Abstract: A device may receive and transform metric data and share of voice data, associated with digital marketing by an entity, into transformed data, may generate model data from the transformed data, and may divide the model data into training data, test data, and validation data. The device may train models, with the training data, to generate training results, and may process the test data, with the models, to generate test results. The device may process the validation data, with the models, to generate validation results, and may select a first model, a second model, and a third model based on the results. The device may utilize the first model to predict a share of voice, and may utilize the second model to predict a click through rate. The device may utilize the third model to predict a conversion rate, and may perform actions based on the predicted data.

Abstract: A device may receive and transform metric data and share of voice data, associated with digital marketing by an entity, into transformed data, may generate model data from the transformed data, and may divide the model data into training data, test data, and validation data. The device may train models, with the training data, to generate training results, and may process the test data, with the models, to generate test results. The device may process the validation data, with the models, to generate validation results, and may select a first model, a second model, and a third model based on the results. The device may utilize the first model to predict a share of voice, and may utilize the second model to predict a click through rate. The device may utilize the third model to predict a conversion rate, and may perform actions based on the predicted data.

Abstract: A system selects a set of advertisement media associated with a product. A set of persistent advertisement media from the set of advertisement media is identified based on one or more tests. A Gaussian Bayesian (GB) network based on the set of advertisement media. A net persistence rate for each of the set of persistent advertisement media is determined based on the GB network. a competitor factor associated with another vendor of the product is computed based on one or more marketing parameters associated with the another vendor. A predicted sales (PS) value associated with each of the set of persistent advertisement media is determined. A persistent advertisement medium is selected in real time based on corresponding PS value. An advertisement is rendered on the selected persistent advertisement medium in real time for marketing the product.

Abstract: A system provides a configurable market mix modeling (MMM) platform based on machine-learning (ML). The system may include configurable MMM pipelines in which an end user may identify portions and/or inputs to the MMM pipelines to be included or excluded from ML modeling. The system may apply ML to market data to automatically discover variables that correlate with a key performance indicator (PKI) such as sales to be used for modeling. The system may automatically generate multiple models, filter the models for robustness and ensemble the filtered models to generate a unified model. The unified model may be optimized using a multi-layered approach and introducing deviations into the model.

Abstract: A system selects a set of advertisement media associated with a product. A set of persistent advertisement media from the set of advertisement media is identified based on one or more tests. A Gaussian Bayesian (GB) network based on the set of advertisement media. A net persistence rate for each of the set of persistent advertisement media is determined based on the GB network. a competitor factor associated with another vendor of the product is computed based on one or more marketing parameters associated with the another vendor. A predicted sales (PS) value associated with each of the set of persistent advertisement media is determined. A persistent advertisement medium is selected in real time based on corresponding PS value. An advertisement is rendered on the selected persistent advertisement medium in real time for marketing the product.