I’ve been tracking non-promotional beauty prices across major retailers in Singapore and compiled a January 2026 dataset that might be useful for analysis or projects.
Coverage includes:
- SKU-level prices (old vs new)
- Category and subcategory classification
- Brand and product names
- Variant / size information
- Price movement (%) month-to-month
- Coverage across Sephora and Takashimaya Singapore
The data captures real shelf prices (excluding temporary promotions), so it reflects structural pricing changes rather than sale events.
Some interesting observations from January:
- Skincare saw the largest increases (around +12% on average)
- Luxury brands drove most of the inflation
- Fragrance gift sets declined after the holiday period
- Pricing changes were highly concentrated by category
I built this mainly for retail and pricing analysis, but it could also be useful for:
- consumer price studies
- retail strategy research
- brand positioning analysis
- demand / elasticity modelling
- data visualization projects
Link in the comment.
submitted by /u/IntelligentHome2342
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