Customereye

House of Amor

Beauty & Wellnessamorlashes.co.uk

Review data last updated .

Based on public reviews and response behavior.

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100 reviews over 588 days (about 5.2 per month). Busiest month: 14% of reviews. Languages: en 100%.

Overall Score

67/100
−58.4 vs. last month4.00 ★ average rating · 100 reviews
67/100 from 100 reviews over 12 months, moderate confidence.

Beauty & Wellness average: score 64.6, rating 4.22 stars, reply rate 38.6%, over 2,561 ranked companies · benchmark 23 Oct 2026

Score

66.9

Industry average 64.6

2.3 above average

Rating

4.00

Industry average 4.22

0.22 below average

Reply rate

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Industry average 38.6%

not measured

Competitive Performance Rank

Among ranked Beauty & Wellness companies

#1224of 2561 ranked in Beauty & Wellness
Top 48% · Upper Halfdown 73 from last month
#1 (best)#2561 (worst)
#1222Peer
#1223Peer
#1224This company
#1225Peer
#1226Peer

Only companies with enough recent, scoreable reviews are ranked.

Overall Customer Sentiment

Above Average

75% of reviews positive, 21% negative

75%
positive
  • Positive75%
  • Neutral4%
  • Negative21%

Sentiment Balance

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

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positive
  • Positive—
  • Neutral—
  • Negative—

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

Sentiment Trend Over Time

Reviews (Count)
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Theme Distribution

Share of theme mentions

Loyalty
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Delivery Shipping
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Product Quality
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Pricing
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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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