predictive study
research designed to predict future sales volumes with different marketing mix options
A predictive study is a type of research design in which data is collected from a sample of individuals or groups, with the goal of predicting future outcomes. The data collected in a predictive study can be either quantitative (numerical) or qualitative (non-numerical) and can involve a wide range of variables, such as demographics, lifestyles, attitudes, behaviors, and health status.
The main objective of a predictive study is to develop and test models that can accurately predict future outcomes based on a set of independent variables. The predictive models can be simple or complex and can involve various statistical techniques, such as regression analysis, decision trees, and machine learning algorithms.
Typically, a predictive study involves the following steps:
1. Defining the research question: This involves identifying the specific outcome that the study aims to predict and the independent variables that are likely to be associated with that outcome.
2. Sampling and data collection: This involves selecting a representative sample of individuals or groups and collecting relevant data from them using various instruments such as surveys, questionnaires, interviews, or observational methods.
3. Data analysis: This involves analyzing the collected data using appropriate statistical techniques and developing predictive models.
4. Model evaluation and refinement: This involves evaluating the predictive models and refining them to improve their accuracy and validity.
5. Reporting and dissemination: This involves preparing a report of the study findings and sharing them with relevant stakeholders, such as policymakers, practitioners, and researchers.
Overall, a predictive study is an important research design that can provide valuable insights into the factors that influence future outcomes and inform decision-making in various fields, such as healthcare, education, social services, and marketing.
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