PlumGuide Property Search Scraper: Extract Luxury Vacation Rental Data

Understanding PlumGuide and Its Premium Rental Market

PlumGuide curates high-end vacation rentals globally, accepting only properties that pass rigorous quality standards. Unlike mass-market platforms, PlumGuide focuses on design-forward, professionally managed homes in prime locations. This selectivity makes it valuable for luxury travel analysis, premium property benchmarking, and understanding high-end rental dynamics.

The platform displays dynamic pricing, promotional discounts, and location proximity—data critical for property managers optimizing rates and travelers analyzing value. Manual comparison across dates, locations, and guest counts is impractical. This scraper automates extraction, delivering structured datasets for pricing analysis, market research, and competitive intelligence.

What This Scraper Extracts and Target Users

The scraper processes PlumGuide search result pages—the listings displayed after setting location, dates, and guest parameters. It captures property-level data visible in search views.

Extracted Data:

Listing: Property identifier and basic information linking to full details.

Origin: Source or listing origin designation within PlumGuide's system.

Nightly Price: Current per-night rate for specified dates and guest count.

Discount Percentage: Applied promotional discount (e.g., 15% off).

Total Price Without Discount / Nightly Price Without Discount: Original pricing before discounts, enabling true cost comparison.

Total Price: Final booking cost after discounts for the entire stay.

Is Price Syncing: Flag indicating if pricing is synchronizing with external systems (useful for identifying dynamic pricing properties).

Is Non Refundable: Indicates non-refundable booking terms.

Dates: Check-in/check-out dates for pricing context.

Proximity: Distance or travel time from search location center (e.g., "15 min to city center").

Input Configuration

Example Input:

{
  "urls": [
    "https://www.plumguide.com/search?adults=1&children=1&datepickerType=calendar&infants=1&location=London&pets=1&placeId=ChIJdd4hrwug2EcRmSrV3Vo6llI"
  ],
  "ignore_url_failures": true,
  "max_items_per_url": 50
}

Parameter Details:

urls: PlumGuide search result page URLs. Construct these by performing searches on PlumGuide with desired filters (location, dates, guests, pets). The URL encodes all search parameters—adults, children, infants, dates, location. Copy URLs directly from your browser after setting search criteria.

ignore_url_failures: Set true for robustness when scraping multiple URLs. Individual failures won't halt the entire run—critical for batch processing across locations or date ranges.

max_items_per_url: Maximum properties to extract per search page (default 20, max typically 50). PlumGuide displays 20-30 results per page. Set higher for comprehensive extraction or lower for testing.

Building Search URLs: Manually search PlumGuide with target parameters (location: "Paris," adults: 2, dates: specific range). Copy resulting URL. Modify parameters in URL directly for variations (change adults=2 to adults=4) or perform new searches for different locations.

Output Structure and Field Meanings

Sample Output:

