Customereye

Restaurant Kits

Food & Dining • United Kingdomrestaurantkitsuk.com

Review data last updated .

Based on public reviews and response behavior.

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100 reviews over 1,701 days (about 1.8 per month). Busiest month: 33% of reviews. Languages: en 97%, unknown 3%.

Overall Score

87/100
−12.1 vs. last month4.67 ★ average rating · 100 reviews
87/100 from 100 reviews over 4 months, moderate confidence.

Food & Dining average: score 52.0, rating 3.33 stars, reply rate 18.6%, over 391 ranked companies · benchmark 30 Oct 2026

Score

86.9

Industry average 52.0

34.9 above average

Rating

4.67

Industry average 3.33

1.34 above average

Reply rate

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Industry average 18.6%

not measured

Competitive Performance Rank

Among ranked Food & Dining companies

#7of 391 ranked in Food & Dining
Top 2% · Top Tierdown 13 from last month
#1 (best)#391 (worst)
#5Peer
#6Peer
#7This company
#8Peer
#9Peer

Only companies with enough recent, scoreable reviews are ranked.

Overall Customer Sentiment

Category Leader

90% of reviews positive, 9% negative

90%
positive
  • Positive90%
  • Neutral1%
  • Negative9%

Sentiment Balance

Covering October 2021 — 33 reviews, not the company's full review history.

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positive
  • Positive—
  • Neutral—
  • Negative—

Takeaway: Positive sentiment accounts for 88% of reviews in this period, with 12% negative and 0% neutral.

Sentiment Trend Over Time

Reviews (Count)
HiddenHidden

Theme Distribution

Share of theme mentions

Onboarding
Hidden
Product Quality
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Delivery Shipping
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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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