Fragrantica.com Scraper

What does Fragrantica Designer Perfume Scraper do?

Fragrantica Designer Perfume Scraper is a Fragrantica data extractor for collecting structured perfume listings from public designer pages such as Zara, Dior, Chanel, and other brands. Enter one designer page URL and the number of records you need to receive perfume names, release years, ratings, review counts, popularity signals, designer metadata, images, and direct perfume links in an Apify dataset.

The output is useful for fragrance catalog building, beauty market research, brand portfolio analysis, competitor monitoring, release-year research, and AI or reporting workflows that need consistent Fragrantica perfume data.

Why use Fragrantica Designer Perfume Scraper?

• Build fragrance catalogs - Collect a designer's perfume portfolio in a structured dataset without manual copy-paste.
• Compare brands - Run the Actor for several designer pages and compare portfolio size, launch years, ratings, reviews, and popularity signals.
• Monitor fragrance trends - Schedule repeat runs and compare datasets to identify new releases and changes in community interest.
• Support research and reporting - Export records as JSON, CSV, Excel, or XML for analysis, dashboards, and business reports.
• Automate downstream workflows - Connect completed runs to Google Sheets, Airtable, webhooks, Make, Zapier, or the Apify API.

What data can you extract from Fragrantica?

Each saved item represents one perfume associated with the selected designer page. Optional fields are omitted when Fragrantica does not publish a value.

Field	Type	Description
designer_name	String	Designer or brand name.
designer_url	String	Designer page used for the run.
designer_parent_company	String	Parent company when available.
designer_slug	String	Designer slug used by Fragrantica.
designer_is_niche	String	Niche-designer marker when available.
designer_is_celebrity	String	Celebrity-designer marker when available.
designer_is_natural_perfumery	String	Natural-perfumery marker when available.
designer_total_perfumes	Number	Total perfume count reported for the designer.
designer_first_year	Number	Earliest release year found in the collected records.
designer_latest_year	Number	Latest release year found in the collected records.
perfume_name	String	Perfume name.
perfume_url	String	Direct Fragrantica perfume page URL.
perfume_id	Number	Fragrantica perfume identifier.
perfume_slug	String	Perfume slug value.
image_url	String	Main perfume image URL.
year	Number	Release year when available.
gender	String	Gender label associated with the perfume.
reviews_count	Number	Primary review count.
rating_value	Number	Community rating value.
rating_rounded	Number	Rounded rating value.
popularity_score	Number	Overall popularity signal.
recent_popularity_score	Number	Recent popularity signal.
collection	String	Collection name when available.
group_id	Number	Fragrantica group identifier when available.
pageviews_7d	Number	Seven-day pageview signal.
pageviews_30d	Number	Thirty-day pageview signal.
pageviews_90d	Number	Ninety-day pageview signal.
popularity_compound_score	Number	Compound popularity metric.
url_*	String	Flattened localized perfume URL, such as url_en or url_fr.
reviews_*	Number	Flattened localized review count, such as reviews_en or reviews_fr.
source_page	Number	Source result page for the record.

How to use Fragrantica Designer Perfume Scraper

1. Open the Actor in Apify Console.
2. Enter a public Fragrantica designer page in startUrl.
3. Set results_wanted to the maximum number of perfume records to save.
4. Start the run and review the dataset preview.
5. Download the results or connect the dataset to your preferred workflow.

Input Parameters

Parameter	Type	Required	Default	Description
startUrl	String	Yes	https://www.fragrantica.com/designers/Zara.html	Public Fragrantica designer page URL, for example a Zara or Dior designer page.
results_wanted	Integer	No	20	Maximum number of perfume records to save. The minimum value is 1.

Output Data

The Actor saves one dataset item per perfume. Records are deduplicated and empty values are omitted, which keeps exports easier to filter and analyze.

Usage Examples

Basic Designer Collection

Collect 20 perfumes from a designer page for a quick test run.

{
  "startUrl": "https://www.fragrantica.com/designers/Zara.html",
  "results_wanted": 20
}

Collect a Larger Designer Portfolio

Increase the result limit when you need a broader view of a designer's catalog.

{
  "startUrl": "https://www.fragrantica.com/designers/Dior.html",
  "results_wanted": 100
}

Research a Different Brand

Run the same Actor for another public designer page to compare brands or build a multi-brand dataset across separate runs.

