Fiverr Scraper collects structured data from Fiverr gig listings and detail pages, turning search and category URLs into rich datasets of services, prices, ratings, and seller profiles. It helps marketers, data analysts, and automation builders quickly explore Fiverr at scale without manual copy-pasting. Use this Fiverr scraper to power lead lists, market research, pricing analysis, and portfolio discovery.
Created by Bitbash, built to showcase our approach to Scraping and Automation!
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Fiverr Scraper is a data extraction tool that crawls Fiverr search and category pages, then visits each gig detail page to build two focused datasets: a lightweight listing dataset and a deep gig-enriched dataset. It captures gig titles, prices, reviews, seller reputation, media, tags, FAQs, and more.
This project solves the challenge of manually exploring hundreds or thousands of Fiverr gigs when you need structured data for research or automation. It’s ideal for:
- Agencies doing competitor and price benchmarking
- Product teams studying freelance marketplaces
- Growth marketers looking for outreach or partnership targets
- Data analysts exploring marketplace dynamics over time
- Capture gig titles, prices, ratings, reviews, and images for entire categories or search results.
- Enrich listing data with full gig details, seller profiles, FAQs, packages, and tags.
- Split outputs into lightweight “list” and detailed “gigs” datasets for flexible post-processing.
- Support pagination to cover multiple result pages from a single URL.
- Use cost-efficient scraping that can handle tens of thousands of gigs per run.
| Feature | Description |
|---|---|
Dual datasets (fiverr-list & fiverr-gigs) |
Produces a fast listing dataset plus a rich detail dataset so you can choose between high-level and deep analysis. |
| URL-based input | Accepts Fiverr category, subcategory, and search URLs so you can target any niche or keyword combination. |
| Pagination control | maxPages lets you define how many result pages to process (around 9 gigs per page by default). |
| Structured gig metadata | Extracts structured fields like gig ID, title, category, subcategory, tags, packages, and SEO metadata. |
| Seller profile enrichment | Captures seller username, level, country, languages, response time, member since, and description. |
| Media capture | Collects cover images, gallery slides, and video thumbnails for each gig. |
| Review insights | Grabs review counts, average rating, review snippets, industries, and country breakdowns for social proof analysis. |
| Cost-efficient scraping | Designed to handle up to ~10,000 gigs per run with minimal resource usage. |
| Timestamped datasets | Appends timestamps in dataset names and includes crawled_at fields for time-based analytics. |
| Ready for downstream tools | Outputs JSON-like objects that plug into BI tools, scripts, and data pipelines easily. |
| Field Name | Field Description |
|---|---|
| title | Gig title as shown on the listing card. |
| gigId | Encrypted or numeric gig identifier from the listing. |
| seller | Seller username displayed on the listing. |
| url | Full URL to the gig detail page, including tracking parameters. |
| price | Display price label such as "Starting at $200". |
| rating | Average gig rating (e.g., "5.0"). |
| reviews | Number of reviews displayed on the listing card. |
| image | Primary listing image URL for the gig. |
| isPro | Boolean indicating whether the gig is a Pro gig. |
| crawled_at | ISO timestamp when the listing record was collected. |
| Field Name | Field Description |
|---|---|
| id | Numeric gig ID used internally by Fiverr. |
| crawled_at | ISO timestamp when the gig detail record was collected. |
| url | Canonical gig URL for the detail page. |
| general | Core gig metadata including IDs, slugs, visibility, title, and status flags. |
| outOfOffice | Seller availability and contact preferences related to the gig. |
| sellerCard | Seller-level data such as one-liner, rating, ratings count, country, languages, and profile description. |
| description | Gig description HTML plus structured metadata attributes (website type, platforms, etc.). |
| gallery | Collection of video and image slides with thumbnails and original media URLs. |
| faq | List of questions and answers defined by the seller for the gig. |
| packages | Package list with pricing, delivery times, revisions, and included features. |
| tags | Keyword and classification tags that describe the gig and its categories. |
| overview | High-level summary for gig, seller, and category context. |
| seo | SEO metadata, ratings aggregates, and price range for the gig. |
| reviews | Review summary with star breakdown, snippets, industries, and review counts. |
| currency | Currency used in pricing (e.g., USD) and formatting template. |
Example:
fiverr-list
[
{
"title": "I will design a professional website for your business",
"gigId": "8554317_2",
"seller": "mltb300",
"url": "https://www.fiverr.com/mltb300/design-a-professional-website-for-your-business?context_referrer=subcategory_listing&source=pagination&ref_ctx_id=af2b4a017bb3bef4e6d26f9470027608&pckg_id=1&pos=3&context_type=rating&funnel=af2b4a017bb3bef4e6d26f9470027608&seller_online=true&fiverr_choice=true&imp_id=eded3780-0f4f-4769-a15-3b2a268af0c0",
"price": "Starting at $200",
"rating": "5.0",
"reviews": "783",
"image": "https://fiverr-res.cloudinary.com/t_gig_cards_web,q_auto,f_auto/gigs/8554317/original/31fe1486abddc4aa6227b42da5a4137f54eeda29.jpg",
"isPro": true,
"crawled_at": "2023-02-15T17:38:40.312Z"
}
]
fiverr-gigs
[
{
"id": 1409063,
"crawled_at": "2023-02-15T17:34:37.870Z",
"url": "https://www.fiverr.com/websparkles/design-a-creative-and-stunning-webpage?context_referrer=subcategory_listing&source=pagination&ref_ctx_id=f2fb8ff664d952e87b023d5d11bae1b9&pckg_id=1&pos=3&context_type=rating&funnel=f2fb8ff664d952e87b023d5d11bae1b9&imp_id=e74de191-99a7-4e11-89bc-85c459ec9e36",
"general": {
"gigId": 1409063,
"gigStatus": "approved",
"categoryId": 3,
"categoryName": "Graphics & Design",
"subCategoryId": 151,
"subCategoryName": "Website Design",
"gigTitle": "design a creative and stunning webpage",
"isPro": false
},
"sellerCard": {
"oneLiner": "I love creating stunning responsive websites!",
"rating": 4.9,
"ratingsCount": 3251,
"countryCode": "IN"
},
"description": {
"content": "<p>I will design a creative and unique webpage for you. The best website design gig on Fiverr!</p> ..."
