Hanshow: Store Digital Twins turn insight to action

A Store Digital Twin is a continuously updated digital view of what is happening across a physical store. Its purpose is not simply to replicate the store on a screen, but to connect three things that are often managed separately: visibility of store conditions, decisions about what needs attention, and action by store teams. By continuously integrating data from products, shelves, shoppers, and store operations, it creates a living digital view of the store that reflects real-world conditions and helps retailers move from visibility to action.

In Hanshow's view, the long-term role of the Store Digital Twin is to create a continuous loop between awareness, intelligence, decision-making, and execution across everyday store operations.

To support this vision, Hanshow has developed a portfolio of interconnected solutions.

• NexShelf provides the intelligent shelf foundation of the Store Digital Twin, making shelf conditions visible, measurable, and actionable through Electronic Shelf Labels, location intelligence, and AI-enabled sensing.

• NexConnect smart cart solution extends the Store Digital Twin to the shopper journey through capabilities such as guided item finding, self-checkout, basket management, and retail media activation, while generating insights into campaign performance and in-store activities.

• NexMate robotics solutions support store operations through applications such as autonomous shelf inspection and intelligent cleaning, providing additional visibility into store conditions while helping automate routine execution tasks.

• xPilot, Hanshow's real-time intelligent store execution platform, helps retailers detect operational exceptions, analyse root causes, prioritise actions, orchestrate tasks, and verify execution outcomes

We have partnered with Rainbow Digital Commercial Co., Ltd. which is one of China's leading digitally enabled retailers and among the country's early pioneers in retail digitalisation. Founded in 1984 and headquartered in Shenzhen, the company operates nearly 200 retail locations across 36 cities, including 102 supermarkets.

Within the Store Digital Twin initiative, the three organisations play complementary roles:

• Rainbow contributes its retail operating expertise and real-world store environments to design, validate, and refine operational workflows.

• Hanshow provides the connected store infrastructure, intelligent IoT touchpoints, and real-time sensing capabilities that make store conditions visible, measurable, and actionable.

• Lingzhi Digital Technology, Rainbow's majority-owned technology subsidiary dedicated to AI and digital transformation for physical retail, serves as the project's core AI technology provider. Leveraging its Bailingniao retail-specific AI model, Lingzhi supports operational analysis, forecasting, decision-making, task orchestration, and performance optimisation.

• A recent example is Rainbow's newly upgraded Shahe sp@ce supermarket in Shenzhen, the retailer's first Store Digital Twin-enabled supermarket. Located in Shenzhen's Nanshan District, the store has served the local community of around 100,000 members for nearly 17 years and has built a loyal customer base

The exact timeline will depend on the scope and deployment strategy, but our experience shows that retailers can begin realising tangible value early in the rollout journey, while continuing to expand capabilities and scale adoption over time. 

Taking the Rainbow project as an example, the initial Store Digital Twin foundation was established in around two months, including NexShelf intelligent shelf infrastructure, NexConnect smart carts, NexMate inspection robots, and data integration. Over the following six months, additional AI capabilities, operational workflows, and optimisation applications were gradually introduced and refined.

Today, having refined our methodology through multiple deployments, we can significantly accelerate this timeline. More importantly, our focus is on ensuring that store operations remain uninterrupted throughout the rollout.

New technologies are introduced progressively and integrated into existing workflows, allowing them to become a natural part of daily store operations rather than creating disruption.

Successful implementation is not only a technology deployment exercise, but also a change-management journey. We place strong emphasis on store associate adoption, ensuring that new tools and workflows support daily operations in a practical and intuitive way.

The main benefit is a more proactive and evidence-led approach to store operations.

Instead of relying only on periodic checks or retrospective reports, store teams can use timely information about shelf conditions to identify exceptions, prioritise work and follow through on the actions that matter most.

A good example is out-of-shelf (OOS) management. Rather than relying on store associates to discover stock gaps during routine inspections, AI vision continuously monitors shelf conditions, while Hanshow's Nebular Ultra Electronic Shelf Labels provide precise item-level location intelligence to identify exactly where a missing product should be.

Lingzhi's Bailingniao AI model then analyses sales and operational data to generate replenishment recommendations and execution tasks. As a result, store teams can intervene earlier, replenish shelves faster, and reduce the risk of lost sales caused by unavailable products.

Beyond issue resolution, AI-powered merchandise optimisation can help retailers better understand shelf productivity and make more informed merchandising decisions, supporting more effective use of selling space and improving the productivity of store floor space.

The same foundation also supports planogram compliance, pricing and promotion management, and merchandise optimisation.

Rather than spending significant time on routine inspections, store associates can focus more on exception handling and customer service. Managers benefit from better prioritisation and execution, while headquarters teams gain a more consistent and scalable approach to store operations, helping successful practices be identified and replicated across the network more efficiently.

Early pilot results have been promising. In selected pilot programmes, planogram compliance for selected FMCG categories reached 99.5%, the out-of-shelf rate for core products was reduced from 3% to 0.5%, and adoption rates for AI-generated replenishment recommendations reached 85%.

These results demonstrate how real-time visibility, AI-driven decision support, and coordinated execution can work together to improve on-shelf availability and operational effectiveness.  

A defining characteristic of the project is its closed-loop operating model. Rather than treating data, insights, and execution as separate processes, the Store Digital Twin connects them into a continuous cycle.

Hanshow's intelligent infrastructure and IoT devices provide real-time sensing and visibility, while Lingzhi's digital twin capabilities and Bailingniao retail-specific AI model transform operational data into decision support across replenishment, pricing, planogram optimisation, merchandising, and promotion management.

Enterprise-grade AI agents then help orchestrate and automate task execution. Operational outcomes are subsequently fed back into the system, enabling continuous learning and optimisation over time.

By connecting insight with action, this closed-loop approach helps retailers move from reactive issue resolution towards a more proactive operating model that continuously learns, adapts, and improves.

More broadly, the Store Digital Twin enables retailers to move beyond reviewing what happened in the past and toward understanding what is happening now and what actions should be taken next.

Hanshow believes this transition from visibility to execution is one of the most significant opportunities in retail digital transformation today.

For suppliers, the opportunity is to improve planning and execution through a clearer, appropriately governed view of what is happening in store. Subject to the retailer’s permissions and data-sharing arrangements, information about on-shelf availability, promotional execution and efficiency and merchandising compliance can help suppliers and retailers identify issues earlier and discuss them using a more consistent operational picture.

Consider a beverage promotion as an illustrative example. If sales are below plan, a retrospective report may show the outcome but not the cause. Store-level operational context could indicate whether products were unavailable, displays were incomplete or promotional placement was inconsistent. The retailer and supplier could then address the execution issue while the campaign is still running, rather than waiting for a post-campaign review.

The value is therefore not simply more data. It is better coordination around specific commercial questions. With clear governance, access controls and agreed measures, this can support more informed forecasting, replenishment and category planning, while keeping the retailer in control of how store and customer information is used.

For shoppers, the biggest benefit is a more convenient, reliable, and engaging shopping experience.

Behind the scenes, improved inventory visibility and replenishment workflows help reduce out-of-shelf situations, making it more likely that customers find the products they want when they visit the store. Better pricing and promotion management also help ensure that product information, pricing, and offers remain accurate and consistent across the store Ultimately, the goal is not simply to add digital touchpoints, but to make shopping easier, more transparent, and more responsive to customer needs.

At Rainbow, digital services are designed to support the entire shopping journey. AI-powered shopping assistance helps customers discover relevant products and recommendations based on their needs, while Smart Cart and in-store navigation help them locate those products quickly and efficiently. Promotional offers, membership benefits, and checkout capabilities are integrated into the same experience, reducing the effort required to search for products, access discounts, or complete a purchase.

Customers also gain access to richer information at the point of decision. Through NFC-enabled shelf interactions and other digital touchpoints, shoppers can view product origin, nutritional information, promotional content, and membership-related benefits directly while browsing products.

This is particularly valuable in categories such as fresh food, health products, and promotional items, where additional transparency and context can support more informed purchasing decisions.

From product discovery to checkout, the objective is to make shopping simpler and more intuitive. By reducing the time spent searching for products, waiting in queues, or navigating fragmented information, retailers can create a smoother shopping journey while helping customers make purchasing decisions with greater confidence.

Retailers and suppliers have traditionally relied on sales reports and post-campaign reviews to assess performance. While these insights are valuable, they often show what happened without fully explaining why it happened.

