilot, then expand on evidence.

Website Crawling for Market Intelligence | Scrapeless