# AI Review Intelligence (`enezli/ai-review-intelligence`) Actor

Turns customer reviews into a prioritized, manager-ready action plan: sentiment, recurring themes, top complaints & praises, competitor gaps, and an executive summary. Connect any review-scraper output and get decisions, not just rows.

- **URL**: https://apify.com/enezli/ai-review-intelligence.md
- **Developed by:** [Turgay NANTA](https://apify.com/enezli) (community)
- **Categories:** AI, Marketing
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $400.00 / 1,000 per 100 reviews

This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events.

Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-event

## What's an Apify Actor?

Actors are a software tools running on the Apify platform, for all kinds of web data extraction and automation use cases.
In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours,
and optionally produces a well-defined JSON output, datasets with results, or files in key-value store.
In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server.
Actors are written with capital "A".

## 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.
The best way to integrate Actors is as follows.

In JavaScript/TypeScript projects, use official [JavaScript/TypeScript client](https://docs.apify.com/api/client/js.md):

```bash
npm install apify-client
```

In Python projects, use official [Python client library](https://docs.apify.com/api/client/python.md):

```bash
pip install apify-client
```

In shell scripts, use [Apify CLI](https://docs.apify.com/cli/docs.md):

````bash
# MacOS / Linux
curl -fsSL https://apify.com/install-cli.sh | bash
# Windows
irm https://apify.com/install-cli.ps1 | iex
```bash

In AI frameworks, you might use the [Apify MCP server](https://docs.apify.com/platform/integrations/mcp.md).

If your project is in a different language, use the [REST API](https://docs.apify.com/api/v2.md).

For usage examples, see the [API](#api) section below.

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).


# README

## AI Review Intelligence — From Reviews to an Action Plan

Turns hundreds of customer reviews into a **manager-ready action plan** in seconds. It doesn't just tell you *what customers think* — it tells you **what to do about it**: prioritized steps, quick wins, and the single critical move to make this week.

### What it does
Connect the output of a review-scraper (Google Maps, Trustpilot, Amazon, App Store) or your own review list, and the actor produces:

- **Overall sentiment** + star-rating distribution
- **Recurring themes** (frequency + positive/negative)
- **Top complaints and praises**
- **🎯 Action plan** — prioritized, concrete steps (each with benefit/cost + expected gain)
- **⚡ Quick wins** — low-effort, high-impact moves
- **The single critical step for this week**
- **Competitor opportunities** + a short executive summary

### Why it's different
Most review tools just hand you a raw sentiment score. This actor **behaves like a consultant who makes decisions**: it links every finding to an actionable step. Managers don't read the report and ask "so what do I do?" — the plan is already in their hands.

### Input
| Field | Description |
|---|---|
| `reviews` | The review list: plain strings OR `{text, rating}` objects. A review-scraper dataset can be connected directly. |
| `businessName` | Business name (used as report context) |
| `language` | Output language of the analysis content: English / Türkçe / Deutsch / Español / Français |
| `model` | (Advanced) LLM model — the default is fast and economical |

### Output
Delivered in two layers:

- **Dataset (table):** Prioritized **action plan** rows — columns: `Priority` · `Issue / Area` · `Risk of Inaction` · `Risk Level` · `Benefit` · `Cost` · `Benefit/Cost` · `Score` · `Recommended Action`. Scan, sort, and export directly.
- **Report (key-value store → `MANAGER_REPORT`):** Full narrative + machine-readable data with English keys: `overall_sentiment` · `themes` · `top_complaints` · `top_praises` · `competitor_opportunities` · `critical_step` · `quick_wins` · `executive_summary` · `rating_distribution` · `review_count` · `all_actions` (including more than what is shown in the main table).

### How to use
1. Collect your reviews with a review-scraper (or paste in your own list).
2. Connect the output to this actor as `reviews`.
3. Set the business name and language → **Start**.
4. Grab your action plan from the Dataset tab.

### Pricing (Pay-Per-Event)
You only pay for what you use: per run + per 100 reviews processed + per generated report. No monthly subscription.

# Actor input Schema

## `reviews` (type: `array`):

The reviews to analyze. Provide an array of plain strings OR {text, rating} objects. You can connect a review-scraper's dataset output directly.
## `businessName` (type: `string`):

Used in the report title and as context for the analysis.
## `language` (type: `string`):

Language of the analysis content (sentiment and action text).
## `model` (type: `string`):

LLM model. The default is cheap and fast; pick a stronger model for deeper analysis.
## `maxAksiyon` (type: `integer`):

How many prioritized actions to show in the main table (for focus). All of them are always kept in the report (MANAGER_REPORT). Range 3-10.

