Case Studies
Lotte Mart Vietnam Leads the Way: Cutting Errors and Boosting Efficiency with AI
Overview
Lotte Mart Vietnam partnered with Tictag to optimise its online grocery fulfilment operations. Early results already show up to 30% faster packing, 60–80% fewer packing errors, and 10–20% labour-cost reduction, while providing full traceability of orders and packing activities. Read on to see how these results were achieved and the full operational impact.
Photo: Lotte Mart Vietnam, Source: https://www.lottemart.vn/en-bdh/about-us
Background
Lotte Mart Vietnam operates an omnichannel supermarket network serving urban consumers, placing strong emphasis on online grocery orders and same-day delivery supported by physical hypermarkets. Its mission is to provide reliable, convenient access to fresh food and household essentials while maintaining competitive prices and high service standards for families and working professionals.
Key Challenges
Lotte’s operations team faced recurring issues that impacted both efficiency and customer experience:
Frequent customer complaints about missing, extra, or expired items, damaged packaging, and late deliveries.
Significant staff time spent processing refunds caused by product shortages, damaged or low-quality items, incorrect promotions, or packing errors.
Manual packing and quality-control workflows that were error-prone, inconsistent, and difficult to scale during peak demand.
Lotte needed to improve packing accuracy, speed, and traceability without increasing manual oversight.
The Solutions
Tictag deployed its AI-Enabled Packing Checker, an intelligent visual-AI system designed to:
- Reduce packing errors and strengthen SOP compliance
- Provide real-time guidance and alerts during packing
- Deliver end-to-end traceability of orders, trolleys, and staff activity
- Improve fresh-food handling and shorten order lead time
Implementation
- Step 1, Data Collection Design: Tictag analysed existing picking and packing workflows, delivery-zone layouts, and CCTV coverage. From this, the team defined data-capture protocols (video angles, barcodes, trolley IDs, staff IDs) and conducted proof-of-concept trials in selected stores.
- Step 2, Expert-Led Labelling: Domain experts mapped Lotte’s packing SOPs like SKU grouping, fresh-food handling, shockproof wrapping, carton sealing and guided Tictag’s labelling team to annotate video data with strict QA standards.
- Step 3, De-identification & Structuring: Raw visuals were de-identified to protect customers while preserving key operational signals (hands, products, trolleys, boxes). The cleaned data was structured into modules such as SKU recognition, SOP-compliance detection, trolley tracking, and packer re-identification.
- Step 4, Building the Final Dataset: Tictag consolidated labelled data into training and validation datasets with clear performance metrics (barcode accuracy, multi-item detection, wrapping/sealing detection). These were integrated into the AI-Enabled Packing Checker for a smooth pilot deployment.
Result & Business Impact
The AI-Enabled Packing Checker delivered measurable operational impact:
- 30% faster packing time driven by real-time AI guidance
- 60–80% reduction in packing errors, improving order accuracy and customer satisfaction
- 10–20% labour-cost reduction due to reduced manual supervision
- Full traceability of each order, enabling managers to verify incidents quickly and accurately
Future Opportunities
- Scale the solution across additional Lotte stores and regional fulfilment hubs
- Adapt the system for dark stores, micro-fulfilment centres, and new retail formats
- Introduce future modules such as dynamic workforce planning and AI-assisted shelf-stock audits
Conclusion
Tictag helped Lotte Mart Vietnam shift from manual supervision to AI-assisted, data-driven packing operations. The solution delivers a faster, more accurate, and fully traceable workflow that enhances both operational performance and customer satisfaction.
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