Conversational commerce has evolved from a niche concept to a central pillar of digital retail, redefining how brands engage, convert, and retain customers in Asia’s increasingly mobile-first markets. Enabled by advancements in generative AI and the growing use of messaging platforms like WhatsApp, LINE, and Messenger, today’s conversational journeys go beyond reactive support—they offer personalised, proactive, and frictionless brand experiences.
Driving this shift is Omnichat, a Hong Kong-based customer engagement platform that has integrated agentic AI into its tools to support end-to-end commerce processes. Its technology facilitates in-chat shopping, real-time campaign management, and more personalised customer interactions across messaging channels.
In this edition of What’s NEXT in Marketing Interview Series, we spoke with Alan Chan, founder and CEO of Omnichat, about the future of conversational commerce, the role of AI agents in redefining customer experience, and why Asia provides a unique environment for this transformation.
The growing role of conversational commerce in shaping digital retail
For Alan, conversational commerce is not just another engagement tactic—it’s becoming fundamental to how e-commerce operates in Asia today.
“Conversational Commerce is the strategic integration of messaging and chat technologies across the entire customer journey – from discovery and consideration to purchase and post-sale support. Its aim is to create a more personal, interactive, and seamless shopping experience that ultimately drives sales and builds loyalty,” he explains.
He notes that in mobile-first regions like Asia, messaging apps function as more than just communication tools—they’re digital storefronts.
“In Hong Kong, for instance, WhatsApp has an impressive 79% penetration rate, and message open rates can be as high as 98%, significantly outperforming traditional channels like email.”
While the pandemic accelerated the shift to online retail, Alan points out that the demand for genuine, human-like interaction hasn’t diminished—it has intensified. Today’s consumers expect responsive, real-time service that mirrors the feel of an in-store experience.
“Consumers in Asia’s fast-moving markets increasingly expect to not just browse, but to engage, ask questions, and receive tailored advice in real-time, much like a personalised in-store experience, but with digital convenience,” he adds. “This makes conversational commerce not just a trend, but a fundamental component of a successful digital retail strategy in the region.”
A generational leap in engagement
Alan traces the evolution of conversational AI from basic rule-based systems to the powerful generative models we see today.
“Conversational AI began with rule-based chatbots, which operated on pre-defined scripts and keyword matching. Their primary role was foundational – automating basic FAQ responses and routing enquiries,” he elaborates. “Today, we’re in the era of Generative AI, allowing AI to understand context far more deeply, generate remarkably human-like, nuanced responses, and even create original content, marking a quantum leap from earlier iterations.”
He highlights the emergence of AI agents as the most transformative shift—intelligent systems capable of handling not only support but also marketing, sales, and more.
“With generative AI, we can deploy multiple AI agents to handle far more complex queries, understand sentiment, troubleshoot dynamically, and offer solutions that aren’t explicitly programmed. These AI Agents extend their capabilities into marketing and sales, and other vital aspects of the business, delivering holistic, proactive, and deeply personalised engagement across the entire customer lifecycle,” Alan shares.
AI agents for full-funnel impact
In response to the rise of generative AI, Alan noted that Omnichat aims to play a leading role in how the technology is applied in commerce. As part of this effort, the company launched Omni-AI, a conversational AI suite that supports customer engagement across every stage of the journey.
“We have developed ‘Omni-AI’, our conversational AI suite of powerful AI agents designed to streamline customer service, marketing, and sales, and provide smarter, faster, and more fluid AI-automated workflows for effortless conversational commerce and superior customer experiences,” Alan said.
Omnichat’s features include AI-generated responses, product recommendations, and smart suggestions for live agents—all driven by contextual data like chat history and purchase behaviour.
A major development is the Omni AI Agent Studio, which lets companies build custom AI agents using LLMs from OpenAI, Google, Meta, Anthropic, Deepseek, and AWS.
“The core innovation of the Omni AI Agent Studio is its empowerment of companies to build bespoke AI agents… This open-ecosystem approach ensures our clients can always use the best-in-class technology for their specific needs,” he adds.
Alan also stresses that AI should enhance, not replace, human interaction.