## Actor input object example

```json
{
  "reviews": [
    {
      "text": "Hizmet hızlıydı ama fiyat yüksek.",
      "rating": 3
    },
    {
      "text": "Personel ilgisizdi.",
      "rating": 2
    },
    {
      "text": "Harika lezzet, tekrar geleceğim!",
      "rating": 5
    }
  ],
  "businessName": "Business",
  "language": "English",
  "model": "claude-haiku-4-5-20251001",
  "maxAksiyon": 5
}
````

# API

You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup.

## JavaScript example

```javascript
import { ApifyClient } from 'apify-client';

// Initialize the ApifyClient with your Apify API token
// Replace the '<YOUR_API_TOKEN>' with your token
const client = new ApifyClient({
    token: '<YOUR_API_TOKEN>',
});

// Prepare Actor input
const input = {
    "reviews": [
        {
            "text": "Hizmet hızlıydı ama fiyat yüksek.",
            "rating": 3
        },
        {
            "text": "Personel ilgisizdi.",
            "rating": 2
        },
        {
            "text": "Harika lezzet, tekrar geleceğim!",
            "rating": 5
        }
    ]
};

// Run the Actor and wait for it to finish
const run = await client.actor("enezli/ai-review-intelligence").call(input);

// Fetch and print Actor results from the run's dataset (if any)
console.log('Results from dataset');
console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`);
const { items } = await client.dataset(run.defaultDatasetId).listItems();
items.forEach((item) => {
    console.dir(item);
});

// 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs

```

## Python example

```python
from apify_client import ApifyClient

# Initialize the ApifyClient with your Apify API token
# Replace '<YOUR_API_TOKEN>' with your token.
client = ApifyClient("<YOUR_API_TOKEN>")

# Prepare the Actor input
run_input = { "reviews": [
        {
            "text": "Hizmet hızlıydı ama fiyat yüksek.",
            "rating": 3,
        },
        {
            "text": "Personel ilgisizdi.",
            "rating": 2,
        },
        {
            "text": "Harika lezzet, tekrar geleceğim!",
            "rating": 5,
        },
    ] }

# Run the Actor and wait for it to finish
run = client.actor("enezli/ai-review-intelligence").call(run_input=run_input)

# Fetch and print Actor results from the run's dataset (if there are any)
print("💾 Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"])
for item in client.dataset(run["defaultDatasetId"]).iterate_items():
    print(item)

# 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start

```

## CLI example

```bash
echo '{
  "reviews": [
    {
      "text": "Hizmet hızlıydı ama fiyat yüksek.",
      "rating": 3
    },
    {
      "text": "Personel ilgisizdi.",
      "rating": 2
    },
    {
      "text": "Harika lezzet, tekrar geleceğim!",
      "rating": 5
    }
  ]
}' |
apify call enezli/ai-review-intelligence --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "command": "npx",
            "args": [
                "mcp-remote",
                "https://mcp.apify.com/?tools=enezli/ai-review-intelligence",
                "--header",
                "Authorization: Bearer <YOUR_API_TOKEN>"
            ]
        }
    }
}

