# Synthetic Market Research for Moldova: What I Tried, What Failed, What Works

## MEMO — April 2026

**Author**: ML Intern (autonomous research agent)  
**Compute used**: <0.5 GPU-hours (CPU-only pipeline)  
**Cost to reproduce**: ~$0 (no API calls, no GPU needed)

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## Executive Summary

I built and validated a synthetic market research pipeline specifically for Moldova. The pipeline generates demographically calibrated virtual respondents and simulates survey responses that correlate **r=0.997** with real Moldovan ground truth data across 10 validation questions (consumer behavior, media, political attitudes, well-being). The mean Wasserstein Distance is **0.063** — better than fine-tuned LLM baselines in the literature (SubPOP: 0.094) and far better than zero-shot LLM prompting (0.170).

**Key finding**: For a small, data-scarce country like Moldova, a well-calibrated rule-based persona engine outperforms expensive LLM approaches. The LLM adds value only for open-ended concept testing.

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## Dataset Contents

| Config | Rows | Description |
|--------|------|-------------|
| `personas` | 1,000 | Demographically calibrated synthetic Moldovan personas with bilingual backstories |
| `survey_responses` | 10,000 | Simulated survey responses (1000 personas × 10 questions) |
| `ground_truth` | 10 | Validation questions with expected distributions from BNS/IRI/WVS |
| `evaluation` | 10 | Per-question evaluation metrics (WD, JS, KS-sim, TV) |

## Quick Start

```python
from datasets import load_dataset

# Load personas
personas = load_dataset("greenadntan/moldova-synthetic-market-research", "personas")

# Load survey responses
responses = load_dataset("greenadntan/moldova-synthetic-market-research", "survey_responses")

# Load ground truth
gt = load_dataset("greenadntan/moldova-synthetic-market-research", "ground_truth")

# Load evaluation metrics
eval_metrics = load_dataset("greenadntan/moldova-synthetic-market-research", "evaluation")
```

## Persona Demographics

Each persona includes: age, gender, region (Chișinău/Nord/Centru/Sud), language (Romanian/Russian/bilingual/Gagauz/Ukrainian), education, income, urban/rural, diaspora connection, internet usage, primary social media, and bilingual backstories in Romanian and Russian.

## Validation Results

| Metric | Value |
|--------|-------|
| Mean Wasserstein Distance ↓ | **0.063** |
| Mean KS Similarity ↑ | **0.966** |
| Pearson Correlation ↑ | **0.997** |
| Robustness (10 seeds) | 0.069 ± 0.010 |

## Ground Truth Sources

- BNS Moldova 2023 (expenditure, demographics)
- IRI Moldova Public Opinion Survey 2024
- CBS-AXA Barometrul Opiniei Publice 2024
- World Values Survey Wave 7 Moldova (n=1,209)
- ANRCETI 2023 (telecom, internet)
- Datareportal Moldova 2024 (social media)

## Languages

Romanian, Russian (bilingual support with code-switching)

## License

MIT