Market Feasibility Surveys
For this reason major international management consulting firms – and indeed their clients – require primary research to ensure due diligence in compiling a credible and defensible financial model for a project that has often only recently left the drawing board.
This service is available from one of WRA’s subscribers. It introduces a quantitative dimension with the key demand segment to plug gaps of hard data left by secondary research or to validate it with the scope of robust in-depth analysis. Typically the research tools we apply to market feasibility surveys draw on:
- Secondary research to estimate the size of the target audience and extract any relevant data pertaining to the business proposition of the client. Just to name a few.
- Census data and allied demographic information.
- Population data of retailers, wholesalers/distributors or manufacturers.
- Macro economic data.
- Incidence rates of a particular respondent segment.
- Market sizes and shares (if available).
- Market trends.
- Company profiles of industry stakeholders.
- New products.
- Technical specifications.
- Pricing data for raw materials and other commodities.
- Import and export regulations/duties.
- Government policies affecting the availability of products or raw materials.
- Short random listing interviews to understand the incidence rate of the target audience as estimated from the secondary research. This helps researchers define and analyse the profile of the target audience, e.g. classification of business activity, size of the business, demographics, etc.
- Quantitative interviews with a representative sample of the target audience.
- Focus groups with consumers if the business concept for them is at a fledgling stage or requires tweaking.
- (Semi)-qualitative interviews with suppliers at relevant levels in the supply chain.
- (Semi)-qualitative interviews with industry experts/observers or other respondents ‘in the know’ (e.g. government officials).
The service developed a proprietary model in order to estimate the likely demand based on several inputs such as awareness, brand image, affinity, current usage, brand used and purchase intent. Its high level of predictive accuracy buoyed demand for this service.