{
  "startUrl": "https://www.fragrantica.com/designers/Chanel.html",
  "results_wanted": 250
}

Sample Output

The following example shows a typical dataset item. Fields that are unavailable on the source page may be omitted.

{
  "designer_name": "Zara",
  "designer_url": "https://www.fragrantica.com/designers/Zara.html",
  "designer_parent_company": "Inditex",
  "designer_slug": "Zara",
  "designer_total_perfumes": 1201,
  "designer_first_year": 2012,
  "designer_latest_year": 2025,
  "perfume_name": "Sunrise On The Red Sand Dunes",
  "perfume_url": "https://www.fragrantica.com/perfume/Zara/Sunrise-On-The-Red-Sand-Dunes-79102.html",
  "perfume_id": 79102,
  "perfume_slug": "Zara/Sunrise-On-The-Red-Sand-Dunes",
  "image_url": "https://fimgs.net/mdimg/perfume/m.79102.jpg",
  "year": 2023,
  "gender": "male",
  "reviews_count": 304,
  "rating_value": 4.288,
  "rating_rounded": 4,
  "popularity_score": 15394,
  "recent_popularity_score": 6320,
  "collection": "Men's Collection 2023",
  "group_id": 23,
  "pageviews_30d": 31062,
  "source_page": 1,
  "url_en": "https://www.fragrantica.com/perfume/Zara/Sunrise-On-The-Red-Sand-Dunes-79102.html",
  "reviews_en": 304
}

Tips for Best Results

• Use a designer URL - Start with a public URL matching the Fragrantica designer-page format, such as /designers/Zara.html.
• Test with a small limit - Use results_wanted: 20 to confirm the URL and dataset shape before larger runs.
• Scale the result limit - Increase results_wanted when you need more of the designer's portfolio. The Actor stops when the limit is reached or available data is exhausted.
• Keep brand runs separate - Use one run per designer when you want clean comparisons between brands.
• Expect optional fields - Ratings, release years, collection names, localized URLs, and popularity signals can be absent for individual records.
• Schedule repeat runs - Recurring runs can refresh a catalog or support trend monitoring over time.

Integrations and Export Formats

• Google Sheets - Review and compare fragrance records in a shared spreadsheet.
• Airtable - Build a searchable designer and perfume catalog.
• Webhooks - Notify another service after a run completes.
• Make or Zapier - Send new dataset results into reporting and automation workflows.
• Apify API - Start runs and retrieve dataset items programmatically.

Apify datasets can be downloaded as JSON, CSV, Excel, XML, and other supported formats.

Frequently Asked Questions

What pages are supported?

Public Fragrantica designer pages are supported. Pass the designer page URL in startUrl, such as https://www.fragrantica.com/designers/Zara.html.

Can I collect more than 20 perfumes?

Yes. Set results_wanted to any integer of 1 or higher. The Actor continues through available result pages until it reaches the requested limit or no more records are available.

Does the Actor collect perfume detail data?

The dataset includes perfume listing information and direct perfume page URLs, including names, identifiers, images, years, ratings, review counts, popularity values, and localized links when available.

Why are some fields missing?

Fields are omitted when Fragrantica does not publish a value for a particular designer or perfume. This is expected for optional metadata such as release year, collection, parent company, or localized review counts.

Are duplicate perfumes saved?

No. Records are deduplicated using the perfume URL, identifier, slug, or name when one of those values is available.

Can I schedule recurring Fragrantica data collection?

Yes. Create an Apify schedule to run the Actor hourly, daily, weekly, or at another interval, then compare the resulting datasets for catalog and trend monitoring.

Is it legal to collect Fragrantica data?

You are responsible for complying with Fragrantica's terms, applicable laws, privacy requirements, and any restrictions on using or redistributing collected data. Use the Actor for legitimate research and business workflows involving publicly available information.

Related Actors

• Sephora Scraper - Collect beauty product listings, prices, ratings, reviews, availability, and direct product links for beauty market research.
• Sephora Reviews Scraper - Collect detailed Sephora product reviews and ratings for sentiment analysis and competitive research.

Support

For issues, feature requests, or reports about changed Fragrantica fields, use the Issues or support options on the Actor page in Apify Console.

Legal Notice

This Actor is intended for legitimate collection and analysis of publicly available information. You are responsible for complying with Fragrantica's terms of service and all applicable laws. Do not use collected data for unlawful purposes or in ways that violate privacy, intellectual property, or redistribution requirements.