# Naver Place Review Monitor — New Reviews to CSV (`royal_niche/naver-place-review-monitor`) Actor

Monitor public Naver Place pages across up to 10 locations. The first run emits a baseline of recent visitor reviews; later runs emit only newly observed reviews, deduplicated per monitor key. Review rows are exportable as CSV/JSON from the run dataset; each run also writes a per-place summary.

- **URL**: https://apify.com/royal_niche/naver-place-review-monitor.md
- **Developed by:** [kiwan kim](https://apify.com/royal_niche) (community)
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

$2.00 / 1,000 place checks

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/actors/running/actors-in-store.md#pay-per-event

## What's an Apify Actor?

An Actor is a serverless cloud program that runs on the Apify platform. It has two run modes.
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.

Apify vocabulary and the platform model are defined once, in the agent quickstart at https://apify.com/agents.md.

## 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.

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 examples already wired to this Actor's own input schema, see the [API](#api) section below.

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`).

# README

## Naver Place Review Monitor — New Reviews to CSV

Monitor public [Naver Place](https://place.naver.com) pages (restaurants, cafés, salons, shops) across up to 10 locations. The first run emits a **baseline** of each place's recent visitor reviews; later runs emit only **newly observed** reviews for the same monitor key, so you can export a spreadsheet of just the new reviews instead of the whole review list again.

Built for people who already check Naver Place reviews regularly — e.g. agencies or operators consolidating reviews for several stores into one report.

### How it works

1. You provide up to 10 public Naver Place URLs and a **monitor key** (any name you choose, e.g. `client-a-weekly`).
2. Run 1 observes each place's recent reviews and writes rows labelled `baseline`.
3. Run 2+ compares against the reviews this monitor key has already observed and writes only rows labelled `newly_observed`.
4. Review rows go to the run's **dataset** (exportable as CSV/JSON/Excel). A per-place run summary is written to the key-value store under `OUTPUT`.

`newly_observed` means *not seen before by this monitor key* — it does not guarantee the review was written recently. A bounded scan can miss reviews; see limits below.

### Input

| Field | Type | Description |
|---|---|---|
| `placeUrls` | string array | 1–10 public Naver Place URLs: `m.place.naver.com/<type>/<id>/...`, `pcmap.place.naver.com/...`, `map.naver.com/.../place/<id>`, or a bare numeric Place ID. Unsupported entries are reported per place (status `invalid_url`) without failing the run. |
| `monitorKey` | string | Stable identifier for this monitored collection (letters, digits, `.`, `-`, `_`; max 100 chars). State is kept separately per key and per user account. |
| `maxReviewsPerPlace` | integer | How many of each place's most recent reviews to scan per run (1–200, default 50). Keep it comfortably above the number of reviews that can accumulate between runs, or older missed reviews fall out of the window. |
| `resetBaseline` | boolean | Opt-in: forget retained history for the places in this run and emit a fresh baseline. |

### Output

#### Dataset fields (one row per review)

| Field | Meaning |
|---|---|
| `placeId` | Stable Naver Place identifier |
| `businessName` | Business name when exposed by the source; otherwise `null` |
| `reviewId` | Stable Naver review identifier |
| `text` | Original review text; `null` for rating-only reviews |
| `publishedAt` | Publication date as exposed by Naver, kept raw — often a yearless display string like `10.13.화`; otherwise `null` |
| `visitedAt` | Visit date (ISO) when exposed, kept separate from publication date; otherwise `null` |
| `sourceUrl` | Public review page URL for the place |
| `observedAt` | Collection timestamp (UTC) |
| `recordType` | `baseline` or `newly_observed` |

Nothing is fabricated: when Naver does not expose a value, the field stays `null`.

#### Run summary (key-value store, key `OUTPUT`)

Per place: `status`, `scanned`, `emittedBaseline`, `emittedNew`, `duplicatesPreviousRuns`, `duplicatesInRun`, `capReached`, `totalAvailable`, `requests`, `elapsedMs`, and an `error` message when something went wrong. Statuses are distinct:

- `ok` — worked (with `capReached: true` if the scan cap ended the run before the window did)
- `empty` — genuinely no reviews returned
- `blocked` — Naver rate-limited or refused (HTTP 401/403/429)
- `failed` — network error, error response, or malformed body
- `invalid_url` — URL not recognized as a Naver Place URL
- `busy` — another run currently holds the lock for this monitor key

#### Example outputs

See `sample-outputs/` for a real (live, 2026-10-14) baseline summary, the identical second run (0 new rows), and a 3-row sample of the review dataset.

