Customereye

Swish Fibre

Software & Web Services • United Kingdomswishfibre.com

Review data last updated .

Based on public reviews and response behavior.

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600 reviews over 260 days (about 70 per month). Busiest month: 20% of reviews.

Overall Score

69/100
−8.6 vs. last month4.60 ★ average rating · 600 reviews
69/100 from 600 reviews over 9 months, high confidence.

Software & Web Services average: score 61.8, rating 4.15 stars, reply rate 34.4%, over 3,145 ranked companies · benchmark 24 Oct 2026

Score

69.4

Industry average 61.8

7.6 above average

Rating

4.60

Industry average 4.15

0.45 above average

Reply rate

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Industry average 34.4%

not measured

Competitive Performance Rank

Among ranked Software & Web Services companies

#1077of 3145 ranked in Software & Web Services
Top 34% · Upper Halfdown 56 from last month
#1 (best)#3145 (worst)
#1075Peer
#1076Peer
#1077This company
#1078Peer
#1079Peer

Only companies with enough recent, scoreable reviews are ranked.

Overall Customer Sentiment

Above Average

87% of reviews positive, 13% negative

87%
positive
  • Positive87%
  • Neutral1%
  • Negative13%

Sentiment Balance

Covering November 2024 — 36 reviews, not the company's full review history.

—
positive
  • Positive—
  • Neutral—
  • Negative—

Takeaway: Positive sentiment accounts for 81% of reviews in this period, with 19% negative and 0% neutral.

Sentiment Trend Over Time

Reviews (Count)
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Theme Distribution

Share of theme mentions

Customer Support
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Product Quality
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Response Speed
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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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