Smartshop Score Methodology
A transparent, algorithmic quality rating from 0 to 100 — no human bias, no paid placements.
How We Score Shops
The Smartshop Score is a composite quality rating from 0 to 100, assigned to every shop in our directory. It is designed to give consumers a quick, reliable indicator of shop quality based on publicly available data.
The score is computed algorithmically — no human judgment enters the calculation. It combines 7 weighted criteria, each measuring a different aspect of shop quality. The weights reflect our assessment of what matters most to consumers: real customer reviews carry the most weight, followed by data completeness and online professionalism.
All data sources, weights, and formulas are documented below. We believe transparency in methodology is essential for trust.
7 Scoring Criteria
Google Reviews
25%Combines the average star rating (1-5) with a review count factor. A shop with 4.5 stars and 200 reviews scores higher than one with 5.0 stars and 3 reviews. The formula rewards both quality and quantity of customer feedback.
Source: Google Places API
Data Completeness
20%Measures how much information is available: website URL, phone number, email, photos, business description, opening hours, and KvK number. Each data point adds to the completeness score. Shops with rich, complete profiles score higher.
Source: Our database
Online Presence
15%Evaluates website quality: SSL certificate (HTTPS), mobile responsiveness, page load speed, and whether the site is currently online. A fast, secure, mobile-friendly site indicates a professional operation.
Source: Automated checks
Verification Status
15%Whether the shop has a verified KvK (Chamber of Commerce) number and has been manually verified by our team. Verified shops demonstrate legitimacy and legal compliance.
Source: KvK / manual
Product Range
10%Counts the number of product categories offered. A smartshop selling truffles, herbs, seeds, and supplements scores higher than one with a single category. Breadth indicates a mature, well-stocked shop.
Source: Website analysis
Social Presence
10%Checks for active social media profiles on Instagram, Facebook, Twitter/X, and TikTok. Active social accounts suggest an engaged business that communicates with customers.
Source: Social profiles
Trustpilot Score
5%If available, the Trustpilot rating is factored in as an additional trust signal. Many Dutch shops don't have Trustpilot profiles, so this carries the lowest weight.
Source: Trustpilot API
Example Calculation
Here is a worked example showing how the Smartshop Score is calculated for a typical shop:
| Criterion | Weight | Score | Weighted |
|---|---|---|---|
| Google Reviews | 25% | 78 | 19.5 |
| Data Completeness | 20% | 78 | 15.6 |
| Online Presence | 15% | 72 | 10.8 |
| Verification Status | 15% | 100 | 15.0 |
| Product Range | 10% | 67 | 6.7 |
| Social Presence | 10% | 50 | 5.0 |
| Trustpilot Score | 5% | 0 | 0.0 |
| Final Smartshop Score | 73 | ||
The weighted scores are summed and rounded to the nearest integer. This shop scores 73 (Very Good).
Score Ranges
Excellent
Top-tier shop with outstanding reviews, complete data, verified status, and strong online presence.
Very Good
Well-established shop with good reviews and solid data. Minor gaps in some criteria.
Good
Decent shop with room for improvement. May be missing some data or have fewer reviews.
Fair
Limited data available. The shop may be new, have few reviews, or lack online presence.
Needs Improvement
Very little data available. Often newly discovered shops that haven't been fully enriched yet.
Limitations
We believe in being honest about what our score does not capture:
- Product quality: We cannot test products. The score reflects the shop's professionalism and reputation, not the quality of individual products.
- Customer service: While reviews may mention service quality, we don't separately measure response times or support quality.
- Pricing: The score does not factor in prices. A high-scoring shop is not necessarily the cheapest, nor is a low-scoring shop necessarily overpriced.
- Personal preference: Some consumers prefer small boutique shops; others prefer large selections. The score cannot account for individual taste.
- New shops: Recently opened shops with few reviews may have artificially low scores. This improves naturally over time as data accumulates.
- Review manipulation: While we rely on platform-level fraud detection, no system is perfect. We encourage consumers to read reviews, not just the overall rating.