How to Scrape Viator Data: Complete Guide for 2026

This guide covers extracting publicly accessible data. Always review a site's robots.txt and Terms of Service before scraping.

TL;DR

To scrape Viator, send a request to AlterLab's API with the target URL. Use Python or Node.js SDKs, rely on auto‑escalating tiers for anti‑bot handling, and optionally extract structured JSON with Cortex. Start at T1; the API promotes to T3/T4 as needed, charging only for the successful tier.

Why collect travel data from Viator?

Viator lists tours, activities, and experiences worldwide. Engineers extract this data for:

• Market research: Compare activity pricing across cities to inform product positioning.
• Price monitoring: Track seasonal fluctuations and dynamic discount patterns.
• Data analysis: Build recommendation engines or travel trend reports using publicly listed ratings and descriptions.

Technical challenges

Travel sites like viator.com deploy standard anti‑bot protections: rate limiting per IP, User‑Agent scrutiny, and lightweight JavaScript checks that can block raw HTTP requests. AlterLab's Smart Rendering API manages proxy rotation, header normalization, and headless browser fallback so you receive the public HTML without manually solving challenges.

Quick start with AlterLab API

See the Getting started guide for SDK installation. Below are ready‑to‑run examples for Python and Node.js.

import alterlab

client = alterlab.Client("YOUR_API_KEY")
response = client.scrape("https://www.viator.com/tours/London/Eiffel-Tower-Summit-Experience/d5072-12345TOUR")
print(response.text[:500])

import { AlterLab } from "alterlab";

const client = new AlterLab({ apiKey: "YOUR_API_KEY" });
const response = await client.scrape("https://www.viator.com/tours/London/Eiffel-Tower-Summit-Experience/d5072-12345TOUR");
console.log(response.text.slice(0, 500));

curl -X POST https://api.alterlab.io/v1/scrape \
  -H "X-API-Key: YOUR_KEY" \
  -d '{"url": "https://www.viator.com/tours/London/Eiffel-Tower-Summit-Experience/d5072-12345TOUR"}'

These snippets retrieve the raw HTML of a public tour page. AlterLab automatically selects the lowest viable tier (starting at T1) and upgrades if the response indicates a block.

Extracting structured data

Once you have the HTML, you can parse visible fields with CSS selectors. Common Viator data points include:

• Tour title (h1.tour-title)
• Price (span.price)
• Average rating (div.rating-stars)
• Description (div.description)

In Python with BeautifulSoup:

from bs4 import BeautifulSoup
soup = BeautifulSoup(response.text, "html.parser")
title = soup.select_one("h1.tour-title").get_text(strip=True)
price = float(soup.select_one("span.price").get_text(strip=True).replace("$", ""))
rating = float(soup.select_one("div.rating-stars")["data-rating"])
description = soup.select_one("div.description").get_text(strip=True)
print({"title": title, "price": price, "rating": rating, "description": description})

Node.js equivalent with Cheerio:

import cheerio from "cheerio";
const $ = cheerio.load(response.text);
const title = $("h1.tour-title").text().trim();
const price = parseFloat($("span.price").text().replace("$", ""));
const rating = parseFloat($("div.rating-stars").attr("data-rating"));
const description = $("div.description").text().trim();
console.log({ title, price, rating, description });

Structured JSON extraction with Cortex

AlterLab's Cortex API returns typed JSON directly, eliminating the need for local parsing. Provide a JSON Schema that matches the fields you want.

import alterlab

client = alterlab.Client("YOUR_API_KEY")
result = client.extract(
    url="https://www.viator.com/tours/London/Eiffel-Tower-Summit-Experience/d5072-12345TOUR",
    schema={
        "type": "object",
        "properties": {
            "title": {"type": "string"},
            "price": {"type": "number"},
            "rating": {"type": "number"},
            "description": {"type": "string"}
        },
        "required": ["title", "price"]
    }
)
print(result.data)  # Typed JSON output

Cortex handles JavaScript rendering and anti‑bot challenges internally, delivering consistent structured output.

Cost breakdown

AlterLab's pricing is usage‑based. The table below shows the cost per request and per 1,000 requests for each tier. For Viator, typical pages require JavaScript rendering and light anti‑bot handling, so the effective tier is often T3 (Stealth) or T4 (Browser). AlterLab auto‑escalates—you begin at T1 and only pay for the tier that succeeds.

See the AlterLab pricing page for the latest rates and volume discounts.

Best practices

• Rate limiting: Start with one request per second per IP; adjust based on response headers.
• Robots.txt: Check https://www.viator.com/robots.txt for disallowed paths before scaling.
• Dynamic content: Use Cortex or set render_js:true if initial HTML lacks the data you need.
• Error handling: Retry failed requests with exponential backoff; inspect response.status for tier‑specific hints.
• Headers: AlterLab supplies a realistic browser User‑Agent; you can add custom headers via the headers parameter if needed.

Scaling up

For large datasets:

• Batch requests: Send up to 100 URLs per batch using the /v1/scrape/batch endpoint to reduce overhead.
• Scheduling: Use AlterLab's scheduling feature** lets you define cron expressions for recurring scrapes (e.g., daily price checks).
• Handling results: Stream responses to a file or database; avoid holding all HTML in memory.
• Responsible scaling: Monitor your API usage dashboard and stay within the rate limits you set for Viator.

Key takeaways

• AlterLab abstracts anti‑bot complexity with