Intel > 实例探究 > 机器学习帮助英特尔重新发现他们的客户群体

机器学习帮助英特尔重新发现他们的客户群体

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 Machine Learning Helps Intel Rediscover Their Customer Demographic  - IoT ONE Case Study
技术
  • 分析与建模 - 机器学习
适用行业
  • 电子产品
适用功能
  • 销售与市场营销
挑战

英特尔的销售和营销部门致力于在新的行业细分市场发展时加强与经销商的沟通,并鼓励经销商参加网络研讨会或会议,以更好地了解英特尔为这些新市场提供的产品。因为销售和营销团队必须将他们的资源集中在那些最有可能产生销售的经销商身上,所以向正确的经销商发送正确的信息有助于提高销售渠道的价值。我们需要一个机器学习系统来帮助我们的销售和营销团队在英特尔庞大的经销商群中确定最佳前景。

客户
关于客户
英特尔处理器在所有类型的计算垂直领域的经销商。
解决方案

在英特尔,我们正在迅速将机器学习从学术追求转变为推动创新并为我们的业务带来竞争优势的驱动力。为此,英特尔 IT 开发了一种机器学习工具,可帮助英特尔的销售和营销部门确定哪些经销商最适合与特定垂直行业的客户建立联系。

机器学习算法帮助我们更多地了解我们的
通过对经销商进行分类,然后用另一种挖掘经销商网站内容的算法来补充这些信息。

收集的数据
Customer Satisfaction Score, Sales
运营影响

  • Intel IT developed a tool named “Reseller Knowledge Base” to help Intel sales and marketing teams tap into Intel’s customer base and identify the resellers that offer the highest probability for sales. To offer a general- purpose knowledge base system, we created a multilayered approach composed of three parts.  

    Part 1:

    Web Insights.  This web mining tool allows users to train a semantic model using a search query and subsequently label pages from any reseller
    or potential reseller’s website. By evaluating reseller website content, WebInsights tells us what resellers tell their customers.


  • Part 2.

    Reseller Insights.  This predictive system uses Intel’s CRM information and learns from the output of the WebInsights tool to find patterns in the data that can predict which resellers are most likely to respond to marketing campaigns. ResellerInsights also reveals reseller focus by evaluating the Intel training that the resellers take and the questionnaires they complete.


  • Part 3.

    SMART Target. This reverse recommendation system finds the resellers most likely to buy and sell Intel® products by unveiling resellers’ buying patterns.

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