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Data Driven Web Experimentation on Design and Personalization

机译:数据驱动的Web实验设计和个性化

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In today's world for we use online medium for virtually every aspect of our lives. Companies run controlled web experiments to make data driven decisions, to provide an intuitive online experience. We see a big correlation between online customer behaviors and designs and personal treatment, which could be used to create better customer engagement. In this paper we have studied the impact of design elements on chat invites~*, by running experiments on a small population, using machine learning algorithms. Based on this we identify significant elements and build the most opportune personalized messages on invites. Statistical results show that, more visitors on the website accept chat invites which are personalized and optimized for the design. At [24]7, we have experimented extensively on user inter-face designs and journey based personalization which resulted in positive impact on our annual revenue.
机译:在今天的世界中,我们在线媒体使用了我们生活的几乎各个方面。 公司运行受控的网络实验来制作数据驱动的决策,提供直观的在线体验。 我们在线客户行为和设计与个人待遇之间看到了大关,可用于创造更好的客户参与。 在本文中,我们研究了使用机器学习算法运行小人物的实验,研究了设计元素对聊天邀请仪〜*的影响。 基于此,我们确定了重要的因素,并在邀请上建立最合适的个性化信息。 统计结果表明,网站上更多的访客接受聊天邀请,这些邀请是为设计的个性化和优化的聊天邀请。 在[24] 7中,我们在用户面部间设计和基于旅程的个性化上进行了实验,这导致了对我们的年度收入的积极影响。

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