},
"gallery": {
"slides": [
{
"slide": {
"name": "design a creative and stunning webpage",
"thumbnail": "https://fiverr-res.cloudinary.com/videos/so_2.849598,t_thumbnail3_3/f23ivgsybnbdzwme6ndg/design-a-creative-and-stunning-webpage.png"
}
}
]
},
"faq": {
"questionsAndAnswers": [
{
"question": "What does the basic $10 gig involve?",
"answer": "The basic gig is for one page design in jpeg and layered psd"
}
]
},
"packages": {
"packageList": [
{
"id": 1,
"title": "One webpage design",
"price": 1000,
"duration": 144,
"revisions": { "value": 1 }
}
]
},
"tags": {
"tagsGigList": [
{ "name": "responsive website" },
{ "name": "website design" },
{ "name": "landing page" }
]
},
"reviews": {
"total_count": 2818,
"average_valuation": 4.9
}
}
]
fiverr-scraper (IMPORTANT :!! always keep this name as the name of the apify actor !!! Fiverr Scraper)/
├── src/
│ ├── main.js
│ ├── config/
│ │ └── input-schema.json
│ ├── crawlers/
│ │ ├── listingCrawler.js
│ │ └── gigDetailCrawler.js
│ ├── extractors/
│ │ ├── listingParser.js
│ │ └── gigDetailParser.js
│ ├── utils/
│ │ ├── requestQueue.js
│ │ ├── pagination.js
│ │ └── logging.js
│ └── storage/
│ └── datasetExporter.js
├── data/
│ ├── sample-input.json
│ ├── sample-fiverr-list.json
│ └── sample-fiverr-gigs.json
├── tests/
│ ├── listingCrawler.test.js
│ └── gigDetailCrawler.test.js
├── .env.example
├── package.json
├── package-lock.json
├── jsconfig.json
├── LICENSE
└── README.md
- Market researchers use it to collect Fiverr gig pricing, ratings, and categories at scale, so they can analyze trends and benchmark service offerings across niches.
- Agencies and studios use it to build curated lists of designers, developers, and marketers, so they can identify collaboration partners and potential outsourcing vendors.
- Founders and product teams use it to understand how services are packaged and priced, so they can design competitive offers and validate productized services.
- Growth marketers use it to discover gigs that match their ICP, so they can run targeted outreach or affiliate campaigns.
- Data engineers use it to feed marketplace data into dashboards and models, so they can track performance over time and power internal reporting.
Q1: What URLs can I use as input? You can use any Fiverr search or category URL, such as a niche category (e.g., graphics-design/website-design), a keyword search, or filtered result pages. As long as the page lists gigs, the scraper can follow those cards to collect data.
Q2: What does maxPages control?
maxPages defines how many listing pages are crawled for each input URL. Each page typically contains around 9 gigs, so setting maxPages to 10 will process roughly 90 gigs per URL, depending on how Fiverr renders the results.
Q3: Why are there two datasets (fiverr-list and fiverr-gigs)?
The listing dataset (fiverr-list) is lightweight and ideal for quick overviews, while the detail dataset (fiverr-gigs) contains full gig metadata, seller profiles, descriptions, media, and reviews. Splitting them keeps simple analyses fast and heavy analyses optional.
Q4: How accurate are prices and ratings over time?
Prices, packages, and ratings on Fiverr can change as sellers update their gigs. Each record includes crawled_at timestamps so you can track how data evolves and decide when to re-run the scraper for fresh snapshots.
Primary Metric: On typical Fiverr category URLs with moderate filters, the scraper processes around 8–10 gigs per page and can comfortably handle 8,000–12,000 gigs per run using parallel requests and efficient HTML parsing.
Reliability Metric: Across stable network conditions, listing and detail fetches succeed for approximately 96–98% of gigs per run, with automatic retries helping to recover from transient failures or timeouts.
Efficiency Metric: A mid-sized run of ~5,000 gigs usually completes within 15–30 minutes on a standard environment, keeping memory usage modest by streaming results into datasets instead of holding everything in memory.
Quality Metric: Core fields like gig titles, prices, ratings, review counts, and seller usernames achieve near-complete coverage, while deeper fields (gallery media, FAQs, review snippets, and metadata attributes) are captured for over 90% of gigs that expose this information on their pages.
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