Stellenbeschreibung:

Description

I am looking for support in collecting structured shop-level data from Etsy jewelry shops (focus: USA & Europe). The goal is to create a clean and well-structured dataset that I can later analyze in Python and R. The process should be transparent and reproducible, ideally using tools like Octoparse or the Etsy API.


Scope of Work
• Collect approx. 5,000 Etsy jewelry shops (shop-level).
• Focus only on shops located in USA and Europe.
• Provide the dataset in CSV or Excel format, with clear and consistent headers.


Required Variables (shop-level)
• shop_id (string, unique identifier)
• shop_name (string)
• shop_url (string)
• country_code (ISO-2, e.g. US, DE)
• region (Europe/USA)
• opened_on (YYYY-MM-DD)
• shop_age_years (float; can be calculated later from opened_on)
• admirers (int)
• total_sales (int; past sales)
• listings_count (int)
• avg_rating (float)
• review_count (int)
• median_price_eur (float; median of product prices per shop, converted to EUR)


Additional Notes

The workflow should be documented briefly (screenshots or short explanation) so I can understand and, if needed, replicate the process.

Ideally done with Octoparse or similar tools, so I can later build on it myself.

I will later select a sample of 1,000 shops from the dataset for further analysis.


Deliverables
• Clean dataset (CSV/Excel) with all required variables.
• Short documentation of the process.
• Reliable and transparent work.

NOTE / HINWEIS:

EN: Please refer to Fuchsjobs for the source of your application

DE: Bitte erwähne Fuchsjobs, als Quelle Deiner Bewerbung