Customereye

dollarsbux.com

Paid Surveys & Rewards • United Kingdomdollarsbux.com

Review data last updated .

Based on public reviews and response behavior.

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1,358 days of reviews, with a sparse monthly review flow. Busiest month: 62% of reviews — one month dominates this sample. Languages: en 88%, es 3%, ar 2%.

Overall Score

55/100
4.59 ★ average rating
55/100 from public reviews over 4 months, limited confidence. no reviews in the last 12 months. one month holds 62% of the reviews.

These figures describe an earlier period, not the last 12 months.

Paid Surveys & Rewards average: score 61.5, rating 4.15 stars, reply rate 30.4%, over 142 ranked companies · benchmark 5 Nov 2026

Score

55.2

Industry average 61.5

6.3 below average

Rating

4.59

Industry average 4.15

0.44 above average

Reply rate

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Industry average 30.4%

not measured

Competitive Performance Rank

Not ranked

no reviews in the last 12 months

Overall Customer Sentiment

Below Average

85% of reviews positive, 15% negative

85%
positive
  • Positive85%
  • Neutral0%
  • Negative15%

Sentiment Balance

Covering August 2023, not the company's full review history.

—
positive
  • Positive—
  • Neutral—
  • Negative—

Takeaway: Positive sentiment accounts for 67% of reviews in this period, with 33% negative and 0% neutral.

Sentiment Trend Over Time

Review activity
HiddenHidden

Half or more of these reviews arrived in a single month

Theme Distribution

Share of theme mentions

Product Quality
Hidden
Pricing
Hidden
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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