What 1,126 Formula-Review URLs Reveal
The chart shows word-based mention counts after deduplication and removal of one standalone applicator-kit listing. It does not measure sentiment, prevalence in the market, or what a representative shopper thinks.
Read this before the chart
The scraper intentionally combined recent-all reviews with rating-stratified helpful-review slices. Rows were then deduplicated by review URL, and one standalone tanning-mitt kit was excluded from formula findings. Theme tags are word-based matches, not sentiment labels. One review can mention several themes, so counts overlap.
The most frequent word-based tags
The source capture contained 1,684 rows and 1,175 unique review URLs. We removed 58 captured rows (49 unique URLs) from one standalone applicator-kit listing. The resulting formula subset contains 1,626 captured rows, 1,126 unique URLs, 1,125 with text, and 1,116 marked verified.
Sampling mix and rating distribution
After deduplication, 866 formula-review URLs (76.9%) appeared only in rating-filtered helpful slices, 92 (8.2%) appeared only in recent-all or validation slices, and 168 (14.9%) appeared in both. This three-way membership view avoids assigning an overlapping URL to whichever slice happened to be retained first. The deliberate stratification supports issue discovery, not natural rating prevalence.
| Rating | URLs | Share |
|---|---|---|
| 1 star | 198 | 17.6% |
| 2 star | 187 | 16.6% |
| 3 star | 207 | 18.4% |
| 4 star | 237 | 21.0% |
| 5 star | 297 | 26.4% |
What changed in our editorial model
Format comes before brand
Mousse, drops, lotion, mist, and express formulas ask for different technique. Our finder now resolves that choice before it recommends a product.
Fit beats a universal winner
Skin tone, face or body use, timing, and tolerance for scent or transfer can outweigh a two-point difference in the overall score.
Drawbacks stay visible
Every review page shows when to skip a product and what we verified near the verdict instead of burying drawbacks below a promotional summary.
Evidence boundary
- This is: a stratified, structured analysis of public formula-review text and product surfaces.
- This is not: a clinical study, representative survey, natural rating distribution, sentiment model, sales ranking, or hands-on wear test.
- Unit of analysis: unique review URLs, not a verified count of unique people.
- Accessory exclusion: the standalone mitt-kit listing is reported above but excluded from formula theme counts.
- Retailer totals: displayed only as retailer context and never substituted for our analyzed review set.
- Reproducibility: the public theme summary is available as JSON; the scoring method is on the methodology page.
Editorial implication
The best-X page should work like a decision system: answer the shopper's use case, show the comparison logic, expose the evidence, and state where the evidence stops. That is the July standard across TheTanList.