Customereye

Katieloxton

Apparel & Fashion • United Kingdomwww.katieloxton.com

Review data last updated .

Based on public reviews and response behavior.

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684 days of reviews, with a sparse monthly review flow. Busiest month: 9% of reviews. Languages: en 100%.

Overall Score

47/100
+40.0 vs. last month2.46 ★ average rating
47/100 from public reviews over 22 months, moderate confidence.

Apparel & Fashion average: score 61.3, rating 4.02 stars, reply rate 35.3%, over 3,009 ranked companies · benchmark 4 Nov 2026

Score

47.2

Industry average 61.3

14.1 below average

Rating

2.46

Industry average 4.02

1.56 below average

Reply rate

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Industry average 35.3%

not measured

Competitive Performance Rank

Among ranked Apparel & Fashion companies

#2492of 3009 ranked in Apparel & Fashion
Top 83% · Bottom Tierup 1120 from last month
#1 (best)#3009 (worst)
#2490Peer
#2491Peer
#2492This company
#2493Peer
#2494Peer

Only companies with enough recent, scoreable reviews are ranked.

Overall Customer Sentiment

Below Average

55% of reviews positive, 45% negative

55%
positive
  • Positive55%
  • Neutral0%
  • Negative45%

Sentiment Balance

Covering October 2026, not the company's full review history.

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positive
  • Positive—
  • Neutral—
  • Negative—

Takeaway: Positive sentiment accounts for 40% of reviews in this period, with 60% negative and 0% neutral.

Sentiment Trend Over Time

Review activity
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Theme Distribution

Share of theme mentions

Delivery Shipping
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Customer Support
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Loyalty
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Response Speed
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Problem Resolution
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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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