The Two Core Competencies

The Two Core Competencies

两类核心竞争力

Good product teams must be good at product discovery, which means they must get good at learning quickly. They need to be able to zero in on the appropriate target customer, identify the key problems to solve for those customers, and typically the most difficult part of all, apply technology and user experience design to come up with good solutions that will solve those problems.

好的产品团队必须擅于产品发现,这就意味着他们必须善于快速地学习。他们需要能够对准适当的目标客户,确定要为那些客户解决的关键问题,通常这是最困难的部分,应用技术和用户体验设计去提出好的解决方案将会解决那些问题。

Our general principle is that we want to learn – test our theories – as fast and cheap as possible.  We have two general approaches to doing so: one qualitative and the other quantitative.

我们的一般原则是我们想去学习-测试我们的理论-尽可能的快并且便宜。我们有两种通常的方法这样去做-一种是定性,另一个就是定量。

User prototyping and user testing:

用户原型设计和用户测试:

User prototypes are very quickly created simulations of the product you’re proposing to build.

用户原型被非常快的创造出来以模拟你将要构建的产品。

The main reason we create them is to be able to very quickly put them in front of real target users and customers, generally face-to-face, and test the response.

我们创建它们的主要原因是能够非常快的置它们于真实的目标用户和客户前面,通常是面对面的来测试这个反映。

The big benefits of user prototypes are that they’re quick and easy to create, generally hours or days; they don’t require developer resources to create; and we can get significant qualitative insights into how the product would be used, whether it will address the customer’s problem or need, and whether people would actually choose to use it or not.

用户原型的益处在于它们是快速并且容易创建的,通常只需几个小时或者几天;它们不需要开发资源去创建;我们能够得到有效的定性来洞悉产品将会被如何使用,无论是明确客户的问题或是需要,也不论人们将是否事实上选择使用或是不选择。

A user prototype is not about statistically significant results; it’s about big insights and rapid learning.

一个用户原型不是统计意义上的结果;它只是针对深刻的洞察和快速学习的。

Live-data prototyping and split testing:

实时数据原型构建和分离测试:

A live-data prototype is real code that’s typically just deployed to a subset of users in some form of an A/B test.

实时数据原型是真实的代码,通常只是以A/B test(译者注:A/B测试是一种新兴的网页优化方法,可以用于增加转化率注册率等网页指标。)的形式部署到用户的一个子集。

The big advantage of a live-data prototype is that we can gather statistically significant results and prove something actually works or doesn’t work.

实时数据原型的最大优势在于我们能够收集具有统计意义的结果和证明某些事事实上在运转或者不运转。

Another advantage of a live-data prototype is that we can also test them face to face in a user test just as we do with a user prototype.

实时数据原型的另一个优势是我们也能够面对面的以用户测试的形式测试它们,就像我们基于用户原型所做的那样。

The big disadvantage of live-data prototypes is that since it’s real code, it needs to be written by developers and it typically takes days or weeks to create rather than hours.

实时数据原型最大的不足是因为它是真实的代码,因此它需要由开发人员来编写,由此需要花费超过几个小时的几天或者几个星期来创建。

Because of our general principle that we want to learn as fast and cheap as possible, this generally means a user prototype, however, for many things we simply can’t learn whether something works without live-data, and in those cases we need live-data prototypes.

因为我们的一般原则是我们想尽可能地又快又便宜的学习,这通常就意味着一个用户原型,然而,在许多情况下,我们不能脱离实时数据来学习我们不能简单学习的事情,在这种情况下,我们需要实时数据原型。

When trying to decide which technique is most appropriate for the situation, one general rule of thumb is:

当试图决定哪些技术是最适合的情况下,一个通用的规则是:

We can best prove something works with live-data prototypes and split testing, but we can best understand why something doesn’t work, and most importantly, what it would take to make it work, with face-to-face user testing.

我们能够基于实时数据原型和分离测试来证明一些事情在运转,但是我们也能更好的明白某事为什么不运转,最重要的是,它将伴随着面对面的测试而使其运转。

But the bottom line is that as a product organization, we need to get good at both forms of learning.

但是底线是,作为产品组织,我们需要两种形式更好的学习。

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