Methodology
Review Intelligence
How we analyse Google Reviews to score each clinic across five categories.
Every clinic profile on SkinCataloq includes a Review Intelligence card that scores the clinic across five categories based on what patients actually say in their Google Reviews. This page explains how that scoring works.
Data Source
Review data is sourced from Google Reviews, a publicly available third-party platform. SkinCataloq does not solicit, edit, or influence these reviews. We display the overall Google rating and review count, and link directly to the clinic's Google Maps listing for full transparency.
The Five Categories
We score each clinic across five categories that matter most when choosing an aesthetic clinic in Singapore:
Service
Quality of staff interactions, communication, personalised care, attentiveness of consultations, and consistency of doctors. Positive signals include friendly staff, clear explanations, and thorough follow-up. Negative signals include rushed consultations, poor communication, and staff turnover.
Comfort & Convenience
Clinic environment, accessibility, and operational efficiency. Positive signals include clean facilities, convenient location, easy booking, and short wait times. Negative signals include dated clinics, long waits, and booking difficulties.
Sales Approach
How the clinic handles recommendations and pricing transparency. Positive signals include no hard-selling, transparent pricing, and honest recommendations. Negative signals include pushy upselling, pressure to buy packages, and bait-and-switch tactics.
Pricing
Perceived value for money. Positive signals include reasonable pricing, good value, frequent promotions, and transparent fees. Negative signals include being overpriced, hidden fees, and surprise charges.
Results
Treatment outcomes and doctor competence. Positive signals include visible improvement, skilful doctors, and effective treatments. Negative signals include poor results, no improvement, and disappointing outcomes.
How Scores Are Calculated
We use AI to read each Google Review and count positive and negative mentions for each category. The AI uses its judgement to identify related sentiments beyond a fixed keyword list — for example, “the doctor really took time to understand my concerns” counts as a positive signal for Service, even though it doesn't use specific keywords.
Each category is scored on a 0 to 10 scale:
- 5.0 = Neutral. No reviews mentioned this category, or positive and negative mentions are evenly balanced.
- Above 5.0 = More positive mentions than negative. The stronger the positive consensus, the higher the score.
- Below 5.0 = More negative mentions than positive. The stronger the negative consensus, the lower the score.
- 10.0 = Practically unattainable. The scoring uses a curve that makes it increasingly difficult to reach the extremes, ensuring scores reflect genuine consensus rather than a handful of reviews.
The Review Analysis score shown on each clinic is the average of all five category scores. This gives a balanced view that doesn't over-index on any single dimension.
Confidence Adjustment
Scores are adjusted based on how many reviews were analysed. A clinic with only a handful of reviews — even if all glowing — has not been tested enough to earn a top score. We use a statistical technique called Bayesian averaging to blend each clinic's raw score with the global average, weighted by the number of reviews analysed.
In practice, this means clinics with more reviews have scores closer to their true performance, while clinics with fewer reviews are pulled toward the average until more data is available. This prevents small-sample clinics from dominating the rankings and ensures that high scores are earned through consistent feedback across many patients.
Refresh Frequency
Review data is refreshed monthly to ensure accuracy. The date of the most recent analysis is recorded internally for each clinic.
Limitations
AI analysis is imperfect. Scores represent our best interpretation of reviewer sentiment but may not capture every nuance. A neutral score (5.0) may mean the category was rarely discussed rather than that patients feel neutral about it.
Google Reviews themselves are user-generated and unverified. SkinCataloq does not endorse or guarantee the accuracy of individual reviews. Our analysis aims to identify patterns across many reviews, not to validate individual claims.
Dispute Process
If you are a clinic owner and believe a score on your profile is inaccurate, please contact us at hello@skincataloq.com. We will review the underlying data and correct any errors. Our goal is accuracy, and we take every report seriously.