Customereye

ZOUSZ

Beauty & Wellnesszousz.com

Review data last updated .

Based on public reviews and response behavior.

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100 reviews over 767 days (about 4 per month). Busiest month: 15% of reviews. Languages: en 99%, it 1%.

Overall Score

79/100
−28.6 vs. last month4.34 ★ average rating · 100 reviews
79/100 from 100 reviews over 12 months, moderate confidence.

Beauty & Wellness average: score 66.1, rating 4.34 stars, reply rate 39.5%, over 2,431 ranked companies · benchmark 24 Oct 2026

Score

79.0

Industry average 66.1

12.9 above average

Rating

4.34

Industry average 4.34

in line with average

Reply rate

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Industry average 39.5%

not measured

Competitive Performance Rank

Among ranked Beauty & Wellness companies

#410of 2431 ranked in Beauty & Wellness
Top 17% · Top Tierdown 343 from last month
#1 (best)#2431 (worst)
#408Peer
#409Peer
#410This company
#411Peer
#412Peer

Only companies with enough recent, scoreable reviews are ranked.

Overall Customer Sentiment

Category Leader

78% of reviews positive, 22% negative

78%
positive
  • Positive78%
  • Neutral0%
  • Negative22%

Sentiment Balance

Covering September 2026 — 7 reviews, not the company's full review history.

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positive
  • Positive—
  • Neutral—
  • Negative—

Takeaway: Positive sentiment accounts for 71% of reviews in this period, with 29% negative and 0% neutral.

Sentiment Trend Over Time

Reviews (Count)
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Theme Distribution

Share of theme mentions

Product Quality
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Customer Support
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Delivery Shipping
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Loyalty
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Communication
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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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