Case Studies
Maximising Flagship Store Performance During High Traffic Event
Client Overview
Industry: Retail
Solution: Tictag Insight AI
A leading sportswear retailer partnered with Tictag to optimise in-store performance during peak promotional events. Early projections indicate conversion rates increasing from 1.85% to ~5%, average transaction value rising by 10–25%, and dwell time in key zones improving by 20–50%, while providing full visibility into foot traffic and customer behaviour. Read on to discover how these insights unlocked measurable retail impact.
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Background
A leading sportswear retailer operates premium flagship stores in high-traffic malls, focusing on providing an engaging in-store shopping experience with performance footwear, lifestyle apparel, and seasonal promotions. Its mission is to attract both loyal high-intent buyers and general visitors while maximising conversion and store efficiency during peak traffic periods.
Key Challenges
The store faced recurring issues that limited sales performance and customer engagement:
- Staff stretched during late-afternoon peak hours, leading to missed customer interactions and slower service.
- Certain store zones had low engagement despite being prime retail space.
- Strong footfall was not translating into finalized sales, particularly for high-value products.
- Revenue was sensitive to competitor promotions, leaving gaps in capturing mid-market customers.
- Existing operational insights were limited, making it difficult to optimise staff deployment and visual merchandising.
The Solutions
Tictag deployed Tictag Insight, an AI-powered retail analytics system designed to:
- Optimise staff deployment and reduce missed customer interactions during peak hours.
- Monitor dwell time and engagement to activate underperforming store zones.
- Analyse customer journeys to identify high-intent visitors who leave unassisted, improving conversion.
- Detect patterns during competitor promotions and recommend tactical offers without impacting margins.
Projected Result & Business Impact
- Conversion rate projected to increase from 1.85% to ~5%
- Average transaction value (ATV) projected to rise by 10–25% through bundle and upsell strategies
- Dwell time in low-traffic zones projected to increase by 20–50%
- Peak-hour service efficiency projected to improve, reducing missed customer interactions during 17:00–19:00
- Revenue retention during competitor promotions projected to improve via tactical “stealth” offers
These numbers are projections derived from applying the recommended operational, merchandising, and marketing strategies in the report, rather than measured post-implementation data.
Future Opportunities
- Scale Tictag Insight across multiple stores and other high-traffic locations to optimise conversion and peak-hour service.
- Enhance zone activation strategies with dynamic layout and product placement adjustments based on ongoing dwell-time and engagement analytics.
- Integrate predictive staffing to anticipate peak-hour surges and improve service capacity.
- Expand marketing tactics using data-driven, competitor-aware offers to protect revenue during promotional gaps.
- Leverage AI insights for merchandising to continuously optimise high-value displays and underperforming zones.
Conclusion
By deploying Tictag Insight, the store not only gained a real-time solution to optimise staff deployment, activate underperforming zones, and improve conversion, but also received a comprehensive, actionable report detailing visitor behaviour, dwell times, and operational bottlenecks. These insights empower the store to make informed decisions, protect revenue during competitive periods, and continuously enhance the customer experience, turning high footfall into measurable sales impact.
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