1. Based only on the cluster analysis data, which preference related variables are most useful for segment identification and evaluation? Which variables are least useful?
This qualitative research aims in identifying and evaluating the potential customers of PicDeck and determinate a precise target.
The interviewees have been asked to answer questions based on a ranking system from 1 (strongly disagree) to 5 (strongly agree). The questions investigate the needs: Q 1, 6 – 9, and interest in this new technology service: Q 2 - 5, as well as the willingness of the interviewees to pay for this service: Q 11 – 13. The cluster method divides the interviewees …show more content…
Establishing these profiles has been difficult because the rates of some clusters are very closed to each others. Indeed, we identified two highly valuated variables by the potential customers: Needs of safety and easiness of transfer. Yet, without any qualitative data, we can’t guess their age, sex, revenue nor lifestyle. This is impossible to establish a fair segmentation or targeting a cluster on the basis of these information.
3. Now, use the profiling information in Exhibit 4 to create a revised profile for each cluster. Is this profile different from what you “guessed” based only on the preference data?
Cluster 1: Technology seekers looking for convenience, 24%
Young to middle-age professionals, 52% are between 25-40 years old. 52% of them are Male. Quasi all are interested in technology magazines and web sites. 72% of them have a data Plan on their mobile.
They are interested in an efficient, easy & safe way of transferring photos as well as better quality phone cameras. They would be eager to use only one digital device in the future: camera on phone.
They are looking at the new technologies as a way to improve