Customereye

Chirp

Media & Content • United Stateschirpbooks.com

Review data last updated .

Based on public reviews and response behavior.

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100 reviews over 1,176 days (about 2.6 per month). Busiest month: 32% of reviews. Languages: en 96%, unknown 3%, da 1%.

Overall Score

68/100
−9.3 vs. last month4.44 ★ average rating · 100 reviews
68/100 from 100 reviews over 4 months, moderate confidence.

Media & Content average: score 60.5, rating 4.02 stars, reply rate 31.2%, over 776 ranked companies · benchmark 30 Oct 2026

Score

68.1

Industry average 60.5

7.6 above average

Rating

4.44

Industry average 4.02

0.42 above average

Reply rate

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Industry average 31.2%

not measured

Competitive Performance Rank

Among ranked Media & Content companies

#271of 776 ranked in Media & Content
Top 35% · Upper Halfdown 34 from last month
#1 (best)#776 (worst)
#269Peer
#270Peer
#271This company
#272Peer
#273Peer

Only companies with enough recent, scoreable reviews are ranked.

Overall Customer Sentiment

Above Average

79% of reviews positive, 21% negative

79%
positive
  • Positive79%
  • Neutral0%
  • Negative21%

Sentiment Balance

Covering November 2023 — 10 reviews, not the company's full review history.

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positive
  • Positive—
  • Neutral—
  • Negative—

Takeaway: Positive sentiment accounts for 80% of reviews in this period, with 20% negative and 0% neutral.

Sentiment Trend Over Time

Reviews (Count)
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Theme Distribution

Share of theme mentions

Pricing
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Product Quality
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Loyalty
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Response Speed
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Problem Resolution
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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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