{
  "listing": {
    "listing_id": 61534,
    "name": "Morning Journal ",
    "photos": [
      "https://i.plumcache.com/listings/9e5d3032-dfec-43fe-b69a-e37def97b961/224c1990-e5c8-4ca7-9548-71923edca650..jpeg",
      "https://i.plumcache.com/listings/9e5d3032-dfec-43fe-b69a-e37def97b961/811d4ad6-dc29-43ad-8a62-c0072a1d2693..jpeg",
      "https://i.plumcache.com/listings/9e5d3032-dfec-43fe-b69a-e37def97b961/8fa1a793-1dab-4341-b844-152af9092aeb..jpeg",
      "https://i.plumcache.com/listings/9e5d3032-dfec-43fe-b69a-e37def97b961/4a214ca7-8789-4be4-abc1-f52f31762356..jpeg",
      "https://i.plumcache.com/listings/9e5d3032-dfec-43fe-b69a-e37def97b961/89fc2b53-4c85-489e-8229-ac4a121dd27a..jpeg",
      "https://i.plumcache.com/listings/9e5d3032-dfec-43fe-b69a-e37def97b961/184848db-3795-400a-9556-81a6ced27ef7..jpeg",
      "https://i.plumcache.com/listings/9e5d3032-dfec-43fe-b69a-e37def97b961/a3096204-401a-4579-9177-6c94a23080f8..jpeg",
      "https://i.plumcache.com/listings/9e5d3032-dfec-43fe-b69a-e37def97b961/f9503765-0f41-4b48-894c-1a9c8db66d9a..jpeg",
      "https://i.plumcache.com/listings/9e5d3032-dfec-43fe-b69a-e37def97b961/f6df85b1-224f-4008-9a60-9b8632a590c2..jpeg",
      "https://i.plumcache.com/listings/9e5d3032-dfec-43fe-b69a-e37def97b961/9cd6e23b-b1fc-41d5-b1fc-744427ea7023..jpeg",
      "https://i.plumcache.com/listings/9e5d3032-dfec-43fe-b69a-e37def97b961/9e74823b-0368-4fbe-8946-3ac25b86ed0f..jpeg",
      "https://i.plumcache.com/listings/9e5d3032-dfec-43fe-b69a-e37def97b961/bea359c3-6d0a-436e-8452-5126633185a5..jpeg",
      "https://i.plumcache.com/listings/9e5d3032-dfec-43fe-b69a-e37def97b961/a6e3a729-c009-4eb4-822f-ba9e9775e423..jpeg",
      "https://i.plumcache.com/listings/9e5d3032-dfec-43fe-b69a-e37def97b961/19e896e2-8351-429d-bf4c-9882c21fac6c..jpeg",
      "https://i.plumcache.com/listings/9e5d3032-dfec-43fe-b69a-e37def97b961/7608cdc0-ef86-412e-ba36-a6379cf01729..jpeg",
      "https://i.plumcache.com/listings/9e5d3032-dfec-43fe-b69a-e37def97b961/1bc0464a-2f8c-496f-8a7f-3397c55a62ac..jpeg",
      "https://i.plumcache.com/listings/9e5d3032-dfec-43fe-b69a-e37def97b961/2bdfdeed-0fc4-4f9e-9f82-f905dea4bf18..jpeg",
      "https://i.plumcache.com/listings/9e5d3032-dfec-43fe-b69a-e37def97b961/f5b155a1-cc84-42a3-8035-2439e44f818d..jpeg",
      "https://i.plumcache.com/listings/9e5d3032-dfec-43fe-b69a-e37def97b961/2a2c0a9e-2d0d-4c11-971a-0662d3fdfb1d..jpeg",
      "https://i.plumcache.com/listings/9e5d3032-dfec-43fe-b69a-e37def97b961/fc6ffa6d-ce3f-4276-82ab-2d691040d9c7..jpeg",
      "https://i.plumcache.com/listings/9e5d3032-dfec-43fe-b69a-e37def97b961/21905115-52f5-4fe2-a420-36425b4c657c..jpeg",
      "https://i.plumcache.com/listings/9e5d3032-dfec-43fe-b69a-e37def97b961/94e649eb-7362-4a87-bb21-ad3806032ebc..jpeg"
    ],
    "featured_image_url": "https://i.plumcache.com/listings/9e5d3032-dfec-43fe-b69a-e37def97b961/224c1990-e5c8-4ca7-9548-71923edca650..jpeg",
    "bathroom_count": 2,
    "bedroom_count": 1,
    "guest_count": 2,
    "short_location": "Bayswater, London",
    "latitude": 51.5135618,
    "longitude": -0.1943577,
    "cancellation_policy_id": 10,
    "property_type": null,
    "is_exclusive": false,
    "tracking": {
      "city": "London",
      "region": "Greater London",
      "country": "United Kingdom",
      "neighbourhood": "Bayswater",
      "place_id": "ChIJdd4hrwug2EcRmSrV3Vo6llI",
      "__typename": "LocationTracking"
    },
    "slug": "morning-journal",
    "__typename": "Listing"
  },
  "origin": "default",
  "nightly_price": null,
  "discount_percentage": null,
  "total_price_without_discount": null,
  "nightly_price_without_discount": null,
  "total_price": null,
  "is_price_syncing": false,
  "is_non_refundable": null,
  "dates": null,
  "proximity": null
}

Listing: Property object containing ID, name, and reference data. Use: Primary key for tracking specific properties, linking to detail pages, building property databases.

Origin: Listing source designation. Use: Understanding property management structure, filtering by listing type.

Nightly Price: Current per-night rate in local currency. Use: Real-time pricing analysis, rate comparisons across properties and dates.

Discount Percentage: Promotional discount applied (0 if none). Use: Identifying promotional strategies, calculating discount prevalence, evaluating true property value.

Total Price Without Discount: Full stay cost before promotions. Use: True cost comparison, understanding base pricing strategies.

Nightly Price Without Discount: Original per-night rate. Use: Benchmarking undiscounted rates, analyzing discount depth.

Total Price: Final booking cost after discounts. Use: Actual cost analysis, budget filtering, price competitiveness assessment.

Is Price Syncing: Boolean indicating dynamic pricing updates. Use: Identifying properties using automated pricing tools, understanding rate fluidity.

Is Non Refundable: Refund policy indicator. Use: Filtering by booking flexibility, analyzing pricing vs. policy tradeoffs.

Dates: Check-in and check-out dates for this pricing. Use: Contextualizing prices, tracking seasonal variations, date-specific analysis.

Proximity: Location proximity metrics. Use: Value-for-distance analysis, filtering by location convenience.

Implementation Guide

1. Define Search Parameters: Decide location, dates, guest composition (adults/children/infants), and pets. Test searches on PlumGuide to ensure results match expectations.

2. Collect Search URLs: Perform searches manually, copy URLs. For multi-market analysis, create URLs for different locations. For seasonal analysis, vary dates.

3. Configure Input: Build JSON with URL list. Set max_items_per_url to 50 for full pages or 20 for standard extraction. Enable ignore_url_failures for multi-URL runs.

4. Run Scraper: Launch via Apify. Processing 5 search URLs with 30 properties each typically completes in 2-4 minutes.

5. Validate Output: Check pricing logic (total_price = nightly_price × nights), verify dates match URLs, ensure proximity data is present.

6. Export Data: JSON for databases, CSV for spreadsheets, Excel for business reports.

Error Handling: Verify URLs are search result pages, not property detail pages. Check that date parameters are valid (future dates, check-out after check-in). Invalid guest counts may return empty results.

Strategic Applications

Dynamic Pricing Analysis: Track how nightly rates fluctuate across booking windows. Compare early booking vs. last-minute pricing. Analyze discount timing and depth across seasons.

Competitive Benchmarking: Monitor competitor properties in same neighborhoods. Compare pricing for similar property types (2BR apartments, penthouses). Identify underpriced or overpriced listings relative to market.

Seasonal Trend Tracking: Scrape same locations monthly across different dates. Map peak season pricing surges, off-season discounts, and shoulder season patterns.

Discount Strategy Intelligence: Calculate discount prevalence by location and season. Analyze correlation between discount depth and booking terms (non-refundable rates get deeper discounts).

Location Value Analysis: Cross-reference proximity data with pricing. Identify value opportunities—lower-priced properties near key attractions. Map price-per-proximity curves.

Market Entry Research: Assess competitive landscapes before launching properties. Understand typical pricing ranges, discount expectations, and market saturation in target neighborhoods.

Maximizing Data Value

Multi-Date Comparison: Scrape same location with different date ranges weekly. Track how pricing evolves as dates approach. Identify optimal booking windows.

Guest Count Sensitivity: Run searches varying adult/children counts for same property/dates. Analyze per-person pricing increments and family-friendly discount patterns.

Historical Database: Archive scraped data with timestamps. Calculate average nightly rates over time, track property additions/removals, measure market growth.

Enrichment Integration: Combine with property detail scrapers for amenities, reviews, and photos. Merge with local event calendars to correlate pricing with major events.

Quality Checks: Flag anomalies—properties with zero discounts when others show 20%, prices outside 2 standard deviations from mean, proximity data missing. Validate total_price calculations.

Refresh Cadence: Luxury rental pricing changes frequently. Weekly scraping captures promotional campaigns and seasonal adjustments. Daily scraping during peak booking seasons tracks high-velocity changes.

Best Practices

Systematic URL Building: For comprehensive market coverage, systematically vary URL parameters—all major neighborhoods in a city, standard date ranges (weekends, week-long stays), typical guest counts (couples, families).

Date Range Strategy: Scrape both near-term (next 30 days) for immediate pricing and far-term (6-12 months) for seasonal patterns. Mix weekday and weekend searches.

Data Validation: Implement checks ensuring nightly_price × nights ≈ total_price (accounting for cleaning fees in totals). Verify discount_percentage matches price reduction calculations.

Respectful Scraping: Space large runs over time. Avoid overwhelming PlumGuide with simultaneous requests. Sustainable practices ensure continued data access.

Conclusion

The PlumGuide Property Search Scraper transforms luxury vacation rental search data into actionable market intelligence. From dynamic pricing patterns to promotional strategies, this tool delivers insights for optimizing property performance, evaluating markets, and understanding high-end rental dynamics. Extract premium rental data today and gain competitive advantage in luxury hospitality.