### Deduplication state and limits

- State lives in a **named key-value store** (`naver-place-review-monitor-state`), retained across runs and kept per user account.
- Per place, the monitor retains the most recent **500 observed review IDs**. Deduplication only covers that retained history.
- Rows are pushed to the dataset *before* their IDs are recorded; state only advances for rows that were saved. If a run dies between the two, those rows can be re-emitted on the next run (at-least-once), but unexported reviews are never falsely marked as seen.
- Concurrent runs of the same monitor key are serialized with a lock record; the later run exits with `busy` rather than racing. The KV store has no compare-and-set, so the lock is best-effort (documented residual race).
- Review edits and deletions are not tracked. Historical backfill beyond `maxReviewsPerPlace` is not provided.

### Honest limitations

- Collects only what public Naver Place pages expose; no login-only data, and no attempt to bypass access controls. If Naver changes or blocks the endpoint, runs report `blocked`/`failed` honestly.
- Polling costs apply on every run, including runs with zero new reviews — keep schedules modest.
- Review counts and windows are Naver's; `totalAvailable` may exceed what your cap scans.
- Naver Place review pages are public but rates are not infinite: requests are paced (~1/second) and retried with backoff.

### Local development

```bash
cd actor
uv venv .venv --python 3.14 && source .venv/bin/activate
uv pip install -r requirements.txt

## deterministic offline verification (59 checks, no network)
python tests/verify_actor.py

## local live run (writes to ./storage)
apify run -i '{"placeUrls":["https://m.place.naver.com/restaurant/832363546/review/visitor"],"monitorKey":"my-monitor","maxReviewsPerPlace":10}'
```

On the Apify platform, review rows appear in the run's **Output → dataset** tab (any run of this Actor has its own dataset — export CSV there), and the run summary appears in the **key-value store** under `OUTPUT`.

### Support

Questions, bug reports, and feature requests go through the **Issues** tab on this Actor's page on Apify Store. When reporting a collection problem, include the run ID and the run summary (key-value store `OUTPUT`) — it lists each place's exact status and error, which makes problems diagnosable without extra back-and-forth.

### Pricing

Not yet set. See the project plan — pricing will be based on measured polling costs (including no-new-review runs), with any minimum charge or platform usage fee made explicit in the listing.

# Actor input Schema

## `placeUrls` (type: `array`):

Public Naver Place page URLs (up to 10). Supported: m.place.naver.com/<type>/<id>/..., pcmap.place.naver.com/<type>/<id>/..., map.naver.com/.../place/<id>, or a bare numeric Place ID. Unsupported entries are reported per place without failing the run.

## `monitorKey` (type: `string`):

Identifier for this monitored collection, kept stable across runs (e.g. the client or campaign name). Reviews already observed under the same monitor key are not exported again. Use a different key to keep independent baselines.

## `maxReviewsPerPlace` (type: `integer`):

How many of each place's most recent reviews to scan per run (1-200). Polling scans this window even when no new reviews exist.

## `resetBaseline` (type: `boolean`):

Explicit opt-in: forget the retained history for the places in this run and treat this run as a new baseline. The next run then reports only reviews observed after this reset.

## Actor input object example

```json
{
  "placeUrls": [
    "https://m.place.naver.com/restaurant/832363546/review/visitor",
    "https://m.place.naver.com/hairshop/1179250551/review/visitor"
  ],
  "monitorKey": "my-monitor",
  "maxReviewsPerPlace": 50,
  "resetBaseline": false
}
```

# Actor output Schema

## `reviews` (type: `string`):

No description

## `runSummary` (type: `string`):

No description

# 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 = {
    "placeUrls": [
        "https://m.place.naver.com/restaurant/832363546/review/visitor",
        "https://m.place.naver.com/hairshop/1179250551/review/visitor"
    ],
    "monitorKey": "my-monitor"
};

// Run the Actor and wait for it to finish
const run = await client.actor("royal_niche/naver-place-review-monitor").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 = {
    "placeUrls": [
        "https://m.place.naver.com/restaurant/832363546/review/visitor",
        "https://m.place.naver.com/hairshop/1179250551/review/visitor",
    ],
    "monitorKey": "my-monitor",
}

# Run the Actor and wait for it to finish
run = client.actor("royal_niche/naver-place-review-monitor").call(run_input=run_input)

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

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

```

## CLI example

```bash
echo '{
  "placeUrls": [
    "https://m.place.naver.com/restaurant/832363546/review/visitor",
    "https://m.place.naver.com/hairshop/1179250551/review/visitor"
  ],
  "monitorKey": "my-monitor"
}' |
apify call royal_niche/naver-place-review-monitor --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,royal_niche/naver-place-review-monitor"
        }
    }
}
```

The hosted server signs you in with OAuth on first connect, so no API token belongs in this config. Clients without OAuth support can send an `Authorization: Bearer <APIFY_API_TOKEN>` header instead, using a token from API & Integrations in Apify Console (https://console.apify.com/settings/integrations).

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/actors/4kU2Iciv0YdAms7iB/builds/y7nDdlWsdXaa82iWd/openapi.json