Download the Body Wash Category Shopee Dataset (October 2024)

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Explore a historical sample of Shopee Singapore body-wash listings. The October 2024 workbook contains 240 listings from 125 distinct shop IDs, with 21 fields. Every record uses SGD and carries an updateTime of October 21, 2024.

October 2024 Shopee Singapore body-wash dataset cover with body-care brand logos, towels and bottles.
Original cover for the October 2024 Singapore archive. Its analysis themes are not measured findings; the workbook is a listing snapshot dated October 21, 2024.

What is in the Singapore archive?

The file is 11012307-BodyWash-singapore.xlsx. Its single worksheet, Sheet1, contains one header row and 240 data rows across columns A–U. Every shop-and-item ID pair is unique within the file. The category label comes from the filename; there is no separate category column.

This is a product-listing snapshot, with no documented sampling method or guarantee of complete category coverage. The titles include liquid washes, refill packs and bar soaps. Review product form and pack size before grouping these listings together.

Fields and what they can support

  • Product and seller identity: name, url, imageUrl, itemId, shopId, shop_name and brand. Preserve IDs as text and retain both shop and item ID when matching listings.
  • Country, currency and date: country, currency and updateTime identify Singapore, Singapore dollars and the recorded snapshot date, stored as 10/21/2024.
  • Prices: price, price_before_discount, discountPercent, price_min, price_max, price_min_before_discount and price_max_before_discount. These values need variant checks before a promotion or unit-price comparison.
  • Ratings and displayed counters: rating, rating_count, sold and historySold. The file does not define the reporting window of sold; it cannot be labelled October orders or treated as verified transaction data.

Three checks before comparing offers

  • 83 listings have different minimum and maximum prices. A product title can describe several sizes or variants. The file has no field mapping each size to a particular price.
  • 79 reference prices are zero. Treat a zero price_before_discount as unavailable for discount calculations. Exclude those rows from calculations that divide by the reference price.
  • 33 brand values are blank. Keep an unknown-brand group and document any later normalization. Do not silently infer a brand from every product title.

The workbook has no dedicated volume, weight or pack-count fields. Refill packs labelled in grams cannot automatically be compared with millilitre bottles, and a bar soap cannot be assigned a price per 100 ml without additional information.

A worked reference-price check

Worksheet row 2 is a NARD body-wash listing from shop 567539088, item 14817529320. Its title lists 500 ml / 1,000 ml. The recorded price is SGD 13.33, the reference price is SGD 23, and the price range is SGD 13.33–19.04.

For the two recorded prices, (23 − 13.33) ÷ 23 × 100 = 42.04%, which rounds to the stored discountPercent of 42. This checks the arithmetic of the displayed reference-price reduction. It does not prove the item previously sold at SGD 23 or that a buyer could obtain the same checkout price.

The row does not map SGD 13.33 to either the 500 ml or 1,000 ml option. Do not calculate a definitive price per 100 ml until the selected size, pack count and corresponding price have been confirmed.

For another example of an ambiguous listing price, see the December 2024 Thailand shampoo archive. Its worked example explains why a stored 1 THB price does not establish the price of the advertised two-bottle pack. Keep that THB snapshot separate from this October SGD sample; the two files are not a matched comparison across markets or periods.

What this snapshot does not establish

The cover lists market share, brand performance, customer preferences and pricing trends as possible analysis themes. This one file does not establish those conclusions: it lacks a full-market denominator, customer research, verified orders and repeated observations over time. Counts and sales counters describe the captured sample.

Keep the original workbook and record cleaning choices in a separate copy. The guide to analyzing Shopee data explains how to separate listing observations from estimates. For current collection requirements, specify the market, fields, refresh schedule and validation sample through our Shopee data scraping service.

Request the October 2024 Singapore workbook

  1. Fill Out the Form: Enter your details to request this historical Singapore workbook. Submitting the form does not customize the archived records.
  2. Submit the Form: After filling, submit the form. Ensure all provided information is accurate to avoid delays.
  3. Check Your Email: Look for the email titled “Your Shopee Data For Is Ready For Download”. Allow time for delivery and check your spam folder if it does not arrive.
  4. Download from Email: Open the email received, click on the download link provided within to access the data set file.
  5. Open & Review Data: After downloading, open the file in your preferred spreadsheet software to start analyzing the data.

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