INTERNATIONAL JOURNAL OF RESEARCH AND INNOVATION IN SOCIAL SCIENCE (IJRISS)
ISSN No. 2454-6186 | DOI: 10.47772/IJRISS | Volume IX Issue XI November 2025
Customer Profitability and Digitalization in the B2B Market:
Systematic Literature Review
Annisa Nur Hanifah*., Aristanti Widyaningsih., Denny Andriana
Master of Accounting, Universitas Pendidikan Indonesia
Received: 10 November 2025; Accepted: 20 November 2025; Published: 06 December 2025
ABSTRAK
This study presents a Systematic Literature Review (SLR) to synthesise and analyse the roles, contributions,
challenges, and gaps in the literature at the intersection of Customer Profitability Analysis (CPA), digitalisation,
and the Business-to-Business (B2B) market. Using an SLR approach, this study identifies and evaluates 30
scholarly articles that focus on CPA in B2B markets within the context of digitalization. The analysis is
conducted thematically to identify models, non-risk challenges, and integration gaps. Digitalization has
transformed B2B CPA from a purely historical, backward-looking model into a predictive, risk-adjusted
approach. The use of Machine Learning (ML) and data mining techniques (such as Boosting and Random Forest)
has proven accurate in estimating customer churn probabilities and risk levels, which are then integrated into
Customer Lifetime Value (CLV) calculations based on Risk-Adjusted Revenue (RAR). The main non-risk
challenges include failures in integrating legacy systems (ERP, CRM, SCM), which hinder accurate tracing of
cost-to-serve, as well as the need for managerial cultural change and the adoption of new hybrid technology
roles.The key gap in the literature is the lack of empirical and technical studies that explicitly explain how digital
technology platforms (hybrid actors such as chatbots or e-marketplaces) automatically capture and allocate
service costs to B2B customer accounts within traditional cost accounting models, particularly Activity-Based
Costing (ABC).
Keywords: Customer Profitability Analysis, Digitalization, B2B Market
INTRODUCTION
Digital transformation has radically changed the business landscape, especially within the Business-to-Business
(B2B) market concept. In general, B2B companies are currently facing increasing pressure to optimize their
customer relationships in response to market volatility and global competition. Data from Anan (2023) indicates
that companies with superior customer analytics capabilities (which are often driven by digitalization) can
achieve a profitability increase of up to 15–20% compared to their competitors. This phenomenon highlights the
importance of Customer ProfitabilityAnalysis (CPA) with an approach that goes beyond total revenue to measure
the costs and profitability associated with each individual customer as a key to efficient resource allocation and
strategic decision-making in a digital environment.
However, the implementation of CPA in the B2B context faces unique challenges compounded by digitalization.
The B2B market is characterized by a smaller number of customers, higher transaction values, and complex,
long-term relationships (Purmonen et al., 2023). The main challenge is the complexity in measuring
differentiated Cost-to-Serve in the digital era. Digital infrastructure generates massive volumes of data (Big
Data) from various touchpoints—ranging from e-procurement platforms, automated Customer Relationship
Management (CRM), to digital technical support services (Voorhees et al., 2025). The core problem that arises
is how to accurately integrate, process, and model this large and varied volume of data to calculate B2B customer
profitability in real-time or near real-time.
Several previous studies have examined CPA, focusing on traditional frameworks such as Activity-Based
Costing (ABC) or Customer Lifetime Value (CLV) models. For example, Lau et al. (2016) reviewed the
integration of ABC in CPA measurement, while Ruch & Sackmann (2012) explored the role of CLV in B2C.
Page 2963
