Summary
Do you want to know what customers’ preferences are but have no solution? How can we design a best commodity combination? AsiaAnalytics Taiwan Value-added Module enables you to get rid of the usage model of programming language and helps you finish designing your products with a more friendly user interface. Besides, it can enhance the common multivariate analysis in marketing analysis so that your analysis won’t be limited because all required analyses can be done in IBM SPSS Statistics. SPSS Marketing Analysis Value-added Module is developed by AsiaAnalytics Taiwan technology team. We integrate the functions and methods to get closer to researchers’ needs based on the situation when they are using data analysis software, so that you can get the conclusions sooner when analyzing more data.
Features
- Conjoin support
- Multivariate Analysis support
Applications
- Market Questionnaire Survey
- Marketing Research
- Customer Purchase Behavior Analysis
- Product Property Analysis
Methods
Conjoint Analysis
Conjoint Analysis is an effective product design/market development research tool through the consumer's preference ranking (or scores) of the joint properties, and then through Conjoint Analysis to convert the importance of all properties.
- Orthoplan
- Conjoint Plus Analysis
Orthoplan permutates and combines important variable properties to design a most suitable commodity combination for the respondents, which can greatly save costs and time during your interview.
How can we design the best product project for consumers? Conjoint Plus Analysis is market research tool for effective product design and development, which can evaluate the good and bad sides of the design property projects of various products and quantify consumers’ preferences for products to thereby reduce the possibility that product can be designed in failure.
Multivariate Analysis
Multivariate Data Analysis refers to any statistical technique used to analyze data that arises from more than one variable. This essentially models reality where each situation, product, or decision involves more than a single variable.
- Principal Component Analysis
- Canonical Correlation Analysis
- Rim Weighting Survey Samples
It is a method of converting multiple variables (dimensions) into a few comprehensive indicators. The variables plot and the object plot present the distribution of the principal dimensions in the principal components space of lower dimension and enables us to clearly observe the relationship between the samples or the variables.
It is the correlation analysis between two sets of variables. Converting these two sets of variables into a linear combination can form a new variable. Calculating the correlation between linear combinations can show the correlation between the two variables for investigating the correlation between the independent variable and the dependent variable groups. Through this scatter diagram, you can see and understand the dispersion of variables groups and observed value.
Because of the difference between the population distribution of investigation samples and of the known population distribution, we can use the weighted correction method to reduce the bias caused by the structure of sample population and to enhance the accuracy of the investigation analysis results.
System Requirements
Suggestion for installing IBM SPSS Statistics Base:
- Windows XP,2000,WIN 7
- Intel Pentium-compatible CPU
- Memory: ≧512MB RAM
- Hard Disk Space: ≧1 GB
- SVGA Display
- Internet Explorer 6