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• W4387604401 abstract "<p>In today’s technologically advanced landscape, where data flows in unparalleled volumes, the power of data mining stands out as a transformative force. Its capabilities extend beyond mere analysis; data mining can be harnessed to create intricate and detailed profiles of various consumer groups. This is particularly pertinent to the agricultural sector, which has long grappled with challenges of reaching its consumers effectively. The quest to refine and elevate marketing strategies for agricultural products amidst this data deluge led us to a methodical approach. We initiated this by sourcing and cleansing customer analysis datasets from Baidu AI, a leading platform in the realm of artificial intelligence and data analytics. Such a foundational step ensured that the data underpinning our analysis was robust and free of inconsistencies. The subsequent analytical journey, comprising rigorous data exploration and the utilization of the <em>K</em>-means clustering method, allowed us to dissect and segment the vast data pool. Through this, we crafted a comprehensive consumer profile that is tailor-made for agricultural product consumption. Such segmentation offers invaluable insights, paving the way for marketers and producers to understand their audience’s nuances. Our research findings highlight the remarkable prowess of the <em>K</em>-means clustering technique. When underpinned by sophisticated intelligent algorithms, it doesn’t just cluster data; it offers a pathway to identify distinct customer segments, shed light on core product offerings that resonate with them, and sculpt effective marketing strategies. By integrating these insights with modern media channels, we can craft marketing narratives that echo the desires and needs of the target demographic. Such a precision-driven approach ensures a symbiotic relationship where products align seamlessly with customer preferences. Beyond meeting immediate needs, this alignment has broader implications. It allows enterprises to tap into the vast opportunities presented by the digital era, positioning them on a trajectory of sustained growth and relevance in an ever-evolving market landscape.</p>" @default.
• W4387604401 created "2023-10-14" @default.
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• W4387604401 date "2023-10-13" @default.
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• W4387604401 title "Construction of agricultural product consumer group portrait and analysis of precision marketing strategies based on K-means cluster analysis" @default.
• W4387604401 doi "https://doi.org/10.32629/jai.v7i1.903" @default.
• W4387604401 hasPublicationYear "2023" @default.
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