Quantitative marketing research is the application of quantitative research techniques to the field of marketing. It has roots in both the positivist view of the world, and the modern marketing viewpoint that marketing is an interactive process in which both the buyer and seller reach a satisfying agreement on the "four Ps" of marketing: Product, Price, Place (location) and Promotion.

As a social research method, it typically involves the construction of questionnaires and scales. People who respond (respondents) are asked to complete the survey. Marketers use the information so obtained to understand the needs of individuals in the marketplace, and to create strategies and marketing plans.

Typical general procedure

Simply, there are five major and important steps involved in the research process:

1. Defining the Problem.
2. Research Design.
3. Data Collection.
4. Analysis.
5. Report Writing & presentation.

The brief discussion on each of these steps are:

1. Problem audit and problem definition - What is the problem? What are the various aspects of the problem? What information is needed?
2. Conceptualization and operationalization - How exactly do we define the concepts involved? How do we translate these concepts into observable and measurable behaviours?
3. Hypothesis specification - What claim(s) do we want to test?
4. Research design specification - What type of methodology to use? - examples: questionnaire, survey
5. Question specification - What questions to ask? In what order?
6. Scale specification - How will preferences be rated?
7. Sampling design specification - What is the total population? What sample size is necessary for this population? What sampling method to use?- examples: Probability Sampling:- (cluster sampling, stratified sampling, simple random sampling, multistage sampling, systematic sampling) & Nonprobability sampling:- (Convenience Sampling,Judgement Sampling, Purposive Sampling, Quota Sampling, Snowball Sampling, etc. )
8. Data collection - Use mail, telephone, internet, mall intercepts
9. Codification and re-specification - Make adjustments to the raw data so it is compatible with statistical techniques and with the objectives of the research - examples: assigning numbers, consistency checks, substitutions, deletions, weighting, dummy variables, scale transformations, scale standardization
10. Statistical analysis - Perform various descriptive and inferential techniques (see below) on the raw data. Make inferences from the sample to the whole population. Test the results for statistical significance.
11. Interpret and integrate findings - What do the results mean? What conclusions can be drawn? How do these findings relate to similar research?
12. Write the research report - Report usually has headings such as: 1) executive summary; 2) objectives; 3) methodology; 4) main findings; 5) detailed charts and diagrams. Present the report to the client in a 10 minute presentation. Be prepared for questions.