# Analyze online store reviews: delivery, quality, support

**Use case:** 

Analyze the reviews of an online store against your own themes (here: delivery, product quality, customer support, returns and refunds, price). Each review gets a sentiment, the themes it praises or criticizes and a severity; each store gets a summary and its unanswered complaints. Works with Trustpilot or Google review scrapers. The sample uses fictional reviews.

## Input

```json
{
  "reviews": [
    {
      "text": "Parcel arrived in two days, the lamp is even nicer than on the photos.",
      "rating": 5,
      "placeName": "Nordic Home Store (sample)",
      "category": "Online store",
      "date": "2026-09-14"
    },
    {
      "text": "Three weeks late, tracking never updated, support only sends copy-paste answers.",
      "rating": 1,
      "placeName": "Nordic Home Store (sample)",
      "category": "Online store",
      "date": "2026-09-25"
    },
    {
      "text": "The chair wobbles and one screw was missing. Return accepted but the refund took a month.",
      "rating": 2,
      "placeName": "Nordic Home Store (sample)",
      "category": "Online store",
      "date": "2026-09-29"
    },
    {
      "text": "Good value for money, the sofa cover fits perfectly.",
      "rating": 4,
      "placeName": "Nordic Home Store (sample)",
      "category": "Online store",
      "date": "2026-08-21",
      "reply": "Thank you for your order!"
    },
    {
      "text": "They charged my card twice and nobody answers the phone.",
      "rating": 1,
      "placeName": "Nordic Home Store (sample)",
      "category": "Online store",
      "date": "2026-10-03"
    },
    {
      "text": "Nice rug, but the colour is darker than shown.",
      "rating": 3,
      "placeName": "Nordic Home Store (sample)",
      "category": "Online store",
      "date": "2026-07-11"
    }
  ],
  "businessType": "auto",
  "themes": [
    "delivery",
    "product quality",
    "customer support",
    "returns: returns and refunds",
    "price"
  ],
  "maxReviews": 500,
  "maxReviewsPerPlace": 100,
  "includeReviewText": true
}
```

## Output

```json
{
  "placeName": {
    "label": "Business",
    "format": "string"
  },
  "reviewsAnalyzed": {
    "label": "Reviews",
    "format": "integer"
  },
  "averageRating": {
    "label": "Rating",
    "format": "number"
  },
  "negativeShare": {
    "label": "Negative share",
    "format": "number"
  },
  "unansweredComplaints": {
    "label": "Unanswered complaints",
    "format": "integer"
  },
  "summary": {
    "label": "Summary",
    "format": "string"
  }
}
```

## How it works

### 1. Sign up on Apify or log in

The Review Analyzer API — Sentiment, Topics & Complaints Actor is ready to run with the inputs already set for "Analyze online store reviews: delivery, quality, support". [Sign up or log in](https://console.apify.com/create-task-from-example/f7WDcry0G9bVMeAmC) and you'll land in Apify Console with a copy of this exact task.

### 2. Start the "Analyze online store reviews: delivery, quality, support" task

The Review Analyzer API — Sentiment, Topics & Complaints Actor will start running based on the input automatically. You can also change all the input fields, like reviews, business type, and more, to match your specific use case.

### 3. Receive the "Analyze online store reviews: delivery, quality, support" output

Monitor the progress in real time. You will be notified as soon as your dataset is complete and ready for review. Each result includes data such as business, reviews, rating, and more.

### 4. Integrate into your workflow

The final output is delivered in JSON, CSV, or Excel format, ready to be plugged into your workflow. You can also [run the "Analyze online store reviews: delivery, quality, support" task via API](https://apify.com/sherwood/review-analyzer.md).

## About this Actor

This example demonstrates how to use [Review Analyzer API — Sentiment, Topics & Complaints](https://apify.com/sherwood/review-analyzer.md) with a specific input configuration. Visit the [Actor detail page](https://apify.com/sherwood/review-analyzer.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/sherwood/review-analyzer.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`).