Dynamic Pricing Engine
Static pricing undervalues rare data and overpays for common data. The Dynamic Pricing Engine adjusts yield in real-time based on supply, demand, geographic representation, and market signals.
Pricing Formula
Final Credit = Base Credit × Active Multiplier × Dynamic Multiplier
Where:
Base Credit = promisedAnnualUsd / reqCount / periodsPerYear
Active Multiplier = earlyBirdMultiplier × regionMultiplier
Dynamic Multiplier = saturation × rarity × funding × geoScarcity
Multiplier Stack
All multipliers are composable — they multiply together to determine the final yield:
1. Region Multiplier (Enrollment-Time, Fixed)
Incentivizes data from populations underrepresented in medical AI training datasets.
| Region | Countries | Multiplier | Rationale |
|---|---|---|---|
| Africa | NG, KE, ZA, GH, ET, TZ, CI, SN, RW, UG | 2.5–3.0x | <1% of medical AI training data is African |
| South/SE Asia | TH, VN, ID, PH, MM, IN, BD, PK, LK, NP, KH, LA | 1.8–2.5x | ~5% representation despite 40% of global population |
| Latin America | BR, MX, CO, PE, AR, CL, EC, GT, BO | 1.3–2.0x | Moderate underrepresentation |
| Middle East | SA, AE, EG, IR, IQ | 1.3–2.0x | Moderate underrepresentation |
| East Asia | JP, KR, CN, TW, HK, SG | 1.0x | Well-represented baseline |
| Europe/NA/Oceania | US, CA, GB, DE, FR, AU, NZ, etc. | 1.0x | Well-represented baseline |
| Unlisted | All others | 1.5x | Default premium for uncharted data |
Of the ~500,000 medical images used to train the top 10 radiology AI models, fewer than 2,000 came from sub-Saharan Africa. A single Nigerian chest X-ray is literally worth 3x a US chest X-ray because it fills a critical blind spot in AI diagnostic accuracy for dark-skinned populations.
2. Early Bird Multiplier (Enrollment-Time, Fixed)
| Condition | Multiplier | Duration |
|---|---|---|
| Enrolled before sponsor funding | 1.5x | First 6 months |
| Enrolled after funding | 1.0x | — |
Early contributors take more risk (they earn "promised credits" that may never convert). The 1.5x bonus rewards that risk.
3. Compliance Tier Multiplier (Rolling, Recalculated)
| Tier | Min Compliance % | Multiplier | Effect |
|---|---|---|---|
| Excellent | ≥ 95% | 1.1x | Bonus for consistency |
| Good | ≥ 80% | 1.0x | Standard rate |
| Partial | ≥ 60% | 0.6x | Reduced — missing data |
| Paused | < 60% | 0.0x | No credits until compliance recovers |
4. Dynamic Pricing Multiplier (Real-Time)
Adjusts every time a submission is evaluated:
a) Enrollment Saturation
if participants/maxParticipants < 25%: ×1.30 (early adopter premium)
if participants/maxParticipants < 50%: ×1.15
if participants/maxParticipants > 90%: ×0.90 (near capacity, marginal value drops)
b) Rarity Score Boost
| Rarity | Score | Permanent Boost |
|---|---|---|
| Ultra-Rare | 5 | +50% |
| Very Rare | 4 | +30% |
| Rare | 3 | +15% |
| Uncommon | 2 | +5% |
| Common | 1 | +0% |
c) Funding Signal
| Status | Adjustment |
|---|---|
| Fully funded | +10% (higher payout confidence) |
| Partially funded | +0% |
| Seeking sponsor | -15% (credits are promises) |
d) Geographic Scarcity Bonus (Per-Program)
Calculated per-country within each program:
if first contributor from country: ×1.50
if country < 2% of program: ×1.30
if country < 5% of program: ×1.15
if country > 30% of program: ×0.95 (over-represented)
Example Yield Scenarios
Scenario 1: Maximum Yield
Program: ALS Motor Neuron ($840/yr), 4 requirements, weekly
Patient: First contributor from Rwanda (RW)
Early bird: 1.5x
Region: 3.0x
Compliance: 95% → Excellent (1.1x)
Saturation: 2/100 → 1.3x
Rarity: Ultra-Rare (5) → 1.5x
Funding: seeking_sponsor → 0.85x
Geo scarcity: first from RW → 1.5x
Base = $840 / 4 / 52 = $4.04 per submission
Final = $4.04 × 1.5 × 3.0 × 1.1 × 1.3 × 1.5 × 0.85 × 1.5
= $4.04 × 11.56
= $46.72 per weekly submission
= $2,429/yr effective yield
Scenario 2: Minimum Yield
Program: Wellness Baseline ($24/yr), 3 requirements, daily
Patient: US, enrolled after funding, good compliance
Early bird: 1.0x
Region: 1.0x
Compliance: 82% → Good (1.0x)
Saturation: 890/1000 → 0.9x
Rarity: Common (1) → 1.0x
Funding: fully_funded → 1.1x
Geo scarcity: US is 35% → 0.95x
Base = $24 / 3 / 365 = $0.022 per submission
Final = $0.022 × 1.0 × 1.0 × 1.0 × 0.9 × 1.0 × 1.1 × 0.95
= $0.022 × 0.94
= $0.021 per daily submission
= $7.58/yr effective yield (lower than promised due to dynamic factors)
Design Improvements: What Could Be Better
1. Time-Decay Multiplier
Long-term contributors should earn progressively more. After 12 months of continuous compliance, apply a loyalty multiplier:
months 1-6: 1.0x (baseline)
months 7-12: 1.1x (retention bonus)
months 13-24: 1.2x (loyalty tier)
months 25+: 1.3x (veteran tier)
2. Data Quality Score
Not all submissions are equally valuable. A "data richness" score based on:
- Completeness: All optional fields filled → +10%
- Frequency: More frequent than required → +5%
- Source quality: Lab import > HealthKit sync > manual entry → +5-15%
- Context: Diagnosis codes attached → +10%
3. Cross-Program Bonus
Patients enrolled in multiple complementary programs (e.g., Diabetes + Pharmacogenomics) provide more valuable correlated data:
- 2 programs: +5%
- 3+ programs: +10%
- Programs sharing ICD codes: +15%
4. Sponsor Competition Premium
When multiple sponsors want the same data type, bid competition should drive prices up:
- 1 sponsor: base rate
- 2 sponsors: +20%
- 3+ sponsors: auction-driven pricing
5. Seasonal Adjustment
Some data is more valuable at certain times:
- Flu season (Oct-Mar): respiratory data +25%
- Allergy season (Apr-Jun): immunology data +15%
- Holiday season (Dec): mental health data +20%