How is tech enhancing e-commerce experience through customer service excellence
By Anton Tomchenko, Chief Revenue & Solutions Officer – Digital & Software, Hexaware
We are currently at the point where competitive advantage comes from the ability to capture, analyse, and utilise personalised customer data at scale. Digital advantage has gone beyond the boundaries of traditional marketing and has become a broader C-suite issue. This is changing the foundation of the customer service world and putting the customers’ needs at the centre of an organisation’s goals. With increasing market competition and consumers seeking quicker, more personalised services, e-commerce companies are now using advanced technology to fulfil and surpass those requirements. Recently, we have seen artificial intelligence (AI) and machine learning (ML) enter the mainstream. While we are still in the early years of this technology’s development and deployment, AI adoption is rapidly expanding, with more companies integrating it into their workflows.
AI and Machine Learning for e-commerce customer service
One of the most common use cases of AI in e-commerce is deploying automated, customer-facing chatbots. AI-driven chatbots and virtual assistants have come a long way from the simplistic and almost scripted responses of yore. Today, AI and ML-powered chatbots can engage in naturalistic, human-like dialogues. These bots have become real-time assistants that can handle deep queries and act 24/7, a key feature in a constantly evolving market where consumer expectation is an instant reply.
Generative AI, for instance, has emerged as an advanced alternative to conventional personalisation approaches as it produces content and solutions on the fly that can ideally respond to the needs and behaviours of individual customers. Today, retail firms are using this technology to create personalised responses to customer queries and process large datasets at high accuracy, predict customer preferences and behaviours, and further their customer relationships with a high degree of customisation. This would not be feasible using traditional methods.
AI in omnichannel strategies
Take the example of how social media changed the dynamics of customer service by focusing on real-time interaction. Today, platforms such as X and Instagram are not just marketing channels but form the core of a company’s customer service plan. Similarly, with the high proliferation of AI, there has been a shift from customer service to customer experience.
Modern consumers expect a seamless and frictionless experience across multiple touchpoints when interacting with brands, be it through mobile apps, social media, or even chatbots on the website. This is where AI and ML can offer an edge. Incorporating AI enables new operating models that are more efficient and ensures a higher level of service that leads directly to a higher degree of customer satisfaction, retention, and revenues.
Another advantage of having AI at the centre of a company’s omnichannel customer service strategy is its ability to learn and evolve. In contrast to static systems, AI platforms dynamically process interactions, detect patterns, and adapt their behaviour. That is to say, a company’s omnichannel approach becomes smarter with every customer touchpoint. The AI can learn what answers are most effective, what channels customers use for a particular query type, and even foresee potential problems ahead of the fact. For instance, if an AI system detects an upward trend in support tickets for a specific product feature, it can instantly alert the support team, ask for more information on what to do with these questions, and even advise on how the process or product should be improved. This type of adaptive intelligence differentiates good from great omnichannel experiences.
Future of AI in e-commerce customer service
Soon, e-commerce platforms will continue to leverage their AI capabilities to meet hyper-personalisation. When a shopper enters an online store, AI will start curating a shopping experience uniquely tailored to that individual’s preferences.
At the core of this AI-driven hyper-personalisation are data analytics, advanced algorithms, and ML learning models that dynamically change with evolving shopper needs. Next-generation search platforms will use these tools to ensure each customer query and product recommendation is aligned with the customer’s interests.
Data shows that approximately 40% of customers switch brands because of poor customer service. This has driven companies to precisely characterise their customer service response time and responses. Also, enhanced predictive analytics will help on the operational side, such as inventory and demand forecasting, and create a more seamless customer experience by reducing out-of-stock and shipping delay problems. AI in these platforms will enable real-time learning, allowing e-commerce firms to continuously improve the accuracy and relevance of responses based on ongoing user interactions.
The rapid advancement of technology in customer service has revolutionised how e-commerce platforms operate, enhancing everything from chat interactions to data analysis and customer recommendations. The result is a continuous improvement cycle that feeds back into customer satisfaction and loyalty. By combining AI, predictive analytics, and omnichannel support, companies are not just staying competitive but establishing a new standard for exceptional customer service. In the competitive domain of e-commerce, offering a cutting-edge customer experience is no longer an option — it is a necessity for growth and survival.
