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【NPS】净推荐值---学习笔记 #BV# 若视频不清晰您也可以跳转到原链接：【NPS】净推荐值讲解与计算_哔哩哔哩_bilibili 来源 NPS(Net Promoter Score)，该概念由贝恩咨询公司的Fred Reichheld于2003年在《哈佛商业评论》文章《The One Number You Need to Grow》The One Number You Need to Grow中首次提出，旨在衡量客户忠诚度。 Reichheld F F. The One Number You Need to Grow[J]. Harvard business review, 2003, 81(12): 46-55. 含义 问题设置 “The top-ranking question was far and away the most effective across industries: •How likely is it that you would recommend [company X] to a friend or colleague? Two questions were effective predictors in certain industries: • How strongly do you agree that [company X] deserves your loyalty? • How likely is it that you will continue to purchase products/services from[company X]? Other questions, while useful in a particular industry, had little general applicability: • How strongly do you agree that [company X] sets the standard for excellence in its industry? • How strongly do you agree that [company X] makes it easy for you to do business with it? • If you were selecting a similar provider for the first time, how likely is it that you would you choose [company X]? • How strongly do you agree that [company X] creates innovative solutions that make your life easier? • How satisfied are you with [company X’s] overall performance?” (Reichheld, 2003, p. 5) 排名最高的那个问题在各行业中都非常有效，遥遥领先： • 您有多大可能向朋友或同事推荐[公司X]？ 以下两个问题在某些行业中是有效的预测指标： • 您有多大程度同意[公司X]值得您忠诚？ • 您有多大可能继续购买[公司X]的产品/服务？ 其他问题虽然在特定行业中有用，但通用性较差： • 您有多大程度同意[公司X]为其行业树立了卓越标准？ • 您有多大程度同意[公司X]让您与之开展业务非常容易？ • 如果您是第一次选择类似的供应商，您有多大可能选择[公司X]？ • 您有多大程度同意[公司X]创造了让您的生活更轻松的创新解决方案？ • 您对[公司X]的整体表现有多满意？ 客户分级依据 “For these reasons, we settled on a scale where ten means “extremely likely” to recommend, five means neutral, and zero means “not at all likely.” When we examined customer referral and repurchase behaviors along this scale, we found three logical clusters. “Promoters,” the customers with the highest rates of repurchase and referral, gave ratings of nine or ten to the question. The “passively satisfied” logged a seven or an eight, and “detractors” scored from zero to six.” (Reichheld, 2003, p. 6) 出于这些原因，我们最终确定了一个量表，其中十分表示“极有可能”推荐，五分表示中立，零分表示“完全不可能”推荐。当我们沿着这个量表考察客户的推荐和复购行为时，我们发现了三个逻辑集群。 “推荐者”是复购率和推荐率最高的客户，他们对该问题的评分是九分或十分。“被动满意者”的评分是七分或八分，“贬损者”的评分是零分到六分。 ![[Pasted image 20250119103405.png]] 计算方法 “Calculate: the percentage of customers who respond with nine or ten (promoters) and the percentage who respond with zero through six (detractors). Subtract the percentage of detractors from the percentage of promoters to arrive at your net-promoter score.” (Reichheld, 2003, p. 8) 计算回答九分或十分的顾客（推荐者）的百分比，以及回答零分到六分的顾客（贬损者）的百分比。从推荐者的百分比中减去贬损者的百分比，得出您的净推荐值。 $$ \text{NPS} = \frac{\text{推荐者数} - \text{贬损者数}}{\text{总客户数}} \times 100 $$ 演示 问卷调查 很多问卷平台都有NPS选项 后面通常可以接一个原因类型问题，以便进行更详细的解释 如：您不推荐xx的原因是？ Excel计算 公式计算 假设A2到A101列为数据列，标出推荐者、被动者、贬损者 =IF(A2>=9, "推荐者", IF(A2>=7, "被动者", "贬损者")) 如果单元格 A2 的值大于或等于 9，则返回 "Promoter"（推广者），表示评分很高，推荐度高。 如果单元格 A2 的值大于或等于 7 且小于 9，则返回 "Passive"（被动者），表示评分中等，既不积极推荐也不反对。 如果单元格 A2 的值小于 7，则返回 "Detractor"（贬损者），表示评分较低，不推荐或反对推荐。 计算三种客户的数量 =COUNTIF(B2:B101, "推荐者") =COUNTIF(B3:B101, "被动者") =COUNTIF(B4:B101, "贬损者") 计算比例 =((COUNTIF(B2:B101, "推荐者") - COUNTIF(B2:B101, "贬损者")) / COUNTA(A2:A101)) * 100 $$ \text{NPS} = \left( \frac{\text{推荐者数}}{\text{总客户数}} - \frac{\text{贬损者数}}{\text{总客户数}} \right) \times 100 $$ $$ \text{NPS} = \frac{\text{推荐者数} - \text{贬损者数}}{\text{总客户数}} \times 100 $$
