Customereye

Transparent Labs

Supplements & Nutrition • United Stateswww.transparentlabs.com

Review data last updated .

Based on public reviews and response behavior.

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1,124 days of reviews, with a sparse monthly review flow. Busiest month: 21% of reviews. Languages: en 100%.

Overall Score

70/100
−19.7 vs. last month4.46 ★ average rating
70/100 from public reviews over 16 months, moderate confidence.

Supplements & Nutrition average: score 65.4, rating 4.42 stars, reply rate 44.4%, over 714 ranked companies · benchmark 4 Nov 2026

Score

69.8

Industry average 65.4

4.4 above average

Rating

4.46

Industry average 4.42

0.04 above average

Reply rate

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Industry average 44.4%

not measured

Competitive Performance Rank

Among ranked Supplements & Nutrition companies

#266of 714 ranked in Supplements & Nutrition
Top 37% · Upper Halfdown 153 from last month
#1 (best)#714 (worst)
#264Peer
#265Peer
#266This company
#267Peer
#268Peer

Only companies with enough recent, scoreable reviews are ranked.

Overall Customer Sentiment

Above Average

82% of reviews positive, 16% negative

82%
positive
  • Positive82%
  • Neutral2%
  • Negative16%

Sentiment Balance

Covering August 2026, not the company's full review history.

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positive
  • Positive—
  • Neutral—
  • Negative—

Takeaway: Positive sentiment accounts for 69% of reviews in this period, with 24% negative and 7% neutral.

Sentiment Trend Over Time

Review activity
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Theme Distribution

Share of theme mentions

Customer Support
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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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