Methods and apparatus to identify affinity between segment attributes and product characteristics
Methods, apparatus, systems and articles of manufacture are disclosed to identify affinity between segment attributes and product characteristics. An example method includes identifying, with a processor, a set of product characteristics from purchase transactions that exhibit a threshold product affinity, selecting, with the processor, a set of products having at least one product characteristic from the set of product characteristics that exhibit the threshold product affinity, the set of products associated with first segments, extracting, with the processor, segment attributes from the first segments, and improving a market success of the product of interest by identifying, with the processor, target segments based on ones of the extracted segment attributes exhibiting a threshold segment affinity.
1. An apparatus comprising:
a product characteristic database storing product identifications (IDs) for a plurality of products and one or more product characteristics associated with respective ones of the product IDs;
a transaction database storing past transactions and one or more of the product characteristics associated with one or more products in respective ones of the past transactions;
a product affinity generator to:
in response to receipt of a first transaction that includes a first product and a second product, access the product characteristic database to identify a first product characteristic corresponding to the first product and a second product characteristic corresponding to the second product, the first transaction received via a network from a first transaction processor;
access the transaction database and perform a comparison of an occurrence of the first product characteristic and the second product characteristic in the same transaction to a frequency support threshold;
define a level of association between the first product characteristic and the second product characteristic based on the comparison; and
generate an affinity rule based on the level of association between the first product characteristic and the second product characteristic; and
a product recommender to:
in response to receipt of a second transaction that includes a third product, access the product characteristic database and identify a third product characteristic corresponding to the third product, the second transaction received via the network from a second transaction processor during a point-of-sale activity;
generate a recommendation for a fourth product in connection with the second transaction based on the affinity rule and the third product characteristic; and
cause an advertisement including the fourth product to be transmitted to the second transaction processor for presentation during the point-of-sale activity.
2. The apparatus of claim 1 , wherein the first product characteristic includes one or more of a brand associated with the first product, a product type associated with the first product, a color associated with the first product, or packaging associated with the first product.
3. The apparatus of claim 1 , wherein the affinity rule is a first affinity rule and the product affinity generator is to generate a second affinity rule based on the third product and the fourth product.
4. The apparatus of claim 1 , wherein the first product and the second product define a first transaction set and the product affinity generator is to:
identify, based on the third product characteristic, a second transaction set including a fifth product and a sixth product; and
generate the affinity rule based on the second transaction set.
5. The apparatus of claim 4 , wherein the product affinity generator is to:
identify a third transaction set;
perform a comparison of a product characteristic associated with the third transaction set to the frequency support threshold;
generate the affinity rule based on the second transaction set if the third transaction satisfies the frequency support threshold; and
refrain from using the third transaction set to generate the affinity rule if the third transaction set does not satisfy the frequency support threshold.
6. The apparatus of claim 1 , wherein the product affinity generator is to identify the first product and the second product based on one or more of an establishment type associated with the second transaction or a product category associated with the second transaction.
7. The apparatus of claim 1 , wherein the product affinity generator is to:
assign a confidence level to the level of association between the first product characteristic and the second product characteristic; and
generate the affinity rule in response to the assignment of the confidence level to the level of association.
8. A non-transitory computer readable storage medium comprising instructions that, when executed, cause at least one machine to at least:
in response to receipt of a first transaction that includes a first product and a second product, access a product characteristic database storing product identifications (IDs) for a plurality of products and one or more product characteristics associated with respective ones of the product IDs, the first transaction received via a network from a first transaction processor;
identify in the product characteristic database a first product characteristic corresponding to the first product and a second product characteristic corresponding to the second product;
access a transaction database storing past transactions and one or more of the product characteristics associated with one or more products in respective ones of the past transactions;
perform a comparison of an occurrence of the first product characteristic and the second product characteristic in the same transaction to a frequency support threshold;
define a level of association between the first product characteristic and the second product characteristic based on the comparison;
generate an affinity rule based on the level of association between the first product characteristic and the second product characteristic;
in response to receipt of a second transaction that includes a third product, access the product characteristic database and identify a third product characteristic corresponding to the third product, the second transaction received via the network from a second transaction processor during a point-of-sale activity;
generate a recommendation for a fourth product in connection with the second transaction based on the affinity rule and the third product characteristic; and
cause an advertisement including the fourth product to be transmitted to the second transaction processor for presentation during the point-of-sale activity.
