METHODS AND APPARATUS TO IDENTIFY NON-NAMED COMPETITORS
Methods, apparatus, systems and articles of manufacture are disclosed to identify non-named competitors. An example method includes identifying, with a processor, a target item to evaluate in connection with historical market activity data, and improving model evaluation efficiency by optimizing, with the processor, erroneous selection of competitive products by: identifying a rest-of-category (ROC) subset of items in the historical market activity data that exclude a same manufacturer as the target item, identifying a rest-of-manufacturer (ROM) subset of items in the historical market activity data that are associated with the same manufacturer as the target item and exclude a same brand as the target item, and identifying a rest-of-brand (ROB) subset of items in the historical market activity data that are associated with the same brand as the target item and exclude the target item.
1 . A computer-implemented method to improve evaluation efficiency of a model, comprising:
identifying, with a processor, a target item to evaluate in connection with historical market activity data; and
improving model evaluation efficiency by optimizing, with the processor, erroneous selection of competitive products by:
identifying a rest-of-category (ROC) subset of items in the historical market activity data that exclude a same manufacturer as the target item;
identifying a rest-of-manufacturer (ROM) subset of items in the historical market activity data that are associated with the same manufacturer as the target item and exclude a same brand as the target item; and
identifying a rest-of-brand (ROB) subset of items in the historical market activity data that are associated with the same brand as the target item and exclude the target item.
2 . The computer-implemented method as defined in claim 1 , wherein the ROC subset, the ROM subset and the ROB subset encapsulate all competitive items of a category associated with the target item.
3 . The computer-implemented method as defined in claim 1 , further including identifying competitive measures for the ROC subset, the ROM subset and the ROB subset.
4 . The computer-implemented method as defined in claim 3 , wherein the competitive measures include a distribution level.
5 . The computer-implemented method as defined in claim 1 , further including analyzing a candidate product from the historical market activity data for a promotional indicator.
6 . The computer-implemented method as defined in claim 5 , further including removing over-parameterization errors of the model by preventing promotional terms associated with the candidate product from influencing the model when the promotional indicator is absent.
7 . The computer-implemented method as defined in claim 1 , further including associating a set of surrogate competitive terms with the ROC subset of items to cause the model to identify, during evaluation by the processor, which ones of the set of surrogate competitive terms affects the target item compared to items in the historical market activity data that are unassociated with the same manufacturer as the target item.
8 . The computer-implemented method as defined in claim 7 , wherein the set of surrogate competitive terms includes at least one of distribution activity, value on promotion activity, regular price activity or promoted price activity.
9 . The computer-implemented method as defined in claim 1 , further including associating a set of surrogate competitive terms with the ROM subset of items to cause the model to identify, during evaluation by the processor, which ones of the set of surrogate competitive terms affects the target item compared to items in the historical market activity data that are associated with the same manufacturer and a brand dissimilar to the target item.
10 . The computer-implemented method as defined in claim 1 , further including associating a set of surrogate competitive terms with the ROB subset of items to cause the model to identify, during evaluation by the processor, which ones of the set of surrogate competitive terms affects the target item compared to items in the historical market activity data that are associated with the same brand as the target item and having alternate features of the target item.
11 . The computer-implemented method as defined in claim 1 , wherein optimizing erroneous selection of competitive products includes at least one of reducing erroneous selection of competitive products or including a selection of competitive products that exhibit an influence.
12 . An apparatus to improve evaluation efficiency of a model, comprising:
a target engine to identify a target item to evaluate in connection with historical market activity data;
a competitor grouping engine to improve model evaluation efficiency by optimizing erroneous selection of competitive products via;
a rest-of-category (ROC) identifier to identify a subset of items in the historical market activity data that exclude a same manufacturer as the target item;
a rest-of-manufacturer (ROM) identifier to identify a subset of items in the historical market activity data that are associated with the same manufacturer as the target item and exclude a same brand as the target item; and
a rest-of-brand (ROB) identifier to identify a subset of items in the historical market activity data that are associated with the same brand as the target item and exclude the target item.
13 . The apparatus as defined in claim 12 , wherein the ROC subset, the ROM subset and the ROB subset encapsulate all competitive items of a category associated with the target item.
14 . The apparatus as defined in claim 12 , wherein the competitor grouping engine is to identify competitive measures for the ROC subset, the ROM subset and the ROB subset.
15 . The apparatus as defined in claim 14 , wherein the competitive measures include a distribution level.
16 . The apparatus as defined in claim 12 , further including a competitive promotion engine to analyze a candidate product from the historical market activity data for a promotional indicator.
17 . A tangible computer readable storage medium comprising instructions that, when executed, causes a processor to, at least:
identify a target item to evaluate in connection with historical market activity data;
improve model evaluation efficiency by optimizing erroneous selection of competitive products by:
identifying a rest-of-category (ROC) subset of items in the historical market activity data that exclude a same manufacturer as the target item;
identifying a rest-of-manufacturer (ROM) subset of items in the historical market activity data that are associated with the same manufacturer as the target item and exclude a same brand as the target item; and
identifying a rest-of-brand (ROB) subset of items in the historical market activity data that are associated with the same brand as the target item and exclude the target item.
18 . The machine readable instructions as defined in claim 17 , wherein the instructions, when executed, cause the processor to encapsulate all competitive items of a category associated with the target item based on the ROC subset, the ROM subset and the ROB subset.
19 . The machine readable instructions as defined in claim 17 , wherein the instructions, when executed, cause the processor to identify competitive measures for the ROC subset, the ROM subset and the ROB subset.
20 . The machine readable instructions as defined in claim 17 , wherein the instructions, when executed, cause the processor to analyze a candidate product from the historical market activity data for a promotional indicator.