Customereye

Moose Mobile

Software & Web Servicesmoosemobile.com.au

Review data last updated .

Based on public reviews and response behavior.

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200 reviews over 124 days (about 49 per month). Busiest month: 55% of reviews — one month dominates this sample. Languages: en 100%.

Overall Score

16/100
Short observation window (124 days)
+0.8 vs. last month1.07 ★ average rating · 200 reviews
16/100 from 200 reviews over 5 months, moderate confidence. trend not shown: window under six months. one month holds 55% of the reviews.

Software & Web Services average: score 59.5, rating 4.06 stars, reply rate 36.1%, over 2,026 ranked companies · benchmark 6 Oct 2026

Score

16.1

Industry average 59.5

43.4 below average

Rating

1.07

Industry average 4.06

2.99 below average

Reply rate

—

Industry average 36.1%

not measured

Competitive Performance Rank

Among ranked Software & Web Services companies

#2006of 2026 ranked in Software & Web Services
Top 99% · Bottom Tier
#1 (best)#2026 (worst)
#2004Peer
#2005Peer
#2006This company
#2007Peer
#2008Peer

Only companies with enough recent, scoreable reviews are ranked.

Overall Customer Sentiment

Below Average

15% of reviews positive, 84% negative

14%
positive
  • Positive14%
  • Neutral2%
  • Negative84%

Sentiment Balance

Covering September 2026 — 32 reviews, not the company's full review history.

—
positive
  • Positive—
  • Neutral—
  • Negative—

Takeaway: Positive sentiment accounts for 13% of reviews in this period, with 84% negative and 3% neutral.

Sentiment Trend Over Time

Reviews (Count)
Hidden

Based on 5 months of reviews, too short to read a trend

Half or more of these reviews arrived in a single month

Theme Distribution

Share of theme mentions

Customer Support
Hidden
Communication
Hidden
Response Speed
Hidden
HiddenHidden

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How this analysis was produced

The figures on this page are calculated from a balanced sample of this company's reviews, spread across the period they were written rather than taken only from the most recent. 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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