Hong Kong Calculators

Customer Effort Score (CES) Calculator

From the sum of response scores and the number of responses, compute the average Customer Effort Score (CES).

輸入資料

Total of all respondents' scores.
Number of valid responses.

計算結果

Sum / number of responses.
5.6

重點速覽:CES = sum of response scores / number of responses (arithmetic mean). It measures the average effort customers exerted to complete a task (resolve an issue, buy, get service). Core idea: reducing customer friction retains loyalty better than delighting them. WARNING: Interpretation depends on your scale direction (higher=easier vs lower=easier) and range (1-5/1-7/1-10); this tool only averages. Education, not advice.

計算公式

客戶費力度分數 CES = 所有回應分數總和 ÷ 回應數。

$$\text{CES} = \dfrac{\sum \text{Response Scores}}{\text{Number of Responses}}$$

使用說明

  1. Sum all respondents' scores into 'Sum of scores'.
  2. Enter the number of valid responses.
  3. View the average CES.

客戶費力度分數 (CES) 計算範例

客戶費力度分數 (CES) 計算範例
情境分數總和回應數CES 平均分
基準560100 份5.60
體驗改善600100 份6.00
回應數較少56080 份7.00

CES = 分數總和 ÷ 回應數 (算術平均)。解讀時須先確認量表方向 (分高越省力 vs 分低越省力) 與範圍 (1-5 / 1-7 / 1-10)。

理財情境案例

案例一:計算客戶費力度分數

某公司在客戶完成客服互動後發出問卷 (量表 1–7 分,分數越高代表越輕鬆省力),收回 100 份有效回應,分數加總為 560。

套用公式:CES = 分數總和 ÷ 回應數 = 560 ÷ 100 = 5.6。

在『分高越省力』的 1–7 量表下,5.6 屬中上,代表多數客戶覺得處理這件事相對輕鬆。但要準確判讀,必須先確認量表方向與範圍 — 若量表是『分低越省力』,同樣的 5.6 就代表偏費力,意義剛好相反。本計算器只做平均,方向由使用者對照自身問卷解讀。

案例二:CES 與 NPS、CSAT 的分工,及平均值的盲點

CES、NPS、CSAT 三個客戶體驗指標側重不同:CSAT 問『你滿意嗎』(即時滿意),NPS 問『你會推薦嗎』(長期忠誠關係),CES 問『這件事讓你費力嗎』(交易/互動的摩擦)。CES 特別適合在客服、退換貨、註冊等流程後即時評估,找出令客戶費力的痛點。

承案例一,若改善流程後分數總和升到 600、回應仍 100 份,CES = 600 ÷ 100 = 6.0,代表費力度下降 (在分高越省力的量表下體驗變好)。

但要警惕平均值的盲點:CES 5.6 可能來自『大家都給中間分』,也可能來自『一半人給高分、一半給低分』的兩極分化 — 兩者平均相同但意義天差地別。因此除了看平均,務必檢視分數分布,尤其關注給出『高費力』評價的客戶,他們是最容易流失的一群。此外,樣本量要足夠、要看趨勢而非單點、並結合開放式回饋找出『為何費力』。本站另有『客戶留存率計算器』與『淨推薦值 (NPS) 計算器』可搭配追蹤客戶體驗。

常見問題

How is CES calculated?

It is simply the mean of all respondents' scores: sum every score, then divide by the number of responses. With 100 responses summing to 560, CES = 5.6. This 5.6 is the average rating of 'how easy/hard it was'. Two things to fix first: the scale range (1-5/1-7/1-10) to judge if 5.6 is high or low, and the scale direction (higher=easier vs lower=easier). This tool only averages; you interpret the direction.

Why use CES, and how is it different from NPS and CSAT?

CES measures effort (friction); NPS measures recommendation intent (long-term loyalty); CSAT measures satisfaction (momentary). Research suggests lowering effort reduces churn more effectively than over-delighting. They are complementary: CES finds friction points, CSAT reflects momentary satisfaction, NPS reflects long-term loyalty.

What should I watch when using and interpreting CES?

Five points: (1) confirm scale direction and range; (2) ensure sufficient sample size; (3) remember the mean hides the distribution — also look at how many gave 'high-effort' scores (they are the churn risk); (4) track trends over time, not single points; (5) pair with open-ended feedback to learn 'why'. This tool gives the average CES; effective improvement needs all of these.

Is a higher CES better or worse?

It depends entirely on your scale design — there is no universal 'good direction'. One common design asks a positive statement (e.g. 'the company made it easy'), so higher = easier = better. The reverse design asks effort directly (1=very little, 7=very much), so higher = more effort = worse. Confirm your scale before judging 5.6 as good or bad, and note the range (1-5/1-7/1-10).

How does CES differ from NPS and CSAT, and which to use?

In one line: CSAT asks 'satisfied?', NPS asks 'would you recommend?', CES asks 'was this effortful?'. CSAT = momentary satisfaction (transaction-level); NPS = recommendation/loyalty (relationship-level, long-term); CES = friction in completing a task (transaction-level, diagnostic). Which to use depends on the question: to find and fix process friction → CES; to gauge momentary satisfaction → CSAT; to track long-term loyalty/word-of-mouth → NPS. They are complementary, not mutually exclusive — many firms track all three.

相關工具

參考資料

內容審核:香港計算器財經團隊。計算邏輯與公式參考香港金融管理局(HKMA)及投資者及理財教育委員會(IFEC)之個人理財計算指引,結果僅供參考,實際以相關機構公佈為準。

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