How do I connect Make to Scrapernode?

Use Make's webhook trigger to receive data from Scrapernode. Copy the webhook URL from Make and paste it into Scrapernode's webhook settings for the scraper. Each completed job sends results automatically.

What PitchBook companies data fields are sent to Make?

All 19 output fields from the PitchBook Companies scraper are included: url, id, company_name, company_socials, year_founded, status, and more. The full payload is sent as structured JSON — no fields are filtered out.

Can I schedule recurring PitchBook scrapes to Make?

Yes. Use Make's scheduling features to trigger Scrapernode scrapes on a recurring basis via the REST API. You can also set up Make to process results as they arrive via webhooks.

How much does it cost to scrape PitchBook companies into Make?

Each companies record costs 2 credits. Credits start at $9 for 3,000 credits (Starter plan). The Make integration itself is included free — no additional charges for data delivery.

What happens if the Make delivery fails?

Your scraped data is always stored in Scrapernode regardless of the integration status. If delivery to Make fails, you can re-trigger the sync or download results manually as CSV or JSON from the job details page.

PitchBookMake

How to Scrape PitchBook Companies into Make

Extract companies data from PitchBook and pipe into Make automatically

Step-by-step guide

Choose the PitchBook Companies scraper

Navigate to the PitchBook Companies scraper in Scrapernode. Select "Fresh Scrape" for real-time data or "Quick Lookup" for pre-collected records. Each record costs 2 credits.

Set up your Make connection

Create a new Make scenario with a Webhook trigger module. Copy the webhook URL into Scrapernode's webhook settings. Use Make's built-in JSON parser to map scraper fields to downstream modules like "Create Spreadsheet Row" or "Send Email".

Provide your PitchBook input URLs

Paste the PitchBook URLs you want to scrape — one per line, or upload a CSV. Scrapernode accepts direct profile links, search result URLs, and content pages.

Launch the scraping job

Click "Start Extraction" to begin. Scrapernode handles proxy rotation, rate limiting, and anti-bot detection automatically. Jobs typically complete in under 60 seconds per batch.

Receive data in Make

When the job completes, Scrapernode sends the full results to your Make workflow. Each record includes 19 fields like url, id, company_name, company_socials. Route the data to any downstream app — CRMs, databases, email tools, and more.

Cost per record

2 credits

Output fields

19 fields

Destination

Make

Sample Output

Preview the data you'll receive — 5 sample records

Record 1 of 5

Url

sample_url

ACoAABcXYZ123

Company Name

Notion Labs, Inc.

Company Socials

sample_company_socials

Year Founded

1,000

Status

sample_status

Primary Industry

sample_primary_industry

Keywords

sample_keywords

Employees

Array [2]

Object {2}

name:"Lisa Su"

role:"CEO"

Object {2}

name:"Mark Papermaster"

role:"CTO"

Location

San Francisco, CA

Description

Enterprise-grade data pipeline platform with real-time processing and 99.99% uptime SLA.

Contact Information

sample_contact_information

Patents

Array [1]

Object {2}

title:"Distributed Payment Processing System"

date_issued:"2023"

Investors

Sequoia Capitala16zIndex Ventures

Funding Rounds

sample_funding_rounds

Total Funding

sample_total_funding

Valuation

sample_valuation

Website

https://stripe.com

Input Url

https://www.linkedin.com/in/sarahchen

Data Dictionary

19 fields returned per record

URL of the company in PitchBook (100.00% fill rate)

Unique identifier for the company (100.00% fill rate)

Name of the company (100.00% fill rate)

Social media links for the company (53.52% fill rate)

Sub-fields

linkTextSocial media URL

domainTextSocial media platform domain

Year the company was founded (76.20% fill rate)

Ownership status (Private, Public, etc.) (95.75% fill rate)

Primary industry of the company (94.41% fill rate)

Keywords describing the company (82.13% fill rate)

Number of employees (range or exact) (82.14% fill rate)

Headquarters location (91.23% fill rate)

Brief description of the company's offerings and purpose (99.17% fill rate)

Contact information for the company (100.00% fill rate)

Sub-fields

TypeTextType of contact (phone, email, etc.)

valueTextContact value

linkTextLink to the contact

Patents associated with the company (10.41% fill rate)

Sub-fields

typeTextPatent type

valueTextPatent number/value

linkTextLink to patent

Investors in the company (49.82% fill rate)

Sub-fields

nameTextInvestor name

urlTextInvestor PitchBook profile URL

typeTextInvestor type (VC, PE, Angel, etc.)

Funding rounds the company has received (44.31% fill rate)

Sub-fields

dateTextDate of the funding round

round_typeTextType of funding round (Seed, Series A, etc.)

amountNumberAmount raised in the round

currencyTextCurrency of the funding amount

Total funding raised by the company (44.31% fill rate)

Company valuation (12.34% fill rate)

Company official website (78.45% fill rate)

The URL that was entered when starting the scraping process (100.00% fill rate)

Frequently Asked Questions

Common questions about How to Scrape PitchBook Companies into Make

Ready to connect PitchBook data to Make?

Start extracting pitchbook companies data and pipe into Make in minutes.

Go to PitchBook Companies scraper Browse all integration guides

No code requiredAuto-delivery to Make19 data fields