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.
Mobility analytics and location intelligence allow you to select the ideal location for opening a restaurant or coffee shop.
Have you ever wondered what your favorite coffee shop does to offer you a unique experience?
With location intelligence solutions it's possible to determine one or more areas where you want to establish a new coffee shop, while mobility analytics identifies all the factors that can be used to maintain and increase its success.
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.
Sushi Itto, a restaurant located in Plaza Fontabella, zone 10, in Guatemala City, captures a potential market of 430 thousand consumers within a 15-minute drive, of which 11% are interested in Japanese food.
Using the Geomarketing solutions we have developed for our clients, CentralAmericaData's Business Intelligence team analyzed the environment of some of the main locations of Asian restaurants operating in Central American countries. Below is an excerpt of the study's findings.
Relocating existing restaurants, strengthening the digital sales channel and identifying the areas where consumers are currently concentrated in order to choose the location of new stores are some of the strategies of the chains when executing their expansion plans.
As a result of the covid-19 outbreak, several expansion projects were affected, which must now reinvent themselves and adapt to the new commercial reality, in which consumers have different lifestyles.
In the last quarter of 2020 and in January 2021 in Panama, Honduras and El Salvador interest in fast food reported a clear rebound, contrary to the situation in Guatemala, Costa Rica and the Dominican Republic, markets where Internet searches decreased.
Through a system that monitors in real time changes in consumer interests and preferences in Central American countries, developed by CentralAmericaData, it is possible to project short and long term demand trends for the different products, services, sectors and markets operating in the region.
Taco Bell, located on 6th Avenue in zone 9 of Guatemala City, has a potential market of 315,000 consumers 15 minutes away by car. Of this group of people, 26% are interested in fast food and 15% in Mexican food.
Using the Geomarketing solutions we have developed for our clients, CentralAmericaData's Trade Intelligence team analyzed the environment of some of the main locations of fast food restaurants operating in Central American countries. Below is an extract of the study's findings.
In Central America, nearly 13 million people search online and participate in conversations related to pizzas, with Papa John's, Pizza Hut and Domino's Pizza being some of the chains with the greatest presence in consumer interactions.
An analysis of consumer interests and preferences in Central America, prepared by the Trade Intelligence Unit of CentralAmericaData, provides interesting results on people's preferences and tastes in food and all kinds of products or services, as well as restaurant chains and activities.