Today's competitive landscape makes the critical link between good decision-making and success more important than ever. From corporations (pharmaceutical companies) and government agencies to research institutes and universities, increasingly organisations are turning to quantitative analysis to guide decision-making processes. Using optimal statistical techniques can provide new information that improves processes, drives development and revenues, and helps you retain valued and satisfied customers.

Quantitative research techniques are used as a formal or a decisive research method to measure, describe, and/or to forecast quantity using a range of sampling strategies. This type of research involves measuring a market and quantifying that measurement with data. Most often the data required relates to market size, market share, penetration, installed base and market growth rates. It can also be used to measure such things as customer attitudes, satisfaction, commitment and a range of other useful market data that is tracked over time.

Another important use of quantitative research is to measure customer awareness and attitudes towards different manufacturers and to understand overall customer behaviour in a market by taking a statistical sample of customers. When these techniques are combined with such techniques as segmentation analysis they can be quite powerful. This is because key audiences can be targeted and monitored over time to ensure the best possible use of the marketing budget.

The statistical sample is the main part of quantitative research. Therefore, it has to be selected carefully as well as the design of the sample questionnaire and the quality of the analysis of data collected.

The main focus of quantitative research is on such decision-makers as physicians and/or patients and is designed to answer very specific marketing questions. Typically, these questions focus on a particular issue. Such questions usually call for quantitative data provided by descriptive research, structured surveys, or controlled experiments.

The following are examples of questions that this type of research addresses: