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

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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 "Maxdiff" (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 MaxDiff 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 MaxDiff, 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 MaxDiff analysis to those issues as well.
Compared with traditional preference rating tools, "Maxdiff" ____.
选项 A、involves more product attributes for options
B、is better at distinguishing customers’ needs
C、requires more customers to participate in
D、is a much more easier rating method
答案B
解析 由题干中标有双引号的Maxdiff一词可定位到第三段。该段介绍有别于偏好评估工具的另一种评估技术。上一段提到传统方法要求客户给一系列的属性打分，而新的方法是对其中代表潜在利益的属性进行选择，并通过选项混合分类的几轮选择，确定每个属性相对于其他属性的重要性名次，由此可知，这种方式避免了消费者在传统评估方式中认为大部分属性他们都需要从而给分不准确的情况，更有针对性且更能清晰地区分顾客的需求。所以答案为B项。
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