METHODS, SYSTEMS, ARTICLES OF MANUFACTURE AND APPARATUS TO DETERMINE PRODUCT CHARACTERISTICS CORRESPONDING TO PURCHASE BEHAVIOR

1 . An apparatus to generate characteristic metrics, the apparatus comprising:

a characteristics identifier to identify characteristics corresponding to purchase data;

a characteristic selector to select one of the characteristics;

a likelihood calculator to calculate a likelihood value of a first level of the selected one of the characteristics; and

an importance metric calculator to reduce discretionary input of an analyst by calculating an importance metric based on a ratio of (a) the likelihood value of the first level and (b) a maximum likelihood value corresponding to the first level of the selected one of the characteristics.

2 . The apparatus as defined in claim 1 , wherein the characteristic identifier is to determine if the characteristic is a binomial characteristic.

3 . The apparatus as defined in claim 2 , wherein the likelihood value is a first likelihood value, and the likelihood calculator is to calculate a second likelihood value of a second level of the selected one of the characteristics.

4 . The apparatus as defined in claim 1 , wherein the characteristic identifier is to determine if the characteristic is a multinomial characteristic.

5 . The apparatus as defined in claim 4 , wherein the multinomial characteristic includes a first characteristic level, a second characteristic level, and a third characteristic level.

6 . The apparatus as defined in claim 5 , wherein the likelihood calculator is to determine a decomposition of the importance metric based on the first characteristic level, the second characteristic level, and the third characteristic level.

7 .- 9 . (canceled)

10 . The apparatus as defined in claim 8 , further including a decay calculator to temporally weight the consumer purchase data and the product attribute data based on a daily decay function.

11 . The apparatus as defined in claim 1 , wherein the importance metric calculator is to generate an attribute importance profile based on the importance metric.

12 . A non-transitory computer readable medium comprising instructions that, when executed, cause at least one processor to, at least:

identify characteristics corresponding to purchase data;

select one of the characteristics;

calculate a likelihood value of a first level of the selected one of the characteristics; and

reduce discretionary input of an analyst by calculating an importance metric based on a ratio of (a) the likelihood value of the first level and (b) a maximum likelihood value corresponding to the first level of the selected one of the characteristics.

13 . The non-transitory computer readable medium as defined in claim 12 , wherein the instructions, when executed, further cause the at least one processor to determine if the characteristic is a binomial characteristic.

14 . The non-transitory computer readable medium as defined in claim 13 , wherein the likelihood value is a first likelihood value, and the instructions, when executed, further cause the at least one processor to calculate a second likelihood value of a second level of the selected one of the characteristics.

15 . The non-transitory computer readable medium as defined in claim 12 , wherein the instructions, when executed, further cause the at least one processor to determine if the characteristic is a multinomial characteristic.

16 . The non-transitory computer readable medium as defined in claim 15 , wherein the multinomial characteristic includes a first characteristic level, a second characteristic level, and a third characteristic level.

17 . The non-transitory computer readable medium as defined in claim 16 , wherein the instructions, when executed, further cause the at least one processor to determine a decomposition of the importance metric based on the first characteristic level, the second characteristic level, and the third characteristic level.

18 .- 22 . (canceled)

23 . An apparatus to generate characteristic metrics, the apparatus comprising:

means for identifying characteristics corresponding to purchase data;

means for selecting one of the characteristics;

means for calculating a likelihood value of a first level of the selected one of the characteristics; and

means for calculating an importance metric to reduce discretionary input of an analyst by calculating the importance metric based on a ratio of (a) the likelihood value of the first level and (b) a maximum likelihood value corresponding to the first level of the selected one of the characteristics.

24 . The apparatus as defined in claim 23 , wherein the characteristics identifying means is to determine if the characteristic is a binomial characteristic.

25 . The apparatus as defined in claim 24 , wherein the likelihood value is a first likelihood value, and the likelihood calculating means is to calculate a second likelihood value of a second level of the selected one of the characteristics.

26 . The apparatus as defined in claim 23 , wherein the characteristics identifying means is to determine if the characteristic is a multinomial characteristic.

27 . The apparatus as defined in claim 26 , wherein the multinomial characteristic includes a first characteristic level, a second characteristic level, and a third characteristic level.

28 . The apparatus as defined in claim 27 , wherein the likelihood calculating means is to determine a decomposition of the importance metric based on the first characteristic level, the second characteristic level, and the third characteristic level.

29 .- 44 . (canceled)