了解你的客户的 "要做的工作"

Innovation success rates are shockingly low worldwide, and have been for decades.

创新的成功率在世界范围内低得令人震惊,几十年来一直如此。

What’s Needed
需要什么

Marketers and product developers focus too much on customer profiles and on correlations unearthed in data, and not enough on what customers are trying to achieve in a particular circumstance.

营销人员和产品开发人员过多地关注客户档案和数据中发现的相关性,而对客户在特定情况下想要实现的目标关注不够。

What’s Effective
什么是有效的

Successful innovators identify poorly performed “jobs” in customers’ lives—and then design products, experiences, and processes around those jobs.

成功的创新者会发现客户生活中表现不佳的 "工作",然后围绕这些工作设计产品、体验和流程。

For as long as we can remember, innovation has been a top priority—and a top frustration—for leaders. In a recent McKinsey poll, 84% of global executives reported that innovation was extremely important to their growth strategies, but a staggering 94% were dissatisfied with their organizations’ innovation performance. Most people would agree that the vast majority of innovations fall far short of ambitions.

从我们有记忆以来,创新一直是领导者的首要任务,也是他们的首要挫折。在最近的一次麦肯锡民意调查中,84%的全球高管报告说,创新对他们的增长战略极为重要,但令人吃惊的是,94%的人对他们组织的创新表现感到不满意。大多数人都会同意,绝大多数的创新都远远没有达到预期的目标。

On paper, this makes no sense. Never have businesses known more about their customers. Thanks to the big data revolution, companies now can collect an enormous variety and volume of customer information, at unprecedented speed, and perform sophisticated analyses of it. Many firms have established structured, disciplined innovation processes and brought in highly skilled talent to run them. Most firms carefully calculate and mitigate innovations’ risks. From the outside, it looks as if companies have mastered a precise, scientific process. But for most of them, innovation is still painfully hit-or-miss.

从纸面上看,这没有任何意义。企业从未如此了解他们的客户。由于大数据革命,企业现在可以以前所未有的速度收集种类繁多、数量巨大的客户信息,并对其进行精密分析。许多公司已经建立了结构化、规范化的创新流程,并引进了高技能人才来管理这些流程。大多数公司仔细计算和减轻创新的风险。从外面看,公司似乎已经掌握了一个精确的、科学的过程。但对大多数公司来说,创新仍然是痛苦的,不成功便成仁。

What has gone so wrong?

什么地方出了这么大的问题?

The fundamental problem is, most of the masses of customer data companies create...

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