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 "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.
The restaurant chain fails in expansion for the lack of

选项 A、healthy options.
B、a modern decoration.
C、a convenient access.
D、new menus.

答案C

解析 根据The restaurant chain可定位到第四段。该段讲到一家餐饮店通过新的评估技术得出之前店面扩张失败的原因。该段第二句提到传统方法得出客户需要更健康的饮食选择和不断翻新的装潢,而末句使用新的评价方式得出的结果是及时的上菜服务和方便的位置更重要(were far more important),因此可知此餐饮连锁店扩张失败的原因就在于这两点。C项为其中一项内容,故为答案。第四段第二句提到了通过焦点小组和偏好调查所得出的客户主要需求,但第四句表明在装潢更现代化的新销售店,销售更低迷(sluggish in the more contemporary new outlets),由此可知,缺乏更现代化的装潢并非失败原因,故可排除B项。该段第三句提到了新菜单,指出推出新菜单后,结果却令人沮丧(dismayed),由此可知采取了相关措施却并未见成效,故A项和D项都不是扩张失败的原因,均可排除。
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