Retailers scale AI as customer journeys fragment
Real-time personalisation is pushing marketers to connect customer data across stores apps and marketplaces as leadership demands results beyond pilots.
Asia Pacific retailers are moving artificial intelligence from pilots into live marketing decisions as executives push for measurable results and customer journeys become harder to track across stores, apps and marketplaces.
Vanessa Matthijssen, Asia-Pacific Consumer Industry Lead at Deloitte, said at least half of regional retailers are already working with AI and agentic tools in marketing and sales. She said the shift is moving retailers away from static segmentation and predefined journeys towards real-time decision-making across channels.
“It's no longer about optimising channels. It's not about static segmentation anymore. No more predefined journeys,” Matthijssen said.
Sarah Richardson, CEO and Founder of Loyalty Group Asia-Pacific, said stronger technology integration and commercial pressure are accelerating adoption. “They're not interested in pilots anymore,” she said, adding that management teams increasingly expect staff to test and deploy AI in day-to-day operations.
Keeping pace with customers now requires a single view across channels. Richardson said retailers need to understand how shoppers move between digital and physical touchpoints, whilst Matthijssen said marketers are increasingly using autonomous segmentation and next-best-action tools to respond in real time.
Execution still breaks down when customer data is fragmented or when online and offline journeys fail to connect. Matthijssen said AI depends on accurate and unified data, as well as employee trust in automated recommendations.
Richardson identified the handover between channels as the biggest blind spot. “Retailers really lose the customer between channels, not inside channels,” she said.
She added that retailers must understand the full omnichannel journey rather than manage individual channels separately if personalisation is to work consistently at scale.
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