Back to Survey analysis to Gain Marketing Insights
Survey analysis to Gain Marketing Insights, Emory University
4.3
30 ratings
About this Course
How do consumers see your brand relative to your competitors? How should a new product be positioned when it’s launched? Which customer segments are most interested in our current offerings? For these questions and many others, surveys remain the tried and true method for gaining marketing insights. From one-off customer satisfaction surveys to brand tracking surveys that are administered on a continuous basis, they provide the information that marketers need to understand how their products, services and brands are seen by consumers. In Analytic Methods for Survey Data, learners will become familiar with established statistical methods for converting survey responses to insights that can support marketing decisions. Techniques discussed include factor analytics, cluster analysis, discriminant analysis and multi-dimensional scaling. These techniques are presented within the STP (Segmentation, Positioning, Targeting) Framework, enabling learners to apply the analytic techniques to develop a marketing strategy. It is recommended that you complete the Meaningful Marketing Insights course offered by Coursera before taking this course.
Note: This course would require using XL Stat, an Excel Add-on that students would need to purchase. XL Stat offers a 30-day free trial, so students could complete this course without incurring additional expense.
Top reviews
By EW
•Dec 06, 2017
Great course, with a much broader content than reflected in the title, allowing to gain insight by using regression analysis of survey data.
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3 Reviews
By Elena Wood
•Dec 06, 2017
Great course, with a much broader content than reflected in the title, allowing to gain insight by using regression analysis of survey data.
By Sonja Glaab-Seuken
•Aug 19, 2017
Well taught class
By Chase McCarthy
•Jul 23, 2017
Interesting concepts but would have enjoyed class more if it did not rely on a proprietary analytics tool
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