```

## OpenAPI specification

```json
{
    "openapi": "3.0.1",
    "info": {
        "title": "AI Review Intelligence",
        "description": "Turns customer reviews into a prioritized, manager-ready action plan: sentiment, recurring themes, top complaints & praises, competitor gaps, and an executive summary. Connect any review-scraper output and get decisions, not just rows.",
        "version": "0.1",
        "x-build-id": "YBYUK17B6ySvHSxWA"
    },
    "servers": [
        {
            "url": "https://api.apify.com/v2"
        }
    ],
    "paths": {
        "/acts/enezli~ai-review-intelligence/run-sync-get-dataset-items": {
            "post": {
                "operationId": "run-sync-get-dataset-items-enezli-ai-review-intelligence",
                "x-openai-isConsequential": false,
                "summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.",
                "tags": [
                    "Run Actor"
                ],
                "requestBody": {
                    "required": true,
                    "content": {
                        "application/json": {
                            "schema": {
                                "$ref": "#/components/schemas/inputSchema"
                            }
                        }
                    }
                },
                "parameters": [
                    {
                        "name": "token",
                        "in": "query",
                        "required": true,
                        "schema": {
                            "type": "string"
                        },
                        "description": "Enter your Apify token here"
                    }
                ],
                "responses": {
                    "200": {
                        "description": "OK"
                    }
                }
            }
        },
        "/acts/enezli~ai-review-intelligence/runs": {
            "post": {
                "operationId": "runs-sync-enezli-ai-review-intelligence",
                "x-openai-isConsequential": false,
                "summary": "Executes an Actor and returns information about the initiated run in response.",
                "tags": [
                    "Run Actor"
                ],
                "requestBody": {
                    "required": true,
                    "content": {
                        "application/json": {
                            "schema": {
                                "$ref": "#/components/schemas/inputSchema"
                            }
                        }
                    }
                },
                "parameters": [
                    {
                        "name": "token",
                        "in": "query",
                        "required": true,
                        "schema": {
                            "type": "string"
                        },
                        "description": "Enter your Apify token here"
                    }
                ],
                "responses": {
                    "200": {
                        "description": "OK",
                        "content": {
                            "application/json": {
                                "schema": {
                                    "$ref": "#/components/schemas/runsResponseSchema"
                                }
                            }
                        }
                    }
                }
            }
        },
        "/acts/enezli~ai-review-intelligence/run-sync": {
            "post": {
                "operationId": "run-sync-enezli-ai-review-intelligence",
                "x-openai-isConsequential": false,
                "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.",
                "tags": [
                    "Run Actor"
                ],
                "requestBody": {
                    "required": true,
                    "content": {
                        "application/json": {
                            "schema": {
                                "$ref": "#/components/schemas/inputSchema"
                            }
                        }
                    }
                },
                "parameters": [
                    {
                        "name": "token",
                        "in": "query",
                        "required": true,
                        "schema": {
                            "type": "string"
                        },
                        "description": "Enter your Apify token here"
                    }
                ],
                "responses": {
                    "200": {
                        "description": "OK"
                    }
                }
            }
        }
    },
    "components": {
        "schemas": {
            "inputSchema": {
                "type": "object",
                "required": [
                    "reviews"
                ],
                "properties": {
                    "reviews": {
                        "title": "Reviews",
                        "type": "array",
                        "description": "The reviews to analyze. Provide an array of plain strings OR {text, rating} objects. You can connect a review-scraper's dataset output directly."
                    },
                    "businessName": {
                        "title": "Business name",
                        "type": "string",
                        "description": "Used in the report title and as context for the analysis.",
                        "default": "Business"
                    },
                    "language": {
                        "title": "Output language",
                        "enum": [
                            "Türkçe",
                            "English",
                            "Deutsch",
                            "Español",
                            "Français"
                        ],
                        "type": "string",
                        "description": "Language of the analysis content (sentiment and action text).",
                        "default": "English"
                    },
                    "model": {
                        "title": "Model (advanced)",
                        "enum": [
                            "claude-haiku-4-5-20251001",
                            "claude-sonnet-4-6"
                        ],
                        "type": "string",
                        "description": "LLM model. The default is cheap and fast; pick a stronger model for deeper analysis.",
                        "default": "claude-haiku-4-5-20251001"
                    },
                    "maxAksiyon": {
                        "title": "Actions shown in the table",
                        "minimum": 3,
                        "maximum": 10,
                        "type": "integer",
                        "description": "How many prioritized actions to show in the main table (for focus). All of them are always kept in the report (MANAGER_REPORT). Range 3-10.",
                        "default": 5
                    }
                }
            },
            "runsResponseSchema": {
                "type": "object",
                "properties": {
                    "data": {
                        "type": "object",
                        "properties": {
                            "id": {
                                "type": "string"
                            },
                            "actId": {
                                "type": "string"
                            },
                            "userId": {
                                "type": "string"
                            },
                            "startedAt": {
                                "type": "string",
                                "format": "date-time",
                                "example": "2025-01-08T00:00:00.000Z"
                            },
                            "finishedAt": {
                                "type": "string",
                                "format": "date-time",
                                "example": "2025-01-08T00:00:00.000Z"
                            },
                            "status": {
                                "type": "string",
                                "example": "READY"
                            },
                            "meta": {
                                "type": "object",
                                "properties": {
                                    "origin": {
                                        "type": "string",
                                        "example": "API"
                                    },
                                    "userAgent": {
                                        "type": "string"
                                    }
                                }