9. The non-transitory computer readable storage medium of claim 8 , wherein the first product characteristic includes one or more of a brand associated with the first product, a product type associated with the first product, a color associated with the first product, or packaging associated with the first product.
10. The non-transitory computer readable storage medium of claim 8 , wherein the affinity rule is a first affinity rule and the instructions, when executed, cause the at least one machine to generate a second affinity rule based on the third product and the fourth product.
11. The non-transitory computer readable storage medium of claim 8 , wherein the first product and the second product define a first transaction set and the instructions, when executed, cause the at least one machine to:
identify, based on the third product characteristic, a second transaction set including a fifth product and a sixth product; and
generate the affinity rule based on the second transaction set.
12. The non-transitory computer readable storage medium of claim 11 , wherein the instructions, when executed, cause the at least one machine to:
identify a third transaction set;
perform a comparison of a product characteristic associated with the third transaction set to the frequency support threshold;
generate the affinity rule based on the second transaction set if the third transaction satisfies the frequency support threshold; and
refrain from using the third transaction set to generate the affinity rule if the third transaction set does not satisfy the frequency support threshold.
13. The non-transitory computer readable storage medium of claim 8 , wherein the instructions, when executed, cause the at least one machine to identify the first product and the second product based on one or more of an establishment type associated with the second transaction or a product category associated with the second transaction.
14. The non-transitory computer readable storage medium of claim 8 , wherein the instructions, when executed, cause the at least one machine to:
assign a confidence level to the level of association between the first product characteristic and the second product characteristic; and
generate the affinity rule in response to the assignment of the confidence level to the level of association.
15. An apparatus comprising:
a product characteristic database storing product identifications (IDs) for a plurality of products and one or more product characteristics associated with respective ones of the product IDs;
a transaction database storing past transactions and one or more of the product characteristics associated with one or more products in respective ones of the past transactions;
and
at least one processor to execute instructions to:
in response to receipt of a first transaction that includes a first product and a second product, access the product characteristic database to identify a first product characteristic corresponding to the first product and a second product characteristic corresponding to the second product, the first transaction received via a network from a first transaction processor;
access the transaction database and perform a comparison of an occurrence of the first product characteristic and the second product characteristic in the same transaction to a frequency support threshold;
define a level of association between the first product characteristic and the second product characteristic based on the comparison;
generate an affinity rule based on the level of association between the first product characteristic and the second product characteristic;
in response to receipt of a second transaction that includes a third product, access the product characteristic database and identify a third product characteristic corresponding to the third product, the second transaction received via the network from a second transaction processor during a point-of-sale activity;
generate a recommendation for a fourth product in connection with the second transaction based on the affinity rule and the third product characteristic; and
cause an advertisement including the fourth product to be transmitted to the second transaction processor for presentation during the point-of-sale activity.
16. The apparatus of claim 15 , wherein the first product characteristic includes one or more of a brand associated with the first product, a product type associated with the first product, a color associated with the first product, or packaging associated with the first product.
17. The apparatus of claim 15 , wherein the affinity rule is a first affinity rule and the at least one processor is to generate a second affinity rule based on the third product and the fourth product.
18. The apparatus of claim 15 , wherein the at least one processor is to:
assign a confidence level to the level of association between the first product characteristic and the second product characteristic; and
generate the affinity rule in response to the assignment of the confidence level to the level of association.
19. The apparatus of claim 15 , wherein the first product and the second product define a first transaction set and the at least one processor is to:
identify, based on the third product characteristic, a second transaction set including a fifth product and a sixth product; and
generate the affinity rule based on the second transaction set.
20. The apparatus of claim 19 , wherein the at least one processor is to:
identify a third transaction set;
perform a comparison of a product characteristic associated with the third transaction set to the frequency support threshold;
generate the affinity rule based on the second transaction set if the third transaction satisfies the frequency support threshold; and
refrain from using the third transaction set to generate the affinity rule if the third transaction set does not satisfy the frequency support threshold.