Title: The application and optimisation of extensive data analysis in the evaluation of the effect of marketing strategies on agricultural machinery enterprises

Authors: Wei Shen

Addresses: Wuxi Normal College, No. 45, Wenliang Road, Huishan District, Wuxi City, 214153, China

Abstract: Effective decision-making is crucial for business growth, particularly when financial factors are involved. This study employs AI models to analyse the relationship between selected agroeconomic indicators and digital marketing data. It is essential to explain how these metrics influence decision-making. Data was collected from the websites of five leading agricultural companies, where index values were recorded and compiled. Psychological stress and depression assessments were used to explore potential correlations with digital marketing usage. Artificial neural network (ANN) models were applied to establish these connections. Key metrics include advertising traffic sources, business-related expenses (both incurred and avoided), and overall digital engagement. Increasingly, large agricultural firms are being advised to invest in AI and digital marketing tools. These technologies help them better understand employment trends and fluctuations in prices of equipment, medications, and agricultural inputs. As a result, companies can make more informed decisions and develop more effective business strategies.

Keywords: agroeconomic indexes; big data; AI; ANN; artificial neural network; digital marketing; digital transformation; predictive analytics; agriculture; DSS; decision support systems.

DOI: 10.1504/IJTPM.2026.154790

International Journal of Technology, Policy and Management, 2026 Vol.26 No.2, pp.179 - 199

Received: 15 May 2025
Accepted: 05 Aug 2025
Published online: 14 Jul 2026 *

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