“Our platform ensures seamless handoffs between AI agents and human staff, providing full context so the customer experience remains smooth and supportive,” he remarked.
He further explains how Omnichat’s AI covers the full journey with four specialised agents: the AI Customer Service Agent for around-the-clock support; the AI Marketing Campaign Agent for targeting, content creation, and automation; the AI Shopping Agent for personalised product assistance; and the AI Customer Loyalty Agent to manage rewards and retention.
“By deploying this suite of interconnected AI agents, Omnichat empowers businesses to proactively engage customers with task-specific assistance that not only elevates their experience but also drives measurable results in sales, workflow efficiency, and the delivery of truly personalised offers at scale,” Alan explains.
The new customer journey, inside a chat
Running conversational AI across platforms like WhatsApp, LINE, and Messenger requires more than just translation—it needs continuity and local context. Omnichat supports this with a shared memory architecture and a role-based agent system.
“Our multi-agent RAG system is tailored for different roles (e.g., customer support, product recommendation) while sharing a unified context layer to create a cohesive experience,” he shares.
Features like dynamic language detection, localised knowledge bases, and real-time feedback loops help agents adjust for each market while meeting compliance standards.
“This holistic approach delivers seamless, multi-turn, multi-language interactions that feel natural and relevant, ultimately driving conversions and customer satisfaction,” he adds.
Alan walks through what an AI-powered journey looks like in practice: the chat begins with proactive engagement on the website, followed by personalised support and product recommendations via messaging apps. If the customer isn’t ready to buy, the AI Marketing Campaign Agent steps in to nurture the lead.
Each handoff between agents takes into account the customer’s real-time behaviour and interaction history. This supports actions such as sending purchase links, testing campaign content, or initiating loyalty-related workflows in a timely and context-aware manner.
“By leveraging AI at each of these stages, Omnichat transforms the customer acquisition journey into a more intelligent, efficient, and personalised process. This significantly improves lead quality and conversion rates, all directly within the chat interfaces customers prefer and trust,” Alan said.
Human-AI synergy for service with empathy
As conversational AI becomes more embedded in commerce, its ability to deliver not just fast responses but empathetic, human-like service is increasingly under scrutiny. Today’s consumers expect more than robotic efficiency—they want personalised, thoughtful support that understands their needs in context.
Alan explains that this balance between automation and empathy is critical to Omnichat’s approach. One example is their own AI Sales Agent, which plays a key role in identifying customer intent and removing friction from the purchase journey
“Our AI Sales Agent actively discovers customer needs by meticulously analysing ongoing conversations, chat history, and integrating vital data points such as browsing behaviour and the customer’s unified profile,” he elaborates.
To make purchasing easier, the AI can send dynamic checkout links or integrate with WhatsApp Catalog, streamlining the process from discovery to conversion.
Maintaining empathy, however, remains a priority.
“Firstly, with Customised Tonality, our Omni-AI can be trained to generate responses that meticulously align with a brand’s specific voice and style… Secondly, through Contextual Understanding, our AI doesn’t treat each query in isolation… This then enables Personalised Resolution Paths…”
When escalation is needed, the platform ensures that human agents receive the full conversation history and customer profile, allowing for a smooth, informed transition.
“Our platform equips live agents with all the necessary context from the AI’s interaction—including the full conversation history and customer profile—enabling them to resolve issues effectively and empathetically without requiring the customer to repeat themselves,” he adds.
Shaping the future of AI-led commerce
Looking ahead, Alan sees conversational AI becoming a driving force in customer journeys—not just a supporting tool.
“We are continuously enhancing their autonomy and intelligence… By enabling our AI to analyse this rich, omnichannel data… we’re empowering it to more accurately predict customer intent, anticipate future needs, and identify optimal engagement points,” he shares.
At the core of this evolution is Social CDP, Omnichat’s unified customer data platform that enables predictive and personalised AI interactions at scale.
“Conversational AI will become a central, intelligent force. It will proactively shape and drive every stage of the customer journey, from initial discovery and acquisition through to lasting loyalty and advocacy,” Alan concludes.