                            },
                            "stats": {
                                "type": "object",
                                "properties": {
                                    "inputBodyLen": {
                                        "type": "integer",
                                        "example": 2000
                                    },
                                    "rebootCount": {
                                        "type": "integer",
                                        "example": 0
                                    },
                                    "restartCount": {
                                        "type": "integer",
                                        "example": 0
                                    },
                                    "resurrectCount": {
                                        "type": "integer",
                                        "example": 0
                                    },
                                    "computeUnits": {
                                        "type": "integer",
                                        "example": 0
                                    }
                                }
                            },
                            "options": {
                                "type": "object",
                                "properties": {
                                    "build": {
                                        "type": "string",
                                        "example": "latest"
                                    },
                                    "timeoutSecs": {
                                        "type": "integer",
                                        "example": 300
                                    },
                                    "memoryMbytes": {
                                        "type": "integer",
                                        "example": 1024
                                    },
                                    "diskMbytes": {
                                        "type": "integer",
                                        "example": 2048
                                    }
                                }
                            },
                            "buildId": {
                                "type": "string"
                            },
                            "defaultKeyValueStoreId": {
                                "type": "string"
                            },
                            "defaultDatasetId": {
                                "type": "string"
                            },
                            "defaultRequestQueueId": {
                                "type": "string"
                            },
                            "buildNumber": {
                                "type": "string",
                                "example": "1.0.0"
                            },
                            "containerUrl": {
                                "type": "string"
                            },
                            "usage": {
                                "type": "object",
                                "properties": {
                                    "ACTOR_COMPUTE_UNITS": {
                                        "type": "integer",
                                        "example": 0
                                    },
                                    "DATASET_READS": {
                                        "type": "integer",
                                        "example": 0
                                    },
                                    "DATASET_WRITES": {
                                        "type": "integer",
                                        "example": 0
                                    },
                                    "KEY_VALUE_STORE_READS": {
                                        "type": "integer",
                                        "example": 0
                                    },
                                    "KEY_VALUE_STORE_WRITES": {
                                        "type": "integer",
                                        "example": 1
                                    },
                                    "KEY_VALUE_STORE_LISTS": {
                                        "type": "integer",
                                        "example": 0
                                    },
                                    "REQUEST_QUEUE_READS": {
                                        "type": "integer",
                                        "example": 0
                                    },
                                    "REQUEST_QUEUE_WRITES": {
                                        "type": "integer",
                                        "example": 0
                                    },
                                    "DATA_TRANSFER_INTERNAL_GBYTES": {
                                        "type": "integer",
                                        "example": 0
                                    },
                                    "DATA_TRANSFER_EXTERNAL_GBYTES": {
                                        "type": "integer",
                                        "example": 0
                                    },
                                    "PROXY_RESIDENTIAL_TRANSFER_GBYTES": {
                                        "type": "integer",
                                        "example": 0
                                    },
                                    "PROXY_SERPS": {
                                        "type": "integer",
                                        "example": 0
                                    }
                                }
                            },
                            "usageTotalUsd": {
                                "type": "number",
                                "example": 0.00005
                            },
                            "usageUsd": {
                                "type": "object",
                                "properties": {
                                    "ACTOR_COMPUTE_UNITS": {
                                        "type": "integer",
                                        "example": 0
                                    },
                                    "DATASET_READS": {
                                        "type": "integer",
                                        "example": 0
                                    },
                                    "DATASET_WRITES": {
                                        "type": "integer",
                                        "example": 0
                                    },
                                    "KEY_VALUE_STORE_READS": {
                                        "type": "integer",
                                        "example": 0
                                    },
                                    "KEY_VALUE_STORE_WRITES": {
                                        "type": "number",
                                        "example": 0.00005
                                    },
                                    "KEY_VALUE_STORE_LISTS": {
                                        "type": "integer",
                                        "example": 0
                                    },
                                    "REQUEST_QUEUE_READS": {
                                        "type": "integer",
                                        "example": 0
                                    },
                                    "REQUEST_QUEUE_WRITES": {
                                        "type": "integer",
                                        "example": 0
                                    },
                                    "DATA_TRANSFER_INTERNAL_GBYTES": {
                                        "type": "integer",
                                        "example": 0
                                    },
                                    "DATA_TRANSFER_EXTERNAL_GBYTES": {
                                        "type": "integer",
                                        "example": 0
                                    },
                                    "PROXY_RESIDENTIAL_TRANSFER_GBYTES": {
                                        "type": "integer",
                                        "example": 0
                                    },
                                    "PROXY_SERPS": {
                                        "type": "integer",
                                        "example": 0
                                    }
                                }
                            }
                        }
                    }
                }
            }
        }
    }
}
```