Customereye

Premium Land

Real Estate & Propertypremiumland.net

Review data last updated .

Based on public reviews and response behavior.

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392 days of reviews, with a sparse monthly review flow. Busiest month: 11% of reviews. Languages: en 73%, unknown 20%, es 2%.

Overall Score

61/100
−41.3 vs. last month4.67 ★ average rating
61/100 from public reviews over 13 months, moderate confidence.

Real Estate & Property average: score 68.3, rating 4.28 stars, reply rate 48.8%, over 1,132 ranked companies · benchmark 5 Nov 2026

Score

60.7

Industry average 68.3

7.6 below average

Rating

4.67

Industry average 4.28

0.39 above average

Reply rate

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Industry average 48.8%

not measured

Competitive Performance Rank

Among ranked Real Estate & Property companies

#830of 1132 ranked in Real Estate & Property
Top 73% · Mid Packdown 208 from last month
#1 (best)#1132 (worst)
#828Peer
#829Peer
#830This company
#831Peer
#832Peer

Only companies with enough recent, scoreable reviews are ranked.

Overall Customer Sentiment

Mid Pack

63% of reviews positive, 34% negative

63%
positive
  • Positive63%
  • Neutral3%
  • Negative34%

Sentiment Balance

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

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positive
  • Positive—
  • Neutral—
  • Negative—

Takeaway: Positive sentiment accounts for 40% of reviews in this period, with 60% negative and 0% neutral.

Sentiment Trend Over Time

Review activity
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Theme Distribution

Share of theme mentions

Response Speed
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Customer Support
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Onboarding
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Delivery Shipping
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Pricing
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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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