Overview
Conventional staff roster schedulers make it challenging for store managers to anticipate and accommodate varying store traffic. Fixed rosters can result in either understaffing, impacting customer experience, or overstaffing, wasting resources.
Leveraging historical footfall patterns and AI models, FootfallCam Staff Roster App recommends an ideal staff-to-footfall ratio for optimal staffing levels.
FootfallCam AI
Without visibility to historical and projected footfall data, store managers have to plan staff rosters in a “uninformed” manner, relying solely on guesswork.
Leveraging diverse datasets such as historical footfall, weather, holidays, and more, FootfallCam AI intelligently processes and recommends the optimal staffing levels based on predictions.
By adopting AI recommendations for determining the ideal staff numbers, retail stores can avoid unnecessary labour cost wastage while enhancing the customer experience.
Features
Leveraging the footfall data and predictive analytics, it helps operation managers with smart staff allocations based on golden ratio of footfall-to-staff.
The review of staffing levels in a retail store is essential in ensuring that there is an optimal balance between customer service and labour cost to achieve optimised shopping experience.
A workspace for operation managers to import staff data and ensure the data readiness for staff planning purpose.
How Does the App Work?
Import or configure a comprehensive list of employees, which includes their permitted working hours and corresponding wages, for the purpose of staff planning. This allows the app to effectively generate staff schedules based on the available workforce.
Store managers can optimise staffing levels and resource allocation by leveraging footfall data to determine the ideal footfall-to-staff ratio. This allows them to align staff schedules with fluctuating footfall patterns and peak periods, resulting in more effective utilisation of resources.
Incorporating advanced Artificial Intelligence (AI), the app intelligently recommends staff rosters based on staff profiles, projected footfall, and sales data. This ensures optimal staffing levels to provide a superior customer experience. Users can also make manual adjustments to the roster for specific functions or time periods as required.
Constantly reviewing staffing levels can help identify potential issues such as understaffing, which could result in missed sales opportunities due to inadequate customer service, or overstaffing, which can lead to unnecessary allocation of resources and increased labour costs.
Case Studies
See all Case StudiesA pharmaceutical retailer in the APAC region with 15,000+ stores globally.
