SPSS k-means clustering

Analyze the data in file to segment consumers into an appropriate number of groups. How do consumers in these segments differ? Discuss marketing implications of this segmentation scheme.

Description of data

Seventy two respondents were asked questions about their background. The questions were:

1. Whenever new technologies emerge in my field, I am among the first to adopt them (1=strongly agree, .. 7=strongly disagree)
2. How often do you use Pager (1=never, . 7=always)
3. How often do you use Phone or voice mail (1=never, . 7=always)
4. How often do you use scheduling or contact-management tools (1=never, . 7=always)
5. How often do others send you time-sensitive information (1=never, . 7=daily)
6. How much of your time do you spend away from your office location (1=0%,.,7=70% or more)
7. How important is wireless communication to you? (1=not at all important,..7=very important)
8. How important is it for you to share information rapidly with colleagues while away from an office location (1=not at all important, .., 7=very important)
9. Age
10. Education (1=high school, 2=some college, 3=college, 4=graduate level)
11. income

Initial Cluster Centers Cluster Innovator Pager Voicemail Scheduler Time Info Remote Wireless Infoshare Age Education Income 2 4 4 4 6 32 38 20 107 Iteration Historya Change in Cluster Centers Iteration 20.777 14.693 a. Convergence achieved due to no or small change in cluster centers. Ihe maximum absolute coordinate change for any center is .000. The current teration is 2. The minimum distance between initial centers is 87.344 Final Cluster Centers Cluster Innovator Pager Voicemail Scheduler Time Info Remote Wireless Infoshare 6 Education Income 40 93 Distances between Final Cluster Centers Cluster 53.435 2 53.435 ANOVA Cluster Error Mean Square df Mean Square df Si Innovator Pager Voicemail Scheduler Time Info Remote Wireless Infoshare Age Education Income 45.563 1.563 5.444 19.877 10.028 563 17.710 9.507 6.674 11.960 20175.835 2.504 2.262 2.557 3.018 2.768 1.649 4.294 1.597 125.028 805 108.435 70 70 70 70 70 70 70 70 70 70 70 186.063 18.193 691 2.129 6.587 3.623 341 4.124 5.952 053 14.855 409 149 012 061 561 046 017 818 The F tests should be used only for descriptive purposes because the clusters have been chosen to maximize the differences among cases in different clusters. The observed significance levels are not corrected for this and thus cannot be interpreted as tests of the hypothesis that the cluster means are equal Initial Cluster Centers Cluster Innovator Pager Voicemail Scheduler Time Info Remote Wireless Infoshare Age Education Income 2 4 4 4 6 32 38 20 107 Iteration Historya Change in Cluster Centers Iteration 20.777 14.693 a. Convergence achieved due to no or small change in cluster centers. Ihe maximum absolute coordinate change for any center is .000. The current teration is 2. The minimum distance between initial centers is 87.344 Final Cluster Centers Cluster Innovator Pager Voicemail Scheduler Time Info Remote Wireless Infoshare 6 Education Income 40 93 Distances between Final Cluster Centers Cluster 53.435 2 53.435 ANOVA Cluster Error Mean Square df Mean Square df Si Innovator Pager Voicemail Scheduler Time Info Remote Wireless Infoshare Age Education Income 45.563 1.563 5.444 19.877 10.028 563 17.710 9.507 6.674 11.960 20175.835 2.504 2.262 2.557 3.018 2.768 1.649 4.294 1.597 125.028 805 108.435 70 70 70 70 70 70 70 70 70 70 70 186.063 18.193 691 2.129 6.587 3.623 341 4.124 5.952 053 14.855 409 149 012 061 561 046 017 818 The F tests should be used only for descriptive purposes because the clusters have been chosen to maximize the differences among cases in different clusters. The observed significance levels are not corrected for this and thus cannot be interpreted as tests of the hypothesis that the cluster means are equal