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 G2 software reviews data fields are sent to Make?

All 19 output fields from the G2 Software Reviews scraper are included: review_id, author_id, author, position, company_size, stars, and more. The full payload is sent as structured JSON — no fields are filtered out.

Can I schedule recurring G2 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 G2 software reviews into Make?

Each software reviews record costs 1 credit. 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.

G2Make

How to Scrape G2 Software Reviews into Make

Extract software reviews data from G2 and pipe into Make automatically

Step-by-step guide

Choose the G2 Software Reviews scraper

Navigate to the G2 Software Reviews scraper in Scrapernode. Select "Fresh Scrape" for real-time data or "Quick Lookup" for pre-collected records. Each record costs 1 credit.

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 G2 input URLs

Paste the G2 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 review_id, author_id, author, position. Route the data to any downstream app — CRMs, databases, email tools, and more.

Cost per record

1 credit

Output fields

19 fields

Destination

Make

Sample Output

Preview the data you'll receive — 5 sample records

Record 1 of 5

Review Id

1,000

Author Id

1,000

Author

Sarah Chen

Position

Software Engineer III

Company Size

sample_company_size

Stars

13,105

Date

2025-12-15

Title

How We Scaled to 1M Users

Likes

34,108

Dislikes

sample_dislikes

Product Id

1,000

Product Name

sample_product_name

Product Url

sample_product_url

Product Rating

1,000

Product Reviews Count

1,000

Product Category

sample_product_category

Review Url

sample_review_url

Verified Current User

Yes

Input Url

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

Data Dictionary

19 fields returned per record

The unique identifier for the review (100.00% fill rate)

The unique identifier for the review author (55.66% fill rate)

The name of the author who wrote the review (93.41% fill rate)

The position or role of the author (67.81% fill rate)

The size or type of the author's company (86.31% fill rate)

The star rating given in the review (1-5) (99.35% fill rate)

The date when the review was posted (100.00% fill rate)

The title or headline of the review (99.35% fill rate)

What the reviewer liked about the product (99.35% fill rate)

What the reviewer disliked about the product (89.22% fill rate)

Unique identifier for the reviewed product (100.00% fill rate)

Name of the reviewed software product (100.00% fill rate)

URL of the product page on G2 (100.00% fill rate)

Overall product rating on G2 (100.00% fill rate)

Total number of reviews for the product (100.00% fill rate)

Software category of the product (100.00% fill rate)

Direct URL to the review (100.00% fill rate)

Whether the reviewer is a verified current user (90.12% 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 G2 Software Reviews into Make

Ready to connect G2 data to Make?

Start extracting g2 software reviews data and pipe into Make in minutes.

Go to G2 Software Reviews scraper Browse all integration guides

No code requiredAuto-delivery to Make19 data fields