Learn About Statistical Analysis For Marketing Research

We've grouped together all the information our site contains on Statistical Analysis to help you quickly and easily find related articles, companies, events, jobs, associations, glossary definitions and more.

Recent Articles

Below are the 5 most recent articles on this topic. These articles were published within the last three years and are only available to registered subscribers.

Data Use: Telling the future from the past: predictive versus classical statistics: This article compares and contrasts predictive and classical statistics, making the case that predictive methods offer an effective way to use current data to make statements about future data.
Data Use: A good choice for choice modeling: Maximum difference scaling lets researchers present respondents with large numbers of choice options without making the process onerous. The article uses examples of a hotel loyalty program and restaurant menu optimization to show the technique in action.
Rapport and reports - what matters to health-care research end users?: Researchers from Observant LLC and Pfizer explore what the key satisfaction drivers are among health-care and pharmaceutical end users. Results suggest anticipation of needs, excellent rapport and boardroom-ready reports matter most.
By the Numbers: How to improve your segmentations with max-diff: The author uses a checking-account example to show how maximum difference scaling, or max-diff, can deliver finely-tuned segmentations without subjecting respondents to an onerous number of comparison questions.
How important is the respondent’s perception of survey length?: Can you improve respondents’ feelings about the survey experience by using more interactive question types? This and other related topics were investigated by three market research firms and they report their findings here along with offering questionnaire design tips.

See more articles on this topic

There are 13 articles in our archive related to this topic. Below are 5 selected at random and available to all users of the site.

Working with a statistical expert and surviving: The author gives advice, aid and comfort to all of those marketing professionals who have required the services of a statistician. While the prospect of hiring a statistician is not always appealing, the author gives a few tips to help the relationship between statistician and market professional.
Data Use: A look at item non-response: Because respondents do not always provide complete data in their questionnaires, data tabulation and statistical analysis can be tricky. This article addresses item non-response, including tabulation and summary statistics, providing a simple example.
Data Use: Weighting survey data: Data weighting, or sample balancing, is both under- and misused. This article discusses data weighting, providing descriptions and examples that may foster more effective use of the technique by researchers in a variety of organizations.
Mapping the future: This article describes the use of correspondence analysis to predict the impact of various marketing strategies on their brand's competitive position. In contrast to other types of perceptual mapping, correspondence analysis summarizes nominal data rather than metric data.
By the Numbers: Let's test everything: In statistical testing, the key is to make sure the right numbers are being tested.