Customereye

FORCHICS

Beauty & Wellness • United Statesforchics.com

Review data last updated .

Based on public reviews and response behavior.

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878 reviews over 2,681 days (about 10 per month). Busiest month: 8% of reviews. Languages: en 99%, fr 1%, es 0%.

Overall Score

67/100
−33.4 vs. last month3.13 ★ average rating · 878 reviews
67/100 from 878 reviews over 64 months, high confidence.

Beauty & Wellness average: score 65.5, rating 4.29 stars, reply rate 39.2%, over 2,500 ranked companies · benchmark 23 Oct 2026

Score

66.7

Industry average 65.5

1.3 above average

Rating

3.13

Industry average 4.29

1.16 below average

Reply rate

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Industry average 39.2%

not measured

Competitive Performance Rank

Among ranked Beauty & Wellness companies

#1231of 2500 ranked in Beauty & Wellness
Top 49% · Upper Halfdown 271 from last month
#1 (best)#2500 (worst)
#1229Peer
#1230Peer
#1231This company
#1232Peer
#1233Peer

Only companies with enough recent, scoreable reviews are ranked.

Overall Customer Sentiment

Above Average

55% of reviews positive, 44% negative

55%
positive
  • Positive55%
  • Neutral1%
  • Negative44%

Sentiment Balance

Covering July 2026 — 3 reviews, not the company's full review history.

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positive
  • Positive—
  • Neutral—
  • Negative—

Takeaway: Positive sentiment accounts for 33% of reviews in this period, with 67% negative and 0% neutral.

Sentiment Trend Over Time

Reviews (Count)
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Theme Distribution

Share of theme mentions

Delivery Shipping
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Loyalty
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Pricing
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Product Quality
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Value For Money
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How this analysis was produced

The figures on this page come from the most recent reviews this company received, up to a per-company limit, so the period they cover depends on how quickly this company receives reviews: a busy company's sample may span only a few weeks, a quieter company's may span years. The window actually covered is stated above with the score. The analysis identifies patterns across many reviews at once and is not intended as a judgement on any individual one. For a complete analysis covering all available feedback, using AI rather than automated rules, .

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