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  3. What happens when you combine product design skills, high-powered market research techniques, and abundant customer data? Too of

What happens when you combine product design skills, high-powered market research techniques, and abundant customer data? Too of

admin2022-07-26  140
问题     What happens when you combine product design skills, high-powered market research techniques, and abundant customer data? Too often, the result is devices that suffer from "feature creep" or the return of billions of dollars’ worth of merchandise by customers who wanted something different after all That kind of waste is bad enough in normal times, but in a downturn it can take a fearsome toll.
    The trouble is that most customer-preference rating tools used in product development today are blunt instruments, primarily because consumers have a hard time articulating their real desires. Asked to rate a long list of product attributes on a scale of 1 ("completely unimportant") to 10 ("extremely important"), customers are apt to say they want many or even most of them. To solve that problem, companies need a way to help customers sharpen the distinction between "nice to have" and "gotta have."
    Some companies are beginning to pierce the fog using a research technique called "Max Diff" (Maximum Difference Scaling), which was pioneered in the 1990s. It requires customers to make a sequence of explicit trade-offs. Researchers begin by amassing a list of product or brand attributes that represent potential benefits. Then they present respondents with sets of four or so attributes at a time, asking them to select which attribute of each set they prefer most and least. Subsequent rounds of mixed groupings enable the researchers to identify the standing of each attribute relative to all the others by the number of times customers select it as their most or least important consideration.
    A popular restaurant chain recently used Max Diff to understand why its expansion efforts were failing. In a series of focus groups and preference surveys, consumers agreed about what they wanted: more healthful meal options and updated decoration. But when the chain’s heavily promoted new menu was rolled out, the marketing team was dismayed by the results. Customers found the complex new choices confusing, and sales were sluggish in the more contemporary new outlets. The company’s marketers decided to cast the range of preferences more broadly. Using Max Diff, they asked customers to compare eight attributes and came to a striking realization. The results showed that prompt service of hot meals and a convenient location were far more important to customers than healthful items and modern furnishings.
    The ability to predict how customers will behave can be extremely powerful. Companies planning cross-border product rollouts need a tool that is free of cultural bias. And as customer tastes fragment, product development teams need reliable techniques for drawing bright lines between customer segments based on the features that matter most to each group. Companies are starting to apply Max Diff analysis to those issues as well.
Most customer-preference rating tools are
选项 A、accurate because of the numerical rating scale.
B、effective in distinguishing customer needs.
C、too blunt to measure customers’ real desires.
D、difficult to manipulate in actual measurement.
答案C
解析 根据题干中的customer-preference rating tools定位到第二段首句。该句表示客户偏好评价工具是较为迟钝的工具(blunt instruments)，其从句部分则表示主要原因是顾客很难确切表达他们的真正需求，意即该工具在测量顾客的真正需求方面还比较迟钝，C项符合文意，为本题答案。A项说的数字评估出现在第二段第二句，该句表示顾客被要求给一长列产品属性打分，可是顾客往往会说很多属性他们都需要，这样一来得到的结果就很模糊宽泛，而非精确，A项中的accurate与原文不符合。第二段第三句提到，企业需要找到一个帮助客户更清晰区分“不错”和“必不可少”的方法，意即“客户偏好评估工具在有效区分客户需求的方面还不够”，排除B项。D项说在真实考量中难以操作，文中并未有相关内容表述，故排除。
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