The Impact of Marketing Automation on Consumer Buying Behavior in the Digital Space Via Artificial Intelligence

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Payam Boozary, Iman Hosseini, Mobina Pourmirza, Hamed GhorbanTanhaei, Sogand Sheykhan


In this research, the role of marketing automation in the identification and analysis of consumer buying behavior patterns in the digital space has been examined. The article explores the application of neural networks in opinion mining, detailing the performance improvements achieved by using a memetic neural network over a standard neural network. The initial tests on a dataset with a standard neural network resulted in a Mean Squared Error (MSE) of 0.004 and a Root Mean Squared Error (RMSE) of 0.03. In contrast, the memetic neural network significantly enhanced accuracy, reducing the MSE to 0.00045 and the RMSE to 0.0028. Using artificial intelligence and advanced algorithms, this method enables the collection and analysis of large and diverse data sets, helping companies to accurately and precisely predict customer behavior and identify patterns. This leads to the provision of more useful information for strategic decision-making in marketing. Additionally, marketing automation allows businesses to maintain continuous and targeted communication with their customers. Furthermore, automation tools enhance the digital shopping experience by providing customers with quick and appropriate responses through relevant content, product recommendations, and special discounts. Ultimately, this method reduces the costs and time required for data analysis, as the process is automated and does not require human intervention.

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