# AI pain-point analysis of Trustpilot reviews

**Use case:** 

Adds an AI report per company: top complaint themes with severity scores, missing features users keep asking for, quick wins and overall sentiment.

## Input

```json
{
  "startUrls": [],
  "searchTerms": [
    "nike"
  ],
  "reviewInsights": false,
  "painPointAnalysis": true,
  "enrichEmails": false,
  "qualifyByPayment": false,
  "scrapeAllReviews": true,
  "filterStars": [],
  "sampling": "balanced",
  "filterLanguages": [],
  "filterDateRange": "all",
  "filterVerifiedOnly": false,
  "filterRepliesOnly": false,
  "filterCountries": [],
  "sortBy": "auto",
  "expandRegionalDomains": false,
  "strictNameMatch": false,
  "splitDatasets": false,
  "flattenCompanyData": false,
  "emitInputStatus": true,
  "includeCompanyDetails": false,
  "includeStats": false,
  "includeTransparency": false,
  "includeCompanyAdditionalFields": false,
  "maxItems": 100,
  "maxConcurrency": 10,
  "minConcurrency": 1,
  "maxRequestRetries": 100
}
```

## Output

```json
{
  "rowType": {
    "label": "Row type",
    "format": "text"
  },
  "company": {
    "label": "Company",
    "format": "text"
  },
  "totalAnalyzed": {
    "label": "Reviews analysed",
    "format": "number"
  },
  "reviewsAnalyzed": {
    "label": "Reviews analysed (AI)",
    "format": "number"
  },
  "averageRating": {
    "label": "Average rating",
    "format": "number"
  },
  "ratingBreakdown": {
    "label": "Rating breakdown",
    "format": "object"
  },
  "sentimentSplit": {
    "label": "Sentiment split",
    "format": "object"
  },
  "overallSentiment": {
    "label": "Overall sentiment",
    "format": "text"
  },
  "topThemes": {
    "label": "Top themes",
    "format": "array"
  },
  "topComplaintTerms": {
    "label": "Top complaint terms",
    "format": "array"
  },
  "missingFeatures": {
    "label": "Missing features",
    "format": "array"
  },
  "quickWins": {
    "label": "Quick wins",
    "format": "array"
  },
  "requests": {
    "label": "Requests",
    "format": "array"
  },
  "summary": {
    "label": "Summary",
    "format": "text"
  },
  "generatedAt": {
    "label": "Generated at",
    "format": "date"
  }
}
```

## About this Actor

This example demonstrates how to use [Trustpilot All Reviews Scraper 💰$0.5+ · No Cap · Incremental](https://apify.com/memo23/trustpilot-scraper-ppe.md) with a specific input configuration. Visit the [Actor detail page](https://apify.com/memo23/trustpilot-scraper-ppe.md) to learn more, explore other use cases, and run it yourself.


## How to integrate an Actor?

If asked about integration, you help developers integrate Actors into their projects.
You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready.
This Task's input is already configured above — use it as-is rather than inventing a new one.

- **AI agents and MCP clients** — the [Apify MCP server](https://docs.apify.com/integrations/mcp.md) at `https://mcp.apify.com` (remote, streamable HTTP, OAuth on first use).
- **Agentic workflows and local Actor development** — [Agent Skills](https://apify.com/.well-known/agent-skills/index.json) with the [Apify CLI](https://docs.apify.com/cli/docs.md): `npm install -g apify-cli`, then `apify login`.
- **JavaScript/TypeScript projects** — the official [JS/TS client](https://docs.apify.com/api/client/js/docs.md): `npm install apify-client`.
- **Python projects** — the official [Python client](https://docs.apify.com/api/client/python/docs.md): `pip install apify-client`.
- **Any other language** — the [REST API](https://docs.apify.com/api/v2.md).

For full API examples (JavaScript, Python, CLI, MCP, OpenAPI), see this Task's Actor page: https://apify.com/memo23/trustpilot-scraper-ppe.md

For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt).