The impact of automation and optimization on customer experience: a consumer perspective

The paper addresses how digitization and automation reshape purchasing processes and affect consumer satisfaction. With the growing reliance on digital technologies, organizations face uncertainty but benefit from IT’s ability to improve information processing and market outcomes. Prior work links digital transformation to productivity and innovation and highlights marketing–IT integration, CRM, and automation (including RPA) as central to customer engagement. Despite increased research on digital transformation, there is limited empirical focus on how service automation promotes consumer wellbeing and engagement and how misapplied automation can harm experience and quality. The study aims to analyze, from the consumer perspective, the impact of automation technologies on purchasing processes and satisfaction, testing five hypotheses: H1: Digitization directly impacts consumer satisfaction during purchasing; H2: Automation is strategic for business activity; H3: Automating repetitive tasks enables more employee time for customer interaction; H4: Automating tasks in purchasing improves service quality via faster response time; H5: RPA improves consumer experience through self-service automation.

The theoretical framework describes digital transformation as rebuilding business models using emerging technologies, a major driver of change across industries. Automation can personalize services and enhance efficiency but introduces risks and the need for human oversight (the ‘ironies of automation’). Marketing’s linkage with IT underscores the importance of trust, security, and online experiences; customer interactions and online reviews inform adaptation. Technologies such as big data, analytics, machine learning, AI, and RPA support personalized service, cost reduction, speed, and error reduction across sectors (HR, banking, insurance, logistics, telecoms, retail). RPA is defined as software that replaces humans in GUI-based tasks, improving productivity and service quality while being limited by environmental requirements. Digitization alters firm–customer relationships, emphasizing satisfaction, loyalty, and CRM/CSR as strategic levers. Customer satisfaction—meeting expectations during the buying process—is critical for attraction and retention and is influenced by digitization and service quality. The review motivates examining how automation, especially RPA, within purchasing processes influences satisfaction and experience, leading to hypotheses H1–H5.

The study employs a quantitative empirical design using a Likert 5-point questionnaire to obtain measurable data and assess consumer perceptions. A four-step model was followed: (1) survey design linking consumer aspects, automation aspects, experience issues, and business perception to H1–H5; (2) survey collection; (3) data integrity and validation checks; and (4) insight analysis for business and consumer implications. Survey design and collection: The 30-item instrument (1 = totally disagree to 5 = totally agree) was adapted from validated sources (Jensen, 2007; Siderska, 2021; Zhang et al., 2022), incorporating items on digital exposure, efficiency and effectiveness of robots, and technology awareness. The questionnaire comprised four blocks: (I) consumer experience issues; (II) business perception; (III) consumer perceptions of automation of experience issues; and (IV) consumer perceptions of business automation aspects, as detailed in Table 1 (items A1–A15; B1–B15). Sample: A representative selected sample of 500 individuals was targeted (March 2023), yielding 215 valid responses from the Community of Madrid. Descriptives: 53.5% women; two unspecified gender; the 45–59 age group constituted 60.9%; 16 respondents were under 29. Analysis: Data were processed in SPSS. One-sample t-tests (test value = 3, "neither agree nor disagree") assessed whether item means differed from neutrality and, where significant, examined direction using the observed means. Descriptive statistics (means, SDs) were computed.

- N = 215. Overall, many items show high agreement with automation- and digitization-friendly statements. Examples of highest means include: A3 (importance of purchase confirmation email) mean = 4.6791; B14 (invest more in technology/tools for customer management) mean = 4.6698; B3 (confirmation email should contain exact details) mean = 4.6372; B2 (confirmation email should be sent ASAP) mean = 4.5674; B8 (customers should handle returns/incidents themselves) mean = 4.2977; B4 (automate basic tasks) mean = 4.1674; B12 (eliminating repetitive tasks increases productivity) mean = 4.1674; B11 (eliminating repetitive tasks allows more time per customer) mean = 4.0977; B6 (response time is a priority) mean = 4.1023; B9 (eliminating repetitive tasks enables serving more customers) mean = 4.0651; B15 (preference for quick/easy purchasing process) mean = 4.1302. - Non-significant or negatively oriented items: A1 (avoid shopping if confirmation must be manual) mean = 3.0605, p = 0.396 (not different from 3); A10 (more employees provide better service) mean = 3.1395, p = 0.063 (not different from 3); A4 (basic tasks best handled by an operator) mean = 2.6465, t = −4.538, p < 0.001; A12 (manual tasks prevent urgent problems) mean = 2.6093, t = −5.794, p < 0.001. - Hypothesis tests: Using item–hypothesis mappings (Table 4) and t-tests, the study reports: • H1 supported: digitization directly impacts consumer satisfaction in purchasing (linked items A1–A8; B1–B9 mostly with means > 3; exceptions A1 non-significant; A4 mean < 3). • H2 and H3 supported: consumers view automation as strategic and believe eliminating repetitive tasks frees employees to improve interaction (means > 3 across A9–A15; B9–B15, except A10 non-significant; A12 mean < 3). • H4 supported: automating purchasing tasks improves service quality via faster response (B1–B15 with means > 3 and significant t-tests). • H5 supported: RPA improves consumer experience through self-service management (B1–B15 with means > 3 and significant t-tests). - Overall, results indicate strong consumer support for automation that accelerates confirmations, reduces manual errors, improves response times, and enables self-service, while some basic tasks may still be preferred with human assistance.

Findings indicate that digitization and automation of organizational tasks positively influence consumer satisfaction during purchasing, aligning with prior work on digitization’s impact on consumers. Appropriate selection and design of automation are crucial, as automation can significantly alter human work and coordination requirements. Automating suitable purchasing tasks can reduce processing times, improve response speed, and enhance self-service, making automation a strategic lever. Consistent with the literature, eliminating repetitive, labor-intensive tasks frees employees to focus on higher-value human-to-human interactions, improving perceived service quality and experience. RPA can automate supplier relations and payment processes, helping optimize response times; yet, results suggest some basic tasks (e.g., changing delivery data, payment) may still benefit from human handling, indicating the need for hybrid approaches that preserve a human touch where valued by customers. Overall, aligning automation initiatives with consumer expectations and communicating effectively about changes supports engagement and satisfaction.

The study demonstrates a direct, positive link between organizational digitization/automation of tasks and consumer satisfaction in purchasing processes. Optimizing tasks improves expectations and can drive loyalty, engagement, and business outcomes; with effective implementation and change management, organizations can strengthen market positioning. A novel contribution is foregrounding RPA as a key, yet still underutilized, digital technology affecting consumer experience. Theoretical implications emphasize incorporating user perceptions into strategy and integrating RPA thoughtfully to ensure effectiveness and efficiency. Future research directions include: examining how organizations implement and adapt automation to optimize time and outcomes; analyzing impacts of task automation on additional organizational areas beyond purchasing and user relationships; exploring organizational variables (culture, technological readiness, financial resources) that shape adoption and outcomes; comparing RPA’s impact with other technologies; and extending studies to new geographies for cross-cultural analyses that account for varying digitization levels and macroeconomic indicators.

The paper underscores the need for further research to understand how organizations can effectively and efficiently manage digital transformation and automation to optimize time and outcomes. It highlights that the current assessment focuses on purchasing and user relationships, suggesting future work should analyze the impact of task automation on other organizational areas and extend the scope to additional types of organizations and professionals that could benefit from RPA. The authors also call for extending research to other territories to enable cross-cultural comparisons. These factors indicate that broader contexts, organizational settings, and geographies should be explored to assess generalizability and implementation nuances.