Nestlé International Travel Retail (NITR) has reported increased in-store shopper engagement following changes to its brand ambassador programme.
The changes, based on traveller statistics and passenger forecasting, were prompted by a joint project with Counter Intelligence Retail (CIR).
According to NITR, the project identified which nationalities are travelling through key airport terminals, with data processed by day of week and time of day. Using intelligence on future passenger traffic, Nestlé said it has optimised future staff planning over a four month period.
 |
The research module aims to help retailers and brands optimise investments in store staffing |
NITR Global Head of Sales Alan Brennan said: “We’ve worked with CIR’s new time of day/day of week traffic forecasting module to pinpoint just when our target traveller groups are in the key terminals. We’ve been able to get a detailed view of the peak times and the expected volumes of traffic in our most important trading locations.
“Using this data, we’ve been able to allocate the right number of appropriate language speaking brand ambassadors across our focus terminals. The analysis has meant we’ve been able to target the best days of week and optimal time of day, to place the right people in the right place. This data is now an essential part of our staff optimisation programme.”
According to NITR, the analysis has had a “significant impact” in the way their brand ambassadors have been able to help and influence shoppers in store.
NITR Category Manager Paul Wheeler commented: “Our brand ambassadors are now reporting greater levels of engagement with shoppers and we’re seeing this translating in to increased sales in the locations where we’ve made changes.”
CIR Business Lounge Manager Kathryn Martinez commented: “This latest development is designed to provide the data and analysis that brands and retailers need to optimise the investment they place in store staffing.”
The analysis is generated using multiple sources of data to identify key travel patterns at the most detailed level possible, CIR stated.
 |
