Case Study
Turning Store Traffic into Sales with Tictag Insight
A Leading Sports Retailer Turns Customer Insights into Smarter AI-Driven Decisions
Introduction
A leading sports retail brand with multiple stores across Southeast Asia is seeking to enhance its in-store performance. Known for its extensive selection of sporting goods and apparel, the retailer aims to deliver engaging shopping experiences while maximising sales conversions.
Situation / Problem
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Limited Visibility of Store Traffic: The retailer lacks detailed footfall data, making it challenging to measure marketing effectiveness, assess the impact of promotions, and identify peak shopping hours for optimising staff schedules and promotional timing through data-driven methods.
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High Traffic, Low Conversion & Limited Customer Behaviour Insights: Stores often have busy periods but low sales, and it is difficult to pinpoint the underlying reasons, such as product placement, customer engagement, or layout issues, that impact conversion and the in-store experience.
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Supplier Coordination Gaps: Insufficient data makes it challenging to provide partners with accurate demand signals, potentially leading to stock mismatches and missed sales opportunities.
Proposed Solution
To address these challenges, Tictag Insight is providing a comprehensive AI-powered retail analytics platform that gives the retailer unprecedented visibility into store performance:
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Footfall Tracking & Hourly Analysis: Identifies peak hours to support data-driven operational decisions, such as optimising staffing levels and promotional timing.
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Customer Journey Analytics: Maps visitor movement patterns to inform product placement and layout.
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Hot & Cold Zone Mapping: Highlights high- and low-traffic areas for smarter merchandising.
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Queue & Conversion Metrics: Tracks engagement and purchase intent around cashier zones.
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Regional Dwell Time Monitoring: Measures how many customers spend a certain amount of time in specific store areas to provide insights on overall footfall distribution and engagement patterns.
Implementation Approach
Tictag Insight is being deployed across multiple store locations. The focus is on:
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Accurate Data Capture: Ensuring staff movements and anomalies do not distort analytics.
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Clear Dashboards: Providing store managers with transparent, actionable insights.
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Scalable Rollout: Designed to expand across regions without heavy hardware investments.
Early Insights & Anticipated Impact
Even in the early stages, the deployment is already providing valuable insights:
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Sharper Data-Driven Insights: Clearer visibility into customer traffic and behaviours.
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Optimised Merchandising: Heatmaps revealing opportunities to refine product placement.
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Stock and Supplier Planning: By analysing footfall against conversion rates, the data is helping uncover potential product demand gaps, such as high interest but low sales, supporting more accurate forecasting and stronger coordination with suppliers.
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Smarter Operations: Peak-hour analysis is guiding better staffing and resource allocation.
Conclusion
By adopting Tictag Insight, the retailer is beginning to shift from assumptions to data-driven decision-making. The platform is delivering actionable insights that are expected to enhance merchandising, elevate customer experiences, and improve conversions across all locations. This ongoing project demonstrates how AI-powered retail analytics can transform store performance without requiring additional hardware or heavy investments.
👉 Start making data-driven retail decisions today!