# Build a Notion vs Asana review battlecard

**Use case:** 

Collect recent and archived G2 reviews for two competing products in one run, with likes, dislikes, problems solved, reviewer role and company size on every row. Feed the result straight into a battlecard or a win/loss deck. Forty reviews per product keeps the test cheap; raise the cap when the shape looks right.

## Input

```json
{
  "productUrls": [
    "notion",
    "asana"
  ],
  "source": "auto",
  "maxReviewsPerProduct": 40,
  "minRating": 1,
  "maxRating": 5,
  "includeHistorical": true,
  "aiTasks": [],
  "aiProvider": "openai",
  "aiModel": "claude-haiku-4-5-20251001",
  "maxAiReviews": 40,
  "proxyConfiguration": {
    "useApifyProxy": true,
    "apifyProxyGroups": [
      "BUYPROXIES94952"
    ]
  }
}
```

## Output

```json
{
  "recordType": {
    "label": "Record type"
  },
  "productName": {
    "label": "Product"
  },
  "productSlug": {
    "label": "Product slug"
  },
  "rating": {
    "label": "Rating"
  },
  "reviewTitle": {
    "label": "Review title"
  },
  "reviewerName": {
    "label": "Reviewer"
  },
  "reviewerRole": {
    "label": "Reviewer role"
  },
  "reviewerCompanySize": {
    "label": "Company size"
  },
  "reviewerIndustry": {
    "label": "Industry"
  },
  "likeBest": {
    "label": "Likes"
  },
  "dislike": {
    "label": "Dislikes"
  },
  "problemsSolved": {
    "label": "Problems solved"
  },
  "publishedDate": {
    "label": "Published"
  },
  "sentiment": {
    "label": "Sentiment"
  },
  "reviewUrl": {
    "label": "Review URL"
  },
  "source": {
    "label": "Source"
  },
  "scrapedAt": {
    "label": "Scraped at"
  }
}
```

## About this Actor

This example demonstrates how to use [G2 Reviews Scraper: Ratings, Pros and Cons](https://apify.com/automation_craft/g2-reviews-scraper.md) with a specific input configuration. Visit the [Actor detail page](https://apify.com/automation_craft/g2-reviews-scraper.md) to learn more, explore other use cases, and run it yourself.


## How to integrate an Actor?

This Task's input is already configured above. Use it as-is rather than inventing a new one.

Do not guess an integration path. Every one of them is in the agent quickstart at https://apify.com/agents.md: the Apify MCP server, Agent Skills with the Apify CLI, the JavaScript and Python clients, the REST API, and the account-free path for an agent with no human to sign in. It also carries the rule on stating cost before the first paid run.

For full API examples (JavaScript, Python, CLI, MCP, OpenAPI), see this Task's Actor page: https://apify.com/automation_craft/g2-reviews-scraper.md

Each client library has reference documentation the quickstart does not restate: [JavaScript/TypeScript](https://docs.apify.com/api/client/js/docs.md) (`npm install apify-client`) and [Python](https://docs.apify.com/api/client/python/docs.md) (`pip install apify-client`).