Decomposition of and Insights Into Revenue Retention Rates
(A2025-126325)

AUTHORS

Thilo Kraft, Goethe University Frankfurt; BERND SKIERA, Goethe University Frankfurt, Germany

ABSTRACT

This paper introduces a novel cohort-based approach for decomposing Revenue Retention Rates (RRR), addressing the challenge of assessing customer value and revenue development using only publicly available data. Decomposing RRR enables the differentiation of customers' revenue contributions, providing benchmarking between competitive firms and insights into revenue developments. The proposed approach models retained revenue as a function of baseline retention, cohort, and age effects, providing flexible and widely applicable usage. A simulation study supports the validity of this approach. The application to 26 firms from four industries yields novel insights about customer value, revenue development, and significant differences in the effects between firms and industries. We further find that all analysed firms have decreasing revenue retention rates as cohorts mature, even though the age effect has the highest impact on revenue development among the analysed effects.