# Data-Driven Decision Support in SaaS Cloud-Based Service Models
###### Abstract  
Software as a service (SaaS) is a major service model for delivering software to end users through the cloud. SaaS platforms provide their users with cost-efficient, flexible and scalable services that can be available on demand, anytime, and anywhere. Moreover, SaaS empowers software providers to establish recurring revenue and create profitable businesses. However, SaaS can endure high customer turnover due to reasons such as serving a wide range of customers, intense competition and rapid evolution of technology. Maintaining a regular customer base and keeping users engaged is crucial for the survival of a SaaS business. Thus, it is crucial for SaaS providers to identify both the reasons behind users' engagement and churn of their app towards taking proper actions to retain them in the long term. SaaS data regarding user behavior, subscriptions and system performance can be utilized for deriving insights and identifying patterns to support decision-making for SaaS providers. To this end, the aim of this survey is to review research in data-driven decision support systems in SaaS, identifying current gaps and challenges and highlighting directions for future improvements towards the development of more efficient and intelligent systems. software as a service; churn prediction; user engagement; machine learning; usage mining +
Footnote †: journal: Applied sciences  
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enables software distribution without the need for installation and hardware setup [4]. Thus, users can use them easily and quickly, while generally paying by subscription instead of a large amount upfront. The SaaS model enables software providers to create profitable businesses allowing software distribution through the cloud to many users, simultaneously [5]. Moreover, the subscription-based business model provides opportunities for stable income streams. Thus, the success of a SaaS model as a business heavily depends on whether it maintains a core user base. When users experience meaningful benefits from a software solution, they use it regularly and for a long time. Engaged users are the superpower of SaaS since they tend to use it in the long term and with minimum support, while they could possibly suggest it to other users. The cost of obtaining new users is generally much higher than retaining the ones that already exist [6]. Thus, SaaS businesses strive to increase user engagement and reduce user churn, i.e., the percentage of users that cancel their subscriptions. Recent industry reports point to several growing challenges that make strong, data-driven decision support systems more important than ever for SaaS companies. One major issue is the high rate of customer churn, shortly after customers sign up, which is commonly observed with new artificial intelligence (AI)-powered tools ([[https://www.paddle.com/blog/saas-market-report-q1-2025](https://www.paddle.com/blog/saas-market-report-q1-2025)]([https://www.paddle.com/blog/saas-market-report-q1-2025](https://www.paddle.com/blog/saas-market-report-q1-2025)), assessed on 1 June 2025). This is particularly a problem in the B2C market, where user behavior changes quickly and is hard to predict. At the same time, many SaaS businesses do not pay enough attention to how they adjust their prices, even though pricing can have a big impact on user retention ([[https://www.omnius.so/blog/saas-industry-report-2024](https://www.omnius.so/blog/saas-industry-report-2024)]([https://www.omnius.so/blog/saas-industry-report-2024](https://www.omnius.so/blog/saas-industry-report-2024)), assessed on 1 June 2025). Another challenge is the rise of multi-cloud and hybrid systems, where companies run their software across several cloud platforms.