Salīdzināt metodes

	RFM Analysis	Customer Equity Modeling
Nozare	Mārketings	Mārketings
Saime	Process / pipeline	Process / pipeline
Izcelsmes gads	2006	2004
Autors	Arthur M. Hughes (popularizer); roots in direct-mail catalog marketing	Robert Blattberg & John Deighton; Roland Rust, Katherine Lemon & Valarie Zeithaml
Tips	Behavioral customer-segmentation and scoring pipeline	Strategic valuation and resource-allocation framework
Pirmavots	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	Rust, R. T., Lemon, K. N., & Zeithaml, V. A. (2004). Return on Marketing: Using Customer Equity to Focus Marketing Strategy. Journal of Marketing, 68(1), 109-127.
Citi nosaukumi	RFM Segmentation, Recency-Frequency-Monetary Analysis, RFM Scoring, RFM Model	Customer Equity Analysis, Return on Marketing Customer Equity, Customer Equity Test, Customer-Based Firm Valuation
Saistītās	4	4
Kopsavilkums	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.	Customer equity modeling treats a firm's customers as financial assets and defines the value of the firm's customer base as the sum of the discounted lifetime values of its current and future customers. The idea was crystallized by Robert Blattberg and John Deighton, who proposed managing marketing by the 'customer equity test,' asking of any initiative whether it will grow customer equity, and who showed how to balance spending between acquiring new customers and retaining existing ones. Roland Rust, Katherine Lemon and Valarie Zeithaml extended the framework into a strategic, driver-based model, decomposing customer equity into value equity (objective perceptions of quality, price and convenience), brand equity (subjective and emotional brand perceptions) and retention equity (the strength of the customer relationship and loyalty programs). Their 'Return on Marketing' approach links each marketing action through these drivers to brand-switching probabilities, to changes in lifetime value, and ultimately to the change in customer equity it produces, so competing strategies can be compared on projected financial return. Customer equity modeling thus connects customer-level analytics to firm-level valuation and budget allocation, providing a common currency for marketing decisions.