Customereye

OOFOS

Apparel & Fashion • United Stateswww.oofos.com

Review data last updated .

Based on public reviews and response behavior.

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200 reviews over 978 days (about 6.2 per month). Busiest month: 7% of reviews. Languages: en 91%, nl 6%, fr 2%.

Overall Score

30/100
+21.3 vs. last month2.29 ★ average rating · 200 reviews
30/100 from 200 reviews over 25 months, moderate confidence.

Apparel & Fashion average: score 64.5, rating 4.25 stars, reply rate 38.3%, over 2,361 ranked companies · benchmark 30 Oct 2026

Score

30.2

Industry average 64.5

34.3 below average

Rating

2.29

Industry average 4.25

1.96 below average

Reply rate

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Industry average 38.3%

not measured

Competitive Performance Rank

Among ranked Apparel & Fashion companies

#2296of 2361 ranked in Apparel & Fashion
Top 97% · Bottom Tierup 27 from last month
#1 (best)#2361 (worst)
#2294Peer
#2295Peer
#2296This company
#2297Peer
#2298Peer

Only companies with enough recent, scoreable reviews are ranked.

Overall Customer Sentiment

Below Average

42% of reviews positive, 58% negative

42%
positive
  • Positive42%
  • Neutral1%
  • Negative58%

Sentiment Balance

Covering July 2026 — 9 reviews, not the company's full review history.

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positive
  • Positive—
  • Neutral—
  • Negative—

Takeaway: Positive sentiment accounts for 44% of reviews in this period, with 56% negative and 0% 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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Pricing
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Onboarding
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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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