ACC
Intelligent Supply Chain Collaboration Models in Retail Supported by Omnichannel Marketing Data
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Abstract
As the retail channel touchpoints continue to expand, marketing data such as search, browsing, add to cart, member interaction, evaluation, and return/exchange have become important variables for identifying demand changes at the front end of the supply chain. Focusing on the transformation of omnichannel marketing data into supply chain collaborative decision-making, an intelligent collaborative framework consisting of data governance, demand perception, inventory linkage, supplier response, and fulfillment scheduling is constructed. A benchmark group and experimental group are set up based on the full-channel promotion scenario for comparison, and the model performance is tested by evaluating prediction errors, shortage rates, inventory turnover, on-time fulfillment rates, and replenishment response cycles. The results show that after embedding marketing behavior variables into the prediction and inventory allocation processes, it is possible to identify rising demand earlier, compress the replenishment lag, and reduce channel inventory mismatch, enabling the retail supply chain to form a more stable resource allocation and service fulfillment capability in the face of market fluctuations.
Keywords
Omnichannel marketing data; retail supply chain; intelligent collaboration; demand perception; inventory optimization
References
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How to cite this paper
Intelligent Supply Chain Collaboration Models in Retail Supported by Omnichannel Marketing Data
How to cite this paper: Xinyan Qian. (2026) Intelligent Supply Chain Collaboration Models in Retail Supported by Omnichannel Marketing Data. Advances in Computer and Communication, 7(3), 154-158.
DOI: http://dx.doi.org/10.26855/acc.2026.09.008
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