05-12-2013 08:25 AM
In the course of a research project with a sample size of > 1000, I intend to first group users in unique motivation/motive classes. These will be derived from qualitative user statements which are manually attributed to multiple binary motivation items- min 5 up to 10 items such as Social, Enjoyment, Achievement or Fitness; multiple occurrences are possible. As the data appears at the moment, users would often state single motivations such as „fun“ or two motives such as a combination of „fun“, „achievement“. Anyway, all combinations are possible. What statistical method is useful in that respect to associate an individual user with a specific motivation class?
As a second dimension for the segmentation analysis, I would like to derive behavioral classes based on mixed variables such as intensity of sport consumption/week, number of different sports types consumed as well as binarily coded variables such as paid subscription (yes/no). Again, what statistical method/clustering approach would be feasible for this kind of data?
In the end, I would like to derive dominant user typologies conducting a cross tabulation of motivational and behavioral user classes.
What other (online) resources would you recommend to take into consideration for such a research project. Thanks in advance for your support and sharing any valuable information you may be able to contribute.