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营销客群标准分-华南地区-服装行业

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北京国际大数据交易所2024-10-18 收录
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https://webs.bjidex.com/sys-bsc-home/#/bscConsole/tradingMarket/detail?id=3566
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资源简介:
该产品采用融合Transformer深度学习模型和神经网络模型,针对华南地区的服装行业营销场景搭建模型,利用卷积神经网络(CNN)的复杂网络结构挖掘模型变量的非线性关系,形成对海量数据高效关联、分析的营销服务产品。本产品引用北京羽乐创新科技有限公司的消费人群洞察、全网标记检测、金盾、响应分等数据服务。通过对通信标签、通信响应、外呼投诉等多维度数据的清洗、整合与分析,运用聚类分析与关联规则挖掘技术,精准构建目标人群消费兴趣、购买潜力、投诉风险等多维度的用户画像。用户仅需输入营销行业、目标群体的区域和人群基本属性,即可精准识别目标人群华南地区服装行业营销活动的匹配度。

This product adopts a hybrid deep learning model integrating Transformer and general neural networks, which is tailored for marketing scenarios of the apparel industry in South China. Leveraging the complex network structure of Convolutional Neural Networks (CNN) to mine the nonlinear relationships among model variables, it enables efficient correlation and analysis of massive data, forming a professional marketing service product. This product utilizes data services including consumer group insight, whole-network tag detection, Jindun, and response score provided by Beijing Yule Innovation Technology Co., Ltd. Through cleaning, integrating and analyzing multi-dimensional data such as communication tags, communication responses, and outbound call complaints, and applying cluster analysis and association rule mining technologies, it accurately constructs multi-dimensional user portraits covering target groups' consumption interests, purchase potential and complaint risks. Users only need to input the marketing industry, the region and basic demographic attributes of the target group, and can accurately identify the matching degree between the target group and marketing activities in the South China apparel industry.
提供机构:
北京羽乐互通信息技术有限公司
搜集汇总
数据集介绍
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背景与挑战
背景概述
该数据集采用Transformer和CNN深度学习模型,整合通信标签、消费洞察等多维数据,为华南地区服装行业提供精准营销客群匹配度分析服务。用户输入行业、区域等基本信息即可获得目标人群的营销活动匹配度评估。
以上内容由遇见数据集搜集并总结生成
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