Those with unlimited rate plans have the highest invoice value, and rate plans were the strongest predictors of contract value -- that is, the individual sub-groups examined within these rate plans yielded both higher and lower means than any other subgroup, meaning segregation occurred more along value lines -- and had relatively low volatility, as well. As the rate plans are by and large direct determiners of value, however, this does not yield especially useful information regarding marketing efforts for the company other than suggesting that unlimited plans should be sold to as many consumers as possible. The type of card consumers carried, measured as preferred or not preferred, did not appear to have a very significant impact on value, and with standard deviations close to the means this particular piece of data is a poor predictor of potential customer value.
Income is also a demographic area that had some surprising trends in regards to customer value. Although the highest earning bracket recorded does yield more valuable contract than lower income brackets on average, the difference is not extreme and the trend is not consistent across all income brackets. Volatility in this area is also quite high, meaning income is not a stable or reliable predictor of contract value for Kudzu. Surprisingly, renters seem to spend significantly more on contracts than homeowners, to a fairly consistent degree.
The strongest predictors of spending habits appear to be gender and ages, with females spending more on contracts than males (as can be observed in both the "Gender" and "Marital Status" categories), and increases in age inversely correlated with contract value -- the older a customer is, the less valuable their contract with Kudzu Communications is likely to be. At the same time, both females (again, in both the "Gender" and "Marital Status" categories) and younger individuals have higher rates of volatility in terms of their contracts than do males and older individuals. This is seen in discrete and direct comparisons between females and males, and can be observed as a basic trend in the age range category, with volatility (standard deviation) decreasing as age increases (with one slight exception). This has significant implications that Kudzu Communications should take into account when designing and implementing its new marketing program.
Recommendation
The clearest indicator of value to be derived from specific demographics that emerges from this data is that younger females should be focused on in marketing plans, as...
The volatility of these demographics as demonstrated by the high standard deviations of these population sets, however, means the company should not solely focus efforts here. Creating a better balance between male and female consumers and focusing on younger consumers will drive both value and stability for Kudzu Communications.
Appendix 1
CATEGORY
MEAN
STD. DEV.
Age
0
71.356
1
2
91.055
86.445
3
83.303
70.574
4
78.488
67.522
5
72.47
60.843
6
64.525
59.912
7
67.045
62.925
Marital Status
Dvrd Female
81.785
70.013
Dvrd Male
77.147
61.986
Female
97.434
93.556
Married
69.227
54.883
Single
78.803
66.483
Unknown
84.128
78.794
Gender
Female
80.817
73.322
Male
74.114
60.752
Null
97.434
93.556
Unknown
87.861
Home Owner
Own
73.416
60.674
Rent
93.299
88.789
Income
30
78.868
67.375
40
79.666
75.531
50
69.098
53.494
60
72.521
57.503
70
76.791
61.706
80
71.92
52.014
72.33
56.616
84.651
82.491
unstated
97.096
94.497
Rate Plan
100 Minute
97.979
67.401
200 Minute
48.307
39.096
300 Minute
71.474
54.407
Basic
41.659
40.859
Other
92.393
Unlimited
63.079
Consumer Card
No
89.869
84.234
Yes
