Methods and apparatus to generate consumer data
Methods and apparatus to generate consumer data are disclosed. An example method of selecting a sample of transaction data corresponding to a membership program includes defining a first type of member of the membership program; defining a second type of member of the membership program; calculating, via a processor, a target for the sample; selecting, via the processor, a first portion of the transaction data for the first type of member in accordance with the target; generating, via the processor, an updated target by recalculating the target with the first portion of the transaction data removed from consideration; and selecting, via the processor, a second portion of the transaction data for the second type of member in accordance with the updated target.
1. A method of selecting a sample of transaction data corresponding to a membership program, the method, comprising:
obtaining, by executing an instruction with a processor, panelist data for a household via a network and retailer data from a database associated with a retailer;
defining, by executing an instruction with a processor, a first type of member and a second type of member of the membership program, the first and second types of member defined by a quantity of retailers associated with respective members;
calculating, by executing an instruction with the processor, a target for a characteristic of the sample of transaction data based on the panelist data and the retailer data;
calculating, by executing an instruction with the processor, a first sample size requirement for the first type of member and a second sample size requirement for the second type of member;
selecting, by executing an instruction with the processor, a first portion of the sample of transaction data for the first type of member that satisfies the target and the first sample size requirement;
generating, by executing an instruction with the processor, an updated target for the characteristic by recalculating the target with the first portion of the sample of transaction data removed from consideration; and
preventing skew due to differential sampling rates in the sample of transaction data by selecting, by executing an instruction with the processor, (a) the first portion of the sample of transaction data and (b) a second portion of the sample of transaction data for the second type of member that satisfies the updated target and the second sample size requirement.
2. A method as defined in claim 1 , wherein the membership program includes an incentive program for registered users.
3. A method as defined in claim 1 , further including applying a purchase threshold filter to the transaction data.
4. A method as defined in claim 1 , further including applying a geographic filter to the transaction data.
5. A method as defined in claim 1 , wherein the defining of the first and second types of member of the membership program includes stratifying the transaction data into first and second strata.
6. A method as defined in claim 1 , wherein the first type of member is a cross-banner household.
7. A method as defined in claim 1 , wherein the second type of member is a single banner household.
8. A method as defined in claim 1 , wherein the calculating of the target is based on a demographic profile.
9. A method as defined in claim 1 , wherein the calculating of the target is based on a geographic profile.
10. A method as defined in claim 1 , wherein the calculating of the target is based on a purchasing behavior profile.
11. An apparatus for selecting a sample of transaction data corresponding to a membership program, the apparatus comprising:
a consumer data generator to:
obtain panelist data for a household via a network and retailer data from a database associated with a retailer;
define a first type of member and a second type of member of the membership program, the first and second types of member defined by a quantity of retailers associated with respective members;
calculate a target for a characteristic of the sample of transaction data based on the panelist data and the retailer data;
calculate a first sample size requirement for the first type of member and a second sample size requirement for the second type of member;
select a first portion of the sample of transaction data for the first type of member that satisfies the target and the first sample size requirement;
generate an updated target for the characteristic by recalculating the target with the first portion of the sample of transaction data removed from consideration; and
prevent skew due to differential sampling rates in the sample of transaction data by selecting, (a) the first portion of the sample of transaction data and (b) a second portion of the sample of transaction data for the second type of member that satisfies the updated target and the second sample size requirement.
12. An apparatus as defined in claim 11 , wherein the consumer data generator is to apply a purchase threshold filter to the transaction data.
13. An apparatus as defined in claim 11 , wherein the consumer data generator is to apply a geographic filter to the transaction data.
14. An apparatus as defined in claim 11 , wherein the consumer data generator is to define the first and second types of member of the membership program by stratifying the transaction data into first and second strata.
15. An apparatus as defined in claim 11 , wherein the consumer data generator is to calculate the target based on a demographic profile.
16. An apparatus as defined in claim 11 , wherein the consumer data generator is to calculate the target based on a purchasing behavior profile.
17. A non-transitory computer readable medium comprising instructions that, when executed, cause a machine to at least:
obtain panelist data for a household via a network and retailer data from a database associated with a retailer;
define a first type of member and a second type of member of a membership program, the first and second types of member defined by a quantity of retailers associated with respective members;
calculate a target for a characteristic of a sample of transaction data associated with the membership program based on the panelist data and the retailer data;
calculate a first sample size requirement for the first type of member and a second sample size requirement for the second type of member;
select a first portion of the sample of transaction data for the first type of member that satisfies the target and the first sample size requirement;
generate an updated target for the characteristic by recalculating the target with the first portion of the sample of transaction data removed from consideration; and
prevent skew due to differential sampling rates in the sample of transaction data by selecting, (a) the first portion of the sample of transaction data and (b) a second portion of the sample of transaction data for the second type of member that satisfies the updated target and the second sample size requirement.
18. A computer readable medium as defined in claim 17 , wherein the instructions, when executed, cause the machine to apply a purchase threshold filter to the transaction data.
19. A computer readable medium as defined in claim 17 , wherein the instructions, when executed, cause the machine to define the first and second types of member of the membership program by stratifying the transaction data into first and second strata.
20. A computer readable medium as defined in claim 17 , wherein the instructions, when executed, cause the machine to calculate the target based on a purchasing behavior profile.