nvNeuralVerge
Company intelligence

G2 Product Data API — Ratings, Reviews & Pricing

Send a G2 product URL and this source returns the profile as data: product information, rating, reviews, discussions, pricing and the feature breakdown.

You send
A G2 product URL
You get back
Rating, reviews, features, pricing and discussions
Coverage
Software products with a public profile.
Price
5 pts$5 per 1,000
Charged only when a profile resolves. A product that cannot be found is not billed.
Comparison

Ways to get this data

Three approaches teams use today, and where each one runs into trouble.

ApproachWhat it takesCostTrade-off
Reading profiles by handOpen the page and scrollFree, and slowFine for one product, useless across a category
Building a scraperWrite it, host it, and repair it when the layout movesEngineering timeA maintenance commitment for something that is not your product
NeuralVergeOne request per product$5 per 1,000, misses not billedReturns what the profile publishes — a snapshot of opinion, not a market truth
Response

What you get back

Every field the response returns.

FieldTypeDescription
product_informationobjectProduct name, description and the company behind it.
ratingobjectOverall star rating and the total number of reviews.
reviewsarrayIndividual reviews with title, content, author and the rating given.
discussionsarrayDiscussion threads with title, author and reply count.
pricingarrayEach plan with its name, price and the features it includes.
featuresarrayKey features with a short description of each.
One response envelope

Every source answers in the same shape: a session id, a readable human summary, a structured machine object and the points the call consumed. Learn it once and it holds across every source in the catalog.

Integration

How to run it

The same lookup works from the app, the API, or as a tool an agent can call mid-task.

A JSON schema passed as extract_schema_json pins the response shape, so the same fields come back on every call. The Get API Code button in the app gives you the complete command with the schema already filled in.

curl -X POST https://api.neuralverge.ai/functions/v1/run-extract \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "url": "https://www.g2.com/products/example",
    "instructions": "Extract data from G2 product profile",
    "settings": {
      "country_code": "us",
      "extract_schema_json": "{ ... }"
    }
  }'
Use cases

What teams use it for

Where this field shows up in an actual workflow.

Competitive intelligence

Track how a competitor's rating and complaints move over time.

Voice-of-customer research

Mine the exact language buyers use about problems you solve.

Positioning and messaging

Find the gap between what a category promises and what its reviews say.

Win-loss context

Understand what buyers liked about the product they chose instead.

Coverage & limits

Coverage, freshness and limits

What this source covers, how fresh it is, and where it stops.

Coverage

Software products with a public profile.

Freshness

Read at request time.

Handling

This source returns publicly visible product information, stamped with the URL it was read from and a session id you can trace.

What it will not do
  • Reviews are self-selected and skew towards strong opinions in both directions.
  • Vendors influence how many reviews they collect, so volume is not a neutral signal.
  • Products with few reviews return thin profiles.
FAQ

Questions, answered

It returns the reviews section of the profile as the schema defines it. If you need every review rather than a profile-level view, run it against the review listing rather than the product page.

Related

Related sources

Try g2 on your own data

One request format across every source in the catalog.

Get started