Qualitative Surveys

Implement qualitative survey workflows for the Emerging Household Energy solution.

This guide is scoped to Emerging Household Energy. It explains how to run baseline, follow-up, and monitoring surveys that complement solution dMRV evidence.

Survey Types

Baseline Survey

Pre-distribution assessment and eligibility verification

Follow-up Survey

Early adoption and performance evaluation

Monitoring Survey

Ongoing SDG impact and emission reduction validation

Survey Stages and Objectives

Baseline Survey (Pre-Project)

  • Timing: Before stove distribution/sales
  • Target Population:
    • Potential adopters
    • Non-adopting households for comparison
  • Objectives:
    • Assess community perception of new stoves
    • Gather socio-economic baseline data
    • Verify household eligibility
    • Validate inclusion criteria
    • Inform sampling design
  • Data Collection:
    • Household demographics
    • Current cooking practices
    • Economic indicators
    • Technology preferences

Follow-up Survey (Post-Installation)

  • Timing: Shortly after stove deployment
  • Objectives:
    • Identify performance strengths
    • Detect early adoption issues
    • Enable rapid problem resolution
    • Assess user satisfaction
  • Focus Areas:
    • Installation quality
    • Initial user experience
    • Technical challenges
    • Usage patterns

Monitoring Survey (Ongoing)

  • Purpose:
    • Validate emission reduction calculations
    • Verify SDG impacts
    • Cross-reference with KPT/SUM data
  • Key Parameters:
    • Stove usage patterns
    • Fuel consumption
    • User satisfaction
    • SDG indicators
    • Inclusion criteria validation

Implementation Requirements

Survey Design
  • MADD Integration:
    • Complete questionnaire in MADD
    • Regular suitability assessment
    • Adaptation based on monitoring feedback
  • Data Collection Protocol:
    • Defined collection methodology
    • Specified storage solutions
    • Clear responsibility assignment
  • Quality Control:
    • Validation procedures
    • Cross-reference mechanisms
    • Update protocols
Data Management
  • Collection Responsibility:
    • Designated data collectors
    • Training requirements
    • Quality assurance roles
  • Storage Solutions:
    • Secure data repositories
    • Access control
    • Backup procedures
  • Data Flow:
    • Collection to storage pipeline
    • Verification process
    • Integration with other data sources
Sampling Design
  • Methodology:
    • Statistical approach
    • Population coverage
    • Stratification criteria
  • Sample Size:
    • Calculation methodology
    • Confidence levels
    • Margin of error
  • Selection Process:
    • Random selection methods
    • Bias prevention
    • Documentation requirements

Quick Start

curl -X POST https://api.emerging.eco/v1/surveys \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -d '{
    "type": "BaselineSurvey",
    "projectId": "did:ixo:project/789",
    "template": {
      "eligibilityCriteria": true,
      "socioEconomicData": true,
      "cookingPatterns": true,
      "stovePerceptions": true
    },
    "sampling": {
      "method": "stratified",
      "size": 100,
      "confidence": 0.95
    }
  }'

Data Models

Survey Template

{
  "templateId": "baseline-v1",
  "sections": [{
    "id": "eligibility",
    "questions": [{
      "id": "current_cooking",
      "type": "multiple_choice",
      "required": true,
      "options": ["wood", "charcoal", "lpg", "electric"]
    }]
  }, {
    "id": "socio_economic",
    "questions": [{
      "id": "household_size",
      "type": "number",
      "validation": {
        "min": 1,
        "max": 20
      }
    }]
  }],
  "validations": {
    "requiredSections": ["eligibility"],
    "completionThreshold": 0.8
  }
}

Survey Response

{
  "responseId": "survey-123",
  "surveyId": "baseline-v1",
  "householdId": "did:ixo:household/123",
  "timestamp": "2024-02-20T10:00:00Z",
  "responses": {
    "eligibility": {
      "current_cooking": ["wood", "charcoal"]
    },
    "socio_economic": {
      "household_size": 5
    }
  },
  "verification": {
    "status": "verified",
    "verifier": "did:ixo:validator/456",
    "timestamp": "2024-02-20T10:15:00Z"
  }
}

Survey Management

from emerging import SurveyManager, DataValidator, SampleCalculator

# Create survey campaign with CDM-compliant sampling
calculator = SampleCalculator(
    project_id="did:ixo:project/789",
    confidence=0.95,
    precision=0.05
)

sampling = calculator.compute(
    population=1000,
    expected_mean=0.8,
    expected_sd=0.2,
    dropout_rate=0.15
)

# Create and deploy survey
manager = SurveyManager("did:ixo:project/789")
campaign = manager.deploy_survey(
    template_id="baseline-v1",
    sampling=sampling,
    collectors=["did:ixo:agent/123"]
)
Tip

For detailed information on sampling methodology and CDM compliance, see the Sample Size Calculator guide.

Data Handling

from emerging import DataProcessor, SDGValidator

# Process survey responses
processor = DataProcessor()
results = processor.analyze_survey_data(
    survey_id="baseline-v1",
    validation_rules={
        "completeness": 0.8,
        "consistency": True
    }
)

# Validate SDG impacts
sdg_validator = SDGValidator()
sdg_impacts = sdg_validator.assess_impacts(
    survey_data=results,
    sdg_targets=["SDG7", "SDG13"]
)

Integration with Monitoring Tools

from emerging import MonitoringIntegration

# Create integrated analysis
integration = MonitoringIntegration(
    project_id="did:ixo:project/789"
)

# Cross-validate data sources
validation = integration.cross_validate(
    survey_data="baseline-v1",
    sum_data="sum-456",
    kpt_data="kpt-789"
)

# Generate comprehensive report
report = integration.generate_report(
    period_start="2024-01-01",
    period_end="2024-01-31"
)

Error Handling

400error

Invalid survey configuration

404error

Survey or response not found

409error

Conflicting response data

Best Practices

Survey Design

  • Align with project objectives
  • Include all MADD requirements
  • Enable data cross-validation
  • Support multiple languages
  • Allow for periodic updates

Data Collection

  • Train survey collectors
  • Implement quality controls
  • Ensure consistent methodology
  • Document collection process
  • Maintain chain of custody

Data Analysis

  • Cross-reference with SUMs/KPTs
  • Validate response consistency
  • Track temporal changes
  • Generate actionable insights
  • Monitor inclusion criteria

Documentation

  • Record methodology
  • Track survey updates
  • Document responsibility assignments
  • Maintain data flow records
  • Archive survey versions

Next Steps

Survey Templates

Standard questionnaire formats

Data Collection

Mobile survey tools

Protocols

Impact assessment methods

Integration Guide

Cross-validation with SUMs

Household Monitoring

Track complete household transitions

Stove Use Monitoring

Validate with sensor data

Kitchen Performance Tests

Measure fuel consumption

Household Reporting

Generate comprehensive reports