Methods, systems, articles of manufacture and apparatus for configurable segmentation of product assortments
Methods, apparatus, systems and articles of manufacture are disclosed for text extraction from a receipt image. An example non-transitory computer readable medium is disclosed comprising instructions that, when executed, cause a machine to at least generate a baseline product hierarchy using product information, calculate categorical impact values for products in the baseline product hierarchy, calculate an average impact value for the baseline product hierarchy using the calculated categorical impact values, calculate a first weighting factor for respective ones of the products based on a comparison between the categorical impact values and the average impact value, calculate a second weighting factor associated with respective ones of the products in the baseline product hierarchy based on sales data, and generate final weighted categorical impact values based on (a) the first weighting factors, (b) the second weighting factors and (c) the categorical impact values corresponding to the respective ones of the products.
1. At least one non-transitory machine-readable medium comprising machine-readable instructions to cause at least one processor circuit to at least:
generate a first item hierarchy structure based on item information, the first item hierarchy structure having a parent category and first sub-categories;
generate a second item hierarchy structure based on the item information, the second item hierarchy structure having the parent category and second sub-categories different than the first sub-categories;
determine sub-category impact values for items in the first and second item hierarchy structures;
determine average impact values for the first and second item hierarchy structures using the sub-category impact values;
determine first weighting factors for ones of the items based on a comparison between the sub-category impact values and the average impact values;
generate item relationship matrices for the first and second item hierarchy structures, respective ones of the item relationship matrices including the sub-category impact values modified by (a) second weighting factors associated with respective ones of the items in the first and second item hierarchy structures and (b) sales data;
determine a confidence metric for final weighted categorical impact values, the final weighted categorical impact values corresponding to items in the first and second item hierarchy structures and determined based on (a) the first weighting factors (b) the second weighting factors, and (c) the modified sub-category impact values;
generate blended categorical impact values based on (a) average values of the final weighted categorical impact values across the first and second item hierarchy structures and (b) the confidence metric of respective ones of the final weighted categorical impact values;
select ones of the blended categorical impact values associated with response criteria corresponding to an item impact query, the selection of blended categorical impact values to form a query result that identifies, with a graphical user interface, impact metrics associated with items of the item impact query; and
add ones of the items to a store shelf based on the impact metrics.
2. The at least one non-transitory machine-readable medium of claim 1 , wherein the machine-readable instructions are to cause one or more of the at least one processor circuit to determine the sub-category impact values using direct impact values from the item information and cross impact values from the item information.
3. The at least one non-transitory machine-readable medium of claim 2 , wherein the direct impact values indicate an effect of a category on itself.
4. The at least one non-transitory machine-readable medium of claim 2 , wherein the cross impact values indicate an effect of a category on its sibling categories.
5. The at least one non-transitory machine-readable medium of claim 2 , wherein the machine-readable instructions are to cause one or more of the at least one processor circuit to determine the sub-category impact values by adding the direct impact values and the cross impact values.
6. The at least one non-transitory machine-readable medium of claim 1 , wherein the machine-readable instructions are to cause one or more of the at least one processor circuit to select final weighted categorical impact values associated with the response criteria to form the query result corresponding to impact metrics in response to the confidence metric satisfying a threshold value.
7. The at least one non-transitory machine-readable medium of claim 1 , wherein the machine-readable instructions are to cause one or more of the at least one processor circuit to determine the first weighting factors for respective ones of the items to be a low weight in response to an average impact value for the first item hierarchy structure being greater than or equal to respective ones of the sub-category impact values.
8. The at least one non-transitory machine-readable medium of claim 1 , wherein the machine-readable instructions are to cause one or more of the at least one processor circuit to determine the first weighting factors for respective ones of the items to be a high weight in response to an average impact value for the first item hierarchy structure being less than respective ones of the sub-category impact values.
9. The at least one non-transitory machine-readable medium of claim 1 , wherein the machine-readable instructions are to cause one or more of the at least one processor circuit to determine the response criteria corresponding to the item impact query based on a grouping of the items from the item information.
10. The at least one non-transitory machine-readable medium of claim 1 , wherein the machine-readable instructions are to cause one or more of the at least one processor circuit to report the query result to cause arrangement of the store shelf to reduce item cannibalization.
11. An apparatus comprising:
interface circuitry;
machine-readable instructions; and
at least one processor circuit to be programmed by the machine-readable instructions to:
generate a first item hierarchy structure based on item information, the first item hierarchy structure having a parent category and first sub-categories;
generate an item hierarchy structure based on the item information, the second item hierarchy structure having the parent category and second sub-categories different than the first sub-categories;
determine sub-category impact values for items in the first and second product item hierarchy structures;
determine average impact values for the first and second item hierarchy structures using the sub-category impact values;
determine first weighting factors for ones of the item based on a comparison between the sub-category impact values and the average impact values;
automatically generate item relationship matrices for the first and second item hierarchy structures, respective ones of the item relationship matrices including the sub-category impact values modified by (a) second factors associated with respective ones of the items in the first and second item hierarchy structures and (b) sales data;
determine a confidence metric for final weighted categorical impact values, the final weighted categorical impact values corresponding to items in the first and second item hierarchy structures and determined based on (a) the first weighting factors (b) the second weighting factors, and (c) the modified sub-category impact values;
generate blended categorical impact values based on (a) average values of the final weighted categorical impact values across the first and second item hierarchy structures and (b) the confidence metric of respective ones of the final weighted categorical impact values;
select ones of the blended categorical impact values associated with response criteria corresponding to an item impact query, the selection of blended categorical impact values to form a query result that identifies, with a graphical user interface, impact metrics associated with items of the item impact query; and
adding ones of the item to a store shelf based on the impact metrics.
12. The apparatus of claim 11 , wherein the confidence metric for final weighted categorical impact values indicates a level of accuracy certainty.
13. A memory for storing data for access by an executable program being executed on a data processing system, comprising:
a data structure stored in the memory, the data structure including information resident in a database used by the executable program including:
a first data object structured to generate a first item hierarchy structure based on item information, the first item hierarchy structure having a parent category and first sub-categories;
a second data object structured to generate a second item hierarchy structure based on the item information, the second item hierarchy structure having the parent category and second sub-categories different than the first sub-categories;
a third data object structured to determine sub-category impact values for items in the first and second item hierarchy structures;
a fourth data object structured to determine average impact values for the first and second item hierarchy structures using the sub-category impact values;
a fifth data object structured to determine first weighting factors for ones of the items based on a comparison between the sub-category impact values and the average impact values;
a sixth data object structured to generate item relationship matrices for the first and second item hierarchy structures, respective ones of the item relationship matrices including the sub-category impact values modified by (a) second weighting factors associated with respective ones of the items in the first and second item hierarchy structures and (b) sales data;
a seventh data object structured to determine a confidence metric for final weighted categorical impact values, the final weighted categorical impact values corresponding to items in the first and second item hierarchy structures and determined based on (a) the first weighting factors (b) the second weighting factors, and (c) the modified sub-category impact values; and
an eighth data object structured to generate blended categorical impact values based on (a) average values of the final weighted categorical impact values across the first and second item hierarchy structures and (b) the confidence metric of respective ones of the final weighted categorical impact values,
the executable program to select ones of the blended categorical impact values associated with response criteria corresponding to an item impact query, the selection of blended categorical impact values to form a query result that identifies, with a graphical user interface, impact metrics associated with items of the item impact query, the ones of the items added to a store shelf based on the impact metrics.