AT MANIFOLD WE LIVE FOR DATA We take numbers and turn them into actionable results
Healthcare Consumer Healthcare Patterns
Stitch together a comprehensive picture of consumers’ healthcare needs, health-related spending, healthcare patterns, and health conditions. It includes 2000+ variables in the following major categories:
- General Health
- Chronic Conditions
- Oral Health
- Health Improvement
- Food Consumption
- Physical Activities
- Sedentary Activities
- Smoking
- Alcohol Consumption
- Life, Job, and Relationships
- Sun Safety
- Driving
- Loss of Productivity
- Home Care
- Healthcare Activities and Experience
- Health Checkup
- Pain Relievers and Drug Use
- Maternal Experience
CPG companies use this data product to find top prospects for baby food, vitamins, and nutritional supplements. Retailers including grocers and pharmacies use this data product to do demand forecasting, optimize product placement, and to contextualize ads in local store trade areas for sun safety, oral care, food, alcohol, pain relievers, baby food, and vitamins or nutritional supplements. Home care and all retailers, including home improvement and sporting good retailers can use this data product to gain customer insight; perform trade area analysis; estimate market potential; tailor communication and identify the best prospects. Insurance companies use this data product to find more new customers. Pharmaceuticals use this data product to optimize distribution.
Most Recent Update |
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2025
Available Geographic Levels |
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6-digit postal code, FSA, DA, CT, CSD, CD, and custom geography
Update Frequency |
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Annual
Methodology |
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Data fusion with stratified sampling techniques. Strata based on the Census, surveys from Statistics Canada, the RTS survey from Numeris, and others are linked to the strata derived from demographic and consumer behaviour information at the postal code geographic level. Thereafter, healthcare patterns are modeled from survey data to general population. Structural coherence is essential in selecting geographic level and the integration process. We have applied techniques from statistics, dynamics, data mining and other disciplines, including multi-staged and adaptive nonlinear methods for dimension reduction, effective statistical distance functions and coherent structural approximations.
Data sources include Canadian Community Health Survey, Canadian Mortgage and Housing Corporation (CMHC), Statistics Canada, Cleanlist, municipal building permits statistics and trends, and the Numeris RTS survey.
Data Format |
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CSV
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Sample Reports |
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Data Dictionary |
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How To Get It |
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