The Growth of Customer Service Infrastructure
E-commerce platforms increasingly rely on layered support systems to handle billions of interactions each year. From self-service portals, to AI chatbots, to live agent escalation, these systems aim to provide continuous assistance. At first glance, that seems efficient, but deeper evidence suggests that multiple tool chains, redundant layers, and unclear pathways create friction rather than helping. Customers often find themselves bouncing between a chatbot that cannot understand their request, a ticket form that asks again for details, and a knowledge base that does not apply to their situation.
The result is cognitive load. Users must recall context between channels, interpret instructions repeatedly, and manage confusion. Studies on digital fatigue indicate that when tools multiply and users must navigate complex systems, frustration and mental energy drain increase (Deloitte 2023).
Chatbots and Virtual Assistants: A Mixed Bag
Many e-commerce companies deploy chatbots or virtual assistants, hoping to reduce costs and wait times. However, research shows that success depends heavily on system quality, information quality, and service quality (Chou 2021).
A more recent study within the retail sector found that ease of problem understanding and resolution strongly influence whether customers will switch back to human agents, or abandon the channel altogether (Chen et al. 2025).
These findings underscore that automation without human-centred design can degrade the experience. When a chatbot misdirects a user to a lengthy ticket form, or irrelevant FAQ, the user ends up spending more time and effort than if they had reached a competent human agent quickly. That extra time is not only frustrating, but also inefficient from a resource perspective. More compute cycles and more backend service transfers accumulate over time (Lin et al. 2024).
The Sustainability Dimension: Beyond Environmental Metrics
When we talk about sustainability of customer service in e-commerce, we tend to focus on environmental footprints such as data centres and energy consumption. But a holistic view recognises social and human cognitive dimensions too.
From the social side, inefficient service systems contribute to user stress, exclusion of people with less digital literacy, and widespread dissatisfaction. From the cognitive side, increased switching costs, repeated data input, long waiting, and error recovery contribute to mental energy use. From the resource side, every escalation, rerouting, or repeated attempt to resolve a problem adds to energy consumption and emissions.
Inefficient support systems also increase operational costs and infrastructure load, which undermines economic sustainability.
Key Practices for More Sustainable Customer Service
Streamline channels
Provide a clear first contact pathway, and avoid sending users through multiple disconnected help layers.Design human centred chatbot flows
Use automation for simple tasks, but ensure quick, intuitive escalation to human agents when needed.Minimise cognitive load
Use plain language, reduce steps, avoid duplicated forms, and preserve context between channels.Measure interaction cost
Monitor hand offs, repeat contacts, search actions, and average time to resolution.Make knowledge bases truly useful
Keep FAQs up to date, remove irrelevant content, and offer structured navigation.Support inclusivity
Ensure that customer service is accessible to users with cognitive, physical, or linguistic challenges, and to those on slower connections or older devices.
These steps reduce friction and mental fatigue, while making support infrastructures leaner, more efficient, and more aligned with sustainability goals.
Conclusion
The sustainability of customer service on e-commerce platforms cannot be confined to energy consumption or automation scale. It must embrace clarity, inclusivity, cognitive well-being, and resource efficiency. Many firms believe that adding more chatbots, more articles, and more channels equals better service. The evidence suggests the opposite. Complexity breeds burden, redundant layers create waste, and poor UX drains both digital and human energy.
By simplifying support journeys, designing smart escalation flows, measuring real interaction cost, and prioritising people’s mental energy, we move toward truly sustainable customer service.
Sources
Chou, EY. (2021). Conversational service experiences in chatbots and cognitive load research insight.
https://www.management-review.org/en/insight/conversational-service-experiences-in-chatbotsChen, S. et al. (2025). Exploring how chatbot service quality shapes customer switching intentions in e-commerce. Nature Scientific Reports.
https://www.nature.com/articles/s41598-025-06490-zLin, X. et al. (2024). How AI powered customer service affects satisfaction and behaviour in online retail. Journal of Management Information Systems.
https://www.tandfonline.com/doi/full/10.1080/07421222.2024.2415773Deloitte (2023). Digital fatigue and the connected consumer.
https://www.deloitte.com/us/en/insights/industry/telecommunications/connectivity-mobile-trends-survey/2023/connected-consumers-digital-fatigue.html
