Location intelligence and foot traffic analytics are transforming the way retail strategies are defined, and department stores are no exception.
The correlation between foot traffic, sales, and the success of department stores 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.
Identifying mobility patterns and classifying consumers within a point of sale or areas of interest helps large retail supermarkets measure foot traffic in and out of their stores while understanding the behavioral patterns of their consumers.
The correlation between foot traffic, visits, sales, and the success of retail supermarkets 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.
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
One of the analytical tools that leading companies use to gather knowledge is heat maps. By creating a graphical representation of their data, new insights emerge, providing companies with the information they need to adapt their strategies and maximize their profits.
Heat maps measure the density of data in a given area. By representing density with colors, heat map data easily identifies the areas where information is most prevalent.
In the competitive retail market, in-store analytics helps retailers to better monitor and understand their customers while providing valuable information on the actual point-of-sale performance.
This type of analytics has become an indispensable part of the operational strategy of brick & mortar retail stores. Its benefits can also be reflected in other areas, such as marketing, merchandising, and fraud prevention.
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.
POI analytics through Big Data techniques allows companies to understand an area of interest and thereby implement strategies, expansion models, and solutions within any business sector.
Information about a specific location or a set of similar locations can help companies make better decisions. Combined with additional contextual parameters such as human mobility, sociology, dynamics of an area, etc., POI data can be used to build meaningful information structures that enable more robust analysis and planning for expansion models.
Location intelligence and footfall analytics can be valuable tools for wholesale distributors to maximize their revenue, optimize their processes