Hanshow believes Store Digital Twins can provide that missing operational context, giving retailers and suppliers a shared, real-time understanding of store conditions. By bringing together information on product availability, inventory, shelf execution, promotions, shopper engagement, and operational tasks, retailers and suppliers can work from a common understanding of store conditions rather than separate datasets and assumptions.

This helps shift the conversation from reviewing outcomes to understanding the drivers behind those outcomes. For example, if a promotion is underperforming, both parties can determine whether the issue is related to product availability, shelf execution, promotional compliance, placement, or shopper engagement, and take corrective action while the campaign is still running.

In Hanshow's view, the next stage of retailer-supplier collaboration is not simply about sharing more data, but about creating greater alignment around objectives, operational realities, and actions.

Store Digital Twins provide the foundation for this by connecting real-time store visibility with decision-making and execution, helping retailers and suppliers move from transactional coordination toward a more connected model built around shared growth objectives and collaborative value creation.

As AI and agent-based capabilities continue to evolve, collaboration could become increasingly responsive, action-oriented, and closely connected to value creation for retailers, suppliers, and shoppers. Shared visibility will increasingly lead to shared decision-making and coordinated execution, allowing both parties to move more quickly from insight to action, and ultimately from alignment to measurable business outcomes.

One of the less visible benefits is the ability to create a common operational language across the retail organisation for a common understanding of operational triggers.

Traditionally, store teams, headquarters personnel, merchandising teams, and technology platforms often work with different datasets and operational priorities. Digital twins help bring these perspectives together around a shared view of store conditions and performance. This not only improves communication and alignment but also makes it easier to scale successful operating practices across multiple stores and regions.

Beyond organisational alignment, digital twins also create the foundations for continuous learning and improvement. Every decision and execution outcome becomes an opportunity to learn and improve. Over time, the value comes not simply from solving today's operational challenges, but from building an operating model that becomes progressively smarter, more adaptive, and more effective over time.

We believe the more immediate question is whether retailers and suppliers are building the foundations required to turn intelligence into action. The next generation of digital twins will not be powered by AI alone. It will depend on a deep understanding of retail operations, high-quality operational data, connected store infrastructure, standardised workflows, and the ability to translate insights into execution.

Retailers and suppliers should therefore focus on improving visibility into real-world store conditions, breaking down data silos, and establishing processes that allow insights to be translated into action consistently and at scale. Just as importantly, they should begin creating the feedback loops needed to measure results and continuously optimise operations over time.

The greatest value will come when both parties align around shared growth objectives, work from the same operational reality, and use a common framework to identify opportunities and coordinate action.

In Hanshow's view, the future of collaboration is not simply about sharing information, but about creating the conditions for faster, more informed, and more effective execution.

Hanshow believes the future store will bring the intelligence, convenience, and personalisation that shoppers have come to expect online into the physical retail environment, while preserving the immediacy, discovery, and human interaction that make in-store shopping unique.

For shoppers, this means a more intuitive, engaging, and seamless experience. Products will be easier to find, information will be easier to access, and recommendations will become more relevant and contextual.

Rather than encountering frustrations such as out-of-shelf situations, inconsistent information, or difficulty locating products, shoppers will benefit from a store environment that is increasingly able to anticipate needs and provide assistance at the right moment.

For store associates, routine activities such as checking shelves, identifying out-of-shelf situations, or managing planogram compliance will increasingly be supported by digital tools and AI, allowing employees to spend more time serving customers and handling exceptions that require human judgement. For store managers and headquarters teams, operational issues will become visible earlier, enabling faster decisions, more effective execution, and the ability to scale successful practices across the network more consistently.

The benefits extend beyond the store itself. Retailers will be able to operate more dynamically, continuously improving merchandising, inventory, promotions, and customer engagement based on real-world conditions. Suppliers and brand partners will gain a clearer understanding of how products, promotions, and campaigns are performing in store, creating new opportunities for collaboration, retail media, category growth, and joint value creation.

Ultimately, Hanshow sees the future store as a continuously learning and optimising environment. Every interaction, decision, and outcome contributes to improving the next one.

Over time, stores will become increasingly capable of sensing what is happening, understanding what matters, determining what action should be taken, and continuously improving performance.

The goal is not simply greater automation, but a retail environment that becomes smarter, more responsive, and more valuable for shoppers, retailers, suppliers, and brands in everyday operations.