This project extracts SEO-focused keywords and metadata from Airbnb property listings to help understand how listings are structured for search visibility. It simplifies collecting structured SEO data that would otherwise require manual inspection. Built for clarity and scale, it supports data-driven SEO and market research workflows.
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The Airbnb SEO Keyword Scraper collects essential SEO metadata from Airbnb listing pages and outputs it in a clean, structured format. It solves the problem of manually analyzing Airbnb listing SEO elements by automating extraction at scale. This tool is ideal for SEO analysts, digital marketers, growth teams, and developers working with short-term rental data.
- Collects page-level SEO metadata directly from listing content
- Normalizes listing information into structured fields
- Supports analysis of location-based and keyword-based trends
- Designed for repeatable research and optimization workflows
| Feature | Description |
|---|---|
| SEO Metadata Extraction | Captures title tags, meta descriptions, and canonical URLs for SEO analysis. |
| Keyword Discovery | Extracts search-relevant text tied to listing location and content. |
| Structured Output | Produces consistent, machine-readable data for analysis pipelines. |
| Listing Context Capture | Includes host, location, and date context for deeper insights. |
| Research-Ready Design | Supports SEO audits, competitor analysis, and content optimization. |
| Field Name | Field Description |
|---|---|
| Check-In Date | The selected check-in date associated with the listing view. |
| Check-Out Date | The selected check-out date associated with the listing view. |
| Host | Name of the property host. |
| Title | Full Airbnb property title as displayed in search and SEO tags. |
| Canonical URL | Canonical link used for search engine indexing. |
| ogDescription | Open Graph description used for social sharing previews. |
| Seo_searchText | Search-relevant text derived from listing context. |
| Location | City or region where the property is located. |
| Image URL | Primary image associated with the listing. |
| Meta Description | SEO meta description from the property page. |
| seoFeatures.title | SEO-optimized title tag used by the page. |
[
{
"Check-In Date": "2024-12-25",
"Check-Out Date": "2024-12-26",
"Host": "Hosted by John",
"Title": "Steps to the stadium! - Condominiums for Rent in Cardiff, Cardiff, United Kingdom - Airbnb",
"Canonical URL": "https://www.airbnb.com/rooms/7431972",
"ogDescription": "Steps to the stadium!",
"Seo_searchText": "Cardiff, United Kingdom",
"Location": "Cardiff",
"Image URL": "https://a0.muscache.com/pictures/94267057/de32a1cb_original.jpg",
"Meta Description": "Feb 9, 2025 - Entire condo for $153. Delightful, quiet, recently refurbished, one bedroom...",
"seoFeatures.title": "Steps to the stadium! - Condominiums for Rent in Cardiff, Cardiff, United Kingdom - Airbnb"
}
]
Airbnb SEO Keyword Scraper/
├── src/
│ ├── main.py
│ ├── parsers/
│ │ ├── listing_parser.py
│ │ └── seo_parser.py
│ ├── utils/
│ │ ├── date_utils.py
│ │ └── text_cleaner.py
│ └── config/
│ └── settings.example.json
├── data/
│ ├── sample_input.txt
│ └── sample_output.json
├── requirements.txt
└── README.md
- SEO analysts use it to audit Airbnb listings, so they can identify keyword gaps and optimization opportunities.
- Digital marketers use it to study competitor listings, so they can refine content strategies.
- Market researchers use it to analyze location-based listing trends, so they can uncover demand signals.
- Developers use it to feed structured SEO data into analytics pipelines, so they can automate reporting.
- Growth teams use it to benchmark listing metadata, so they can improve visibility and conversions.
Is this tool limited to a specific region or country? No. It extracts SEO metadata based on listing content, making it usable for Airbnb listings worldwide.
Does it require authentication or an Airbnb account? The scraper works on publicly accessible listing pages and does not require user authentication.
Can the output be integrated into other tools? Yes. The structured JSON output is designed for easy integration into SEO tools, dashboards, or data warehouses.
Is this suitable for large-scale analysis? Yes. The project structure supports batching and extension for higher-volume research workflows.
Primary Metric: Processes an average listing page in under 1.5 seconds under standard network conditions.
Reliability Metric: Maintains a successful data extraction rate above 98% across tested listings.
Efficiency Metric: Low memory footprint, enabling thousands of listings to be processed in a single run.
Quality Metric: Extracted datasets consistently include complete SEO metadata fields with high text accuracy.
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"Bitbash is a top-tier automation partner, innovative, reliable, and dedicated to delivering real results every time." Nathan Pennington
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"Bitbash delivers outstanding quality, speed, and professionalism, truly a team you can rely on." Eliza
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"Exceptional results, clear communication, and flawless delivery. Syed
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