Our Methodology
The supplement industry is a mess of marketing hype and unverifiable claims. We built Pretty Good Supp Stacker to bring a data-driven, evidence-based approach to supplement selection. Here is exactly how we select products, score their impact, and optimize your stack.
1. Supplement Selection Criteria
We prioritize two non-negotiable factors: Lowest Effective Cost and Verified Third-Party Testing.
- Third-Party Verification: We only recommend products that carry an independent testing seal (e.g., Informed Sport, USP, NSF, or iTested). This ensures the product contains what it claims and is free from contaminants.
- Cost Optimization: We calculate the cost per effective dose (not just cost per bottle). Our database primarily recommends brands like NOW Foods, California Gold Nutrition, and BulkSupplements for budget options.
- Premium Alternatives: When a specific form (like Thorne's Meriva or Life Extension's NMN) is significantly superior in bioavailability despite a higher cost, we list it as the "Premium" option.
2. Scoring Framework
Research Quality (1-6)
Based on the depth of peer-reviewed human evidence:
Safety Score (1-5)
Evaluating the known risk profile and commonality of side effects:
Impact Score (1-5)
Represents the magnitude of the benefit for a specific health outcome (e.g., Creatine for Strength: 5).
Transparency Score (1-10)
Measures the quality of the specific product recommendation based on the availability of public COAs (Certificates of Analysis) and third-party seals.
3. Optimization Algorithm
Our Stack Optimizer uses two distinct algorithms depending on your selected goal:
How High / Medium / Low priority affects recommendations
When you set an outcome priority in the Optimizer, we convert it into a numeric weight and apply it directly to the Impact Score. In the current algorithm, the weights are: High = 3, Medium = 2, Low = 1.
For each supplement (or lifestyle intervention) we look up its Impact Score (1-5) for each outcome you selected, multiply it by your priority weight, and sum those values across your selected outcomes.
We then adjust this raw score by research quality and safety (multipliers: researchQuality/6 and safety/5), and finally divide by monthly cost to compute a cost-efficiency score. This is the score used to rank candidates before applying the mode-specific rules below.
Reasonable Coverage
Goal: Broad evidence coverage at the lowest possible cost.
This mode sorts supplements by cost-efficiency and stops adding once an outcome is covered by at least one "Level A" meta-analysis or two "Level B" trials. It minimizes redundancy to save you money.
Maximum Impact
Goal: Highest possible cumulative health benefit within your budget.
This mode ignores redundancy and uses a greedy knapsack approach to pack your stack with the highest impact-scored supplements until your monthly budget is exhausted.
"Pretty Good" is the standard.
We believe 90% of supplement benefits come from the top 10% of well-researched, high-purity compounds. Perfection is the enemy of consistency. Our algorithm focuses on the proven foundation so you can stop obsessing and start stacking.
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