I'm an almost graduated applied math student. I do some sporadic work in marketing. I have done a few market segmentation projects. I am soon going to do one which is important to me. I usually segment customer types: in a questionnaire people are asked about how they "feel" or what they "like" or consider "important" about a certain type of product or situation, and using this data (usually scaled from 1 to 5, 5 beeing a strong agreement with... or considering ... to be very important) I group people that respondend in a similar fashion. I have only used K-means clustering to achieve this.
This new project is somewhat different. This questionnaire is aimed towards "day moments" (breakfast - supper - dinner, for example) and people are asked at what time they consumed X and WHY? [questions like the ones explained before (scaled from 1 to 5, 5 beeing a strong agreement with... or considering ... to be very important) but in this context], so the idea here is to segment moments of consumption not consumers. My question is, has anybody heard of these analysis? and if so, what are people using to do this? Im sure I can use k-means as usual but I wanted to know what's happening in the world and what could be the pros and cons of studying a bit more and trying something new or just sticking to what I know.
Greetings to all.
