System and method for determining retail-business-rule coefficients from current prices
Business rules can govern a single price or they can define relationships between different products involving two or more decision prices. One problem that retailers can face is that business rules are generally not codified and are rarely followed consistently, and thus it can be difficult to articulate existing business rules or generate new business rules. However, existing price information inherently contains industry knowledge and experience, even if retailers find it difficult to express that knowledge. The disclosed technology generates business rules by reverse engineering rule bounds and coefficients from existing price information. The reverse engineered rule bounds and coefficients can be used in price optimization to generate recommended prices for retail products that optimize revenue and profit while complying with a set of business rules.
1. A computer-implemented method comprising:
obtaining existing price information for one or more products;
calculating, via a processor, one or more target prices based at least in part on the existing price information;
generating price bounds for each rule in a set of bounded rules, wherein the set of bounded rules is based at least in part on the one or more calculated target prices;
generating rule parameters for each rule in a set of comparative rules, wherein the set of comparative rules is based at least in part on the existing price information; and
generating at least one recommended price for at least one of the one or more products by applying the price bounds and the rule parameters to the existing price information.
2. The computer-implemented method of claim 1 , further comprising:
for each comparative rule in the set of comparative rules, determining whether the comparative rules is stable.
3. The computer-implemented method of claim 2 , where the determination of stability is based on a statistical confidence measurement.
4. The computer-implemented method of claim 2 , wherein each comparative rule in the set of comparative rules is one of a named comparative rule or a measured comparative rule.
5. The computer-implemented method of claim 1 , wherein for each bounded rule in the set of bounded rules generating an upper bound value, a lower bound value and a target value.
6. The computer-implemented method of claim 5 , wherein each bounded rule in the set of bounded rules is one of a competitive bounded rule, a margin bounded rule, a step-size bounded rule, or a general bounded rule.
7. The computer-implemented method of claim 1 , wherein the price information comprises at least one of product attributes, competitive prices, reference prices, or current price.
8. At least one non-transitory computer-readable storage medium, storing instructions which, when executed by a processor, causes the processor to:
obtain existing price information for one or more products;
calculate one or more target prices based at least in part on the existing price information;
generate price bounds for each rule in a set of bounded rules, wherein the set of bounded rules is based at least in part on the one or more calculated target prices;
generate rule parameters for each rule in a set of comparative rules, wherein the set of comparative rules is based at least in part on the existing price information; and
generate at least one recommended price for at least one of the one or more products by applying the price bounds and the rule parameters to the existing price information.
9. The at least one non-transitory computer-readable storage medium of claim 8 , further comprising instructions which when executed by the processor causes the processor to:
for each comparative rule in the set of comparative rules, determine whether the comparative rules is stable.
10. The computer-implemented method of claim 9 , where the determination of stability is based on a statistical confidence measurement.
11. The computer-implemented method of claim 9 , wherein each comparative rule in the set of comparative rules is one of a named comparative rule or a measured comparative rule.
12. The computer-implemented method of claim 8 , wherein for each bounded rule in the set of bounded rules generate an upper bound value, a lower bound value and a target value.
13. The computer-implemented method of claim 12 , wherein each bounded rule in the set of bounded rules is one of a competitive bounded rule, a margin bounded rule, a step-size bounded rule, or a general bounded rule.
14. The computer-implemented method of claim 8 , wherein the price information comprises at least one of product attributes, competitive prices, reference prices, or current price.
15. A system comprising:
a processor; and
a memory storing instructions which, when executed by the processor, causes the processor to:
obtain existing price information for one or more products;
calculate one or more target prices based at least in part on the existing price information;
generate price bounds for each rule in a set of bounded rules, wherein the set of bounded rules is based at least in part on the one or more calculated target prices;
generate rule parameters for each rule in a set of comparative rules, wherein the set of comparative rules is based at least in part on the existing price information; and
generate at least one recommended price for at least one of the one or more products by applying the price bounds and the rule parameters to the existing price information.
16. The system of claim 15 , further comprising instructions which when executed by the processor causes the processor to:
for each comparative rule in the set of comparative rules, determine whether the comparative rules is stable.
17. The system of claim 16 , where the determination of stability is based on a statistical confidence measurement.
18. The system of claim 16 , wherein each comparative rule in the set of comparative rules is one of a named comparative rule or a measured comparative rule.
19. The system of claim 15 , wherein for each bounded rule in the set of bounded rules generate an upper bound value, a lower bound value and a target value.
20. The system of claim 19 , wherein each bounded rule in the set of bounded rules is one of a competitive bounded rule, a margin bounded rule, a step-size bounded rule, or a general bounded rule.