Big Data brings together data from different applications, infrastructures, third-party sources and emerging technologies such as location analytics to improve decision making in the strategic, tactical and operational processes that make up supply chain management.
This tool reshapes the supply chain by providing useful and actionable data that can help improve the efficiency of individual companies and the ecosystems in which they operate,helping to synchronize supply chain planning and execution by improving real-time visibility into these processes and their impact on customers and the bottom line. Read the complete article here
Foot Traffic analytics can identify the characteristics of transit stops and routes, helping to determine and improve the overall coverage of any transit system.
When it comes to public transport, foot traffic analytics can be of great help to authorities, who are faced with various challenges such as road congestion and the diversity of modes of transport, among others. This poses difficulties for public transport managers and operators when it comes to planning.
The secret to site selection in such a competitive market is based on the ability to analyze the right data and be able to understand and interpret the site selection strategies of nearby locations to stay ahead of their expansion plans and gain a competitive advantage.
Where? This is the fundamental question that guides any site selection decision. Tools such as location intelligence and footfall analytics enable the aggregation, analysis and visualization of spatial data and bring significant advantages to the site selection process.
Location intelligence is a key tool that shopping center managers should use since, via people’s location and mobility data, they gain valuable insights such as how much time consumers spend in stores and how often they visit.
Shopping centers can use this technology to collect geospatial data sets, transaction history, and point-of-sale data, as well as other business processes for in-depth geographic analysis by providing demographic data on adjacent businesses, including competitors.
Supermarkets can apply location intelligence techniques and footfall analytics to understand consumer mobility patterns, generate efficient site selection strategies, understand the performance of their stores, and estimate competitor turnover.
The correlation between foot traffic visitation, sales, and the success of retail supermarkets 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.
POI characterization through Big Data has become more frequent as it allows the implementation of strategies and site selection solutions within the various business sectors.
Leaders use these techniques to make more efficient and concise decisions that generate greater profitability by maximizing revenues and optimizing costs.
Case Study: Visitor profiling at Perisur, one of the most exclusive shopping malls in Mexico City.
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.
The heat map is one of the most useful and powerful data analysis tools in business intelligence. It provides a visualization feature that presents multiple pieces of data in a way that makes immediate sense by assigning a different size and color.
New geographic information systems (GIS) allow us to see our complex world in a new way. With the right data sets, heat maps can be produced that show how different factors vary from one area to another. In recent years, several organizations have developed dynamic mapping systems that allow users to choose areas, data layers, filters, and presentation features. Read the complete article here
Understanding mobility and identifying points of interest help large retail office products suppliers to measure foot traffic in and out of their stores and to better comprehend the behavioral patterns of consumers.
The correlation between foot traffic, visits, sales, and the success of retail office products suppliers has been studied and proven, so the development of this type of analysis has become a priority in the site selection process and expansion modeling.
Retail home improvement franchises need to apply location intelligence techniques and foot traffic analytics to identify consumer mobility patterns, in order to maximize sales and generate more efficient expansion models.
The correlation between foot traffic, visits, sales, and the success of hardware home improvement 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 modeling.
Retailers are already implementing Big Data tools such as location intelligence and foot traffic analytics to understand consumer mobility patterns, measure foot traffic at each store, understand the performance of their outlets, and estimate competitor turnover.
Location Intelligence is transforming the way brands communicate with their current and potential customers, maximizing marketing campaigns and optimizing costs.
Location analytics leverages and enhances marketing campaigns by providing faster and deeper insights to your customers.
Location intelligence and POI characterization through Big Data are increasingly being used to make business decisions in the retail, real estate, logistics, and port sectors, among others.