Customereye

opus card

Finance & Insurance • United Kingdomwww.opuscard.co.uk

Review data last updated .

Based on public reviews and response behavior.

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100 reviews over 2,634 days (about 1.2 per month). Busiest month: 6% of reviews. Languages: en 99%, cs 1%.

Overall Score

73/100
3.03 ★ average rating · 100 reviews
73/100 from 100 reviews over 12 months, moderate confidence.

Finance & Insurance average: score 63.6, rating 4.19 stars, reply rate 46.7%, over 2,895 ranked companies · benchmark 2 Nov 2026

Score

73.2

Industry average 63.6

9.6 above average

Rating

3.03

Industry average 4.19

1.16 below average

Reply rate

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Industry average 46.7%

not measured

Competitive Performance Rank

Among ranked Finance & Insurance companies

#815of 2895 ranked in Finance & Insurance
Top 28% · Upper Half
#1 (best)#2895 (worst)
#813Peer
#814Peer
#815This company
#816Peer
#817Peer

Only companies with enough recent, scoreable reviews are ranked.

Overall Customer Sentiment

Above Average

64% of reviews positive, 34% negative

64%
positive
  • Positive64%
  • Neutral2%
  • Negative34%

Sentiment Balance

Covering March 2024 — 4 reviews, not the company's full review history.

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positive
  • Positive—
  • Neutral—
  • Negative—

Takeaway: Positive sentiment accounts for 100% of reviews in this period, with 0% 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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Customer Support
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Product Quality
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Communication
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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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