方法对比

	Customer Journey Analysis	RFM Analysis
领域	市场营销	市场营销
方法族	Process / pipeline	Process / pipeline
起源年份	2016	2006
提出者	Katherine N. Lemon & Peter C. Verhoef	Arthur M. Hughes (popularizer); roots in direct-mail catalog marketing
类型	Customer-experience mapping and measurement pipeline	Behavioral customer-segmentation and scoring pipeline
开创性文献	Lemon, K. N., & Verhoef, P. C. (2016). Understanding Customer Experience Throughout the Customer Journey. Journal of Marketing, 80(6), 69-96.	Hughes, A. M. (2006). Strategic Database Marketing: The Masterplan for Starting and Managing a Profitable, Customer-Based Marketing Program (3rd ed.). McGraw-Hill. ISBN: 9780071457507
别名	Customer Journey Mapping, Customer Experience Journey Analysis, Touchpoint Analysis, Journey Analytics	RFM Segmentation, Recency-Frequency-Monetary Analysis, RFM Scoring, RFM Model
相关	4	4
摘要	Customer journey analysis is the systematic mapping and measurement of the full sequence of touchpoints a customer experiences with a firm, across the prepurchase, purchase and postpurchase stages, in order to understand and improve the end-to-end customer experience. It reflects a shift from evaluating isolated interactions or single satisfaction scores toward seeing the customer experience as a dynamic, cumulative, multi-touchpoint process that unfolds over time and recurs in loops. Katherine Lemon and Peter Verhoef's influential 2016 Journal of Marketing synthesis provided the field's organizing framework, defining customer experience as a customer's cognitive, emotional, sensory, social and behavioral responses across the journey, and classifying touchpoints as brand-owned, partner-owned, customer-owned and social or external. The analysis inventories these touchpoints stage by stage, measures the experience at each, traces the paths customers actually take through them, and identifies the moments and pain points that most shape outcomes such as conversion, satisfaction and loyalty. The result is a diagnostic that connects specific interactions to overall experience and guides where to invest in redesign, integrating behavioral analytics with qualitative experience research.	RFM analysis is a long-standing, behavior-based method for scoring and segmenting customers by how recently they purchased (Recency), how often they purchase (Frequency), and how much they spend (Monetary value). Rooted in catalog and direct-mail marketing and popularized in Arthur Hughes's Strategic Database Marketing, it rests on the empirical observation that customers who bought recently, buy frequently, and spend more are the most likely to respond to the next offer. The classic procedure ranks customers into quintiles on each of the three dimensions, assigns each a score from 1 to 5, and combines the scores into cells, typically a 5x5x5 grid of 125 segments. Campaign managers then measure historical response rates per cell, compare them to a break-even threshold derived from contact cost and order margin, and target only the cells that are profitable to contact. Despite its simplicity, RFM is remarkably effective and cheap to run, requiring only transaction history. It remains a workhorse for segmentation and a natural precursor to model-based customer-base analysis and lifetime-value estimation.