Micro-mobility analytics improve retailers’ expansion strategies by accurately identifying consumer demographics, understanding customer behavior, and understanding how their competitors are performing.
Micro-mobility is a methodology that combines geospatial data and foot-traffic analytics to solve several problems and improve site selection strategies by helping to understand how people move around specific brick n’ mortar locations, allowing companies to analyze movement patterns around specific locations, such as retail stores, to extract meaningful information.
Footfall analytics and POI characterization through Big Data are being used by different business sectors in order to make smarter business decisions and thereby maximize their revenues and optimize their costs.
Case Study: POI analysis of N1 City in Cape Town, South Africa
Footfall analytics have revolutionized the way retailers implement site selection, commercial and operational strategies in the quick-service restaurant franchise market.
The correlation between location and footfall analytics, visits, sales, and the success of retail fast-food franchises have been studied and proven, so the development of this type of analysis has become a priority in the site selection process and expansion strategies.
Heat maps are used by any business sector to identify foot traffic and vehicular mobility patterns in an area or point of interest, as their visualization presents multiple pieces of data in a way that makes immediate sense.
Heat maps can be used to identify foot traffic patterns from a country-level scale to a more detailed level such as the infrastructure of a store or building.
Identifying mobility patterns and classifying consumers within a point of sale or areas of interest helps large retail fast fo measure foot traffic in and out of their stores while understanding the behavioral patterns of their consumers.
The correlation between location and footfall analytics, visits, sales, and the success of retail fast-food franchises have been studied and proven, so the development of this type of analysis has become a priority in the site selection process and expansion strategies.
Footfall analytics and POI characterization through Big Data are being used by retail industry leaders to make smarter business decisions, by maximizing revenue and optimizing costs.
Case Study: Footfall analysis of the largest Starbucks Coffe in Bangalore India
At PREDIK Data-Driven we conducted a detailed study of Starbucks Coffe, the largest physical store in Bangalore, India. Through a footfall analysis and POI characterization of the area and people who visited that establishment, we estimated the foot traffic, identified the most and least crowded places, classified the users who visit, live or work in the area, the observations per day, the most and least visited places by the establishment’s customers as well as their relative wealth index characteristics.
With Big Data management techniques, companies can optimize their strategic business planning, by taking advantage of market and companies' data.
Big data has emerged as a powerful tool that organizations can use to leverage data-driven decision making for better strategic planning, determine which market niches of their products, are growing or shrinking, obtain traffic data of their stores or website, determining where they come from, what kind of devices they use, dwell time, and foot traffic patterns to help analyze which promotions and efforts are successfully driving their business.
Location and Footfall Analytics has changed the way retailers implement marketing and commercial strategies in the fast-food restaurant franchise business.
Understanding consumers’ mobility behavioral patterns are critical for all types of restaurants. Big Data tools and spatial data play a very important role in these analyses since they make it possible to measure the foot traffic and mobility patterns of any area or point of interest.
Location Analytics has changed the way marketing and commercial strategies are defined in the fast-food restaurant franchise business.
Understanding consumers’ behavior patterns is critical for all types of restaurants. Big Data tools play a very important role in this analysis, since they make possible to measure the foot traffic and mobility patterns of a specific area or location, among other variables.
It is estimated that in the municipality of Antiguo Cuscatlán, in El Salvador, about 23% of the commercial establishments correspond to companies in the service sector, which are mostly beauty salons, supermarkets and clothing stores.
An analysis of commercial establishments in El Salvador, prepared by the Trade Intelligence Unit of CentralAmericaData, gives interesting results on the characteristics of companies operating in Antiguo Cuscatlán, a municipality in the department of La Libertad, according to their location and type of activity.
It is estimated that in San Salvador two out of every ten commercial establishments are service sector companies, which are mostly vehicle maintenance workshops, banks and consulting agencies.
An analysis of commercial establishments in El Salvador, prepared by the Trade Intelligence Unit of CentralAmericaData, shows interesting results on the characteristics of the companies operating in the country's capital, according to their location and type of activity.
By opening this new restaurant in Libertad Port, the chain now has 35 locations in the country.
The company already has 35 years in the Salvadoran market.
Laprensagrafica.com reported statements by Olmedo Quintanilla, Biggest Marketing Manager: "We believe that we are in a great country, as well as the best place in the zone, but it has been historically neglected by the industry."