Abstract: Systems and methods for attribute-based modelling are disclosed. A system includes an attribute-based decomposition engine, which when executed using a processor, causes the engine to retrieve one or more product attributes associated with each of a set of products, an importance of the product attributes being determined based on the product sales data, product data, product parameters, and financial data associated with product. The attribute-based decomposition engine using the processor establishes, for a set of products, a relationship between a retrieved one or more product attributes and product sales associated with product, based on implementation of a non-parametric machine learning (ML) modeling on a data model. The attribute-based decomposition engine quantifies contribution of each product attribute on product sales based on an established relationship and a game theoretic framework.

Abstract: Systems and methods for facilitating automated estimation of factors influencing product sales are disclosed. The system may include a data pre-processor and a data analyzer. The data pre-processor may generate an input dataset that may pertain to a captured trend of product sales associated with a product. The data analyzer may analyze the input dataset using a state space model to generate a state space representation indicative of a plurality of observations. The data analyzer may process the state space representation through Kalman filtering algorithm combined with the state space model to facilitate estimation of a state variable. The state variable may be indicative of a factor influencing the captured trend. Based on the factor influencing the captured trend of product sales, the system may generate one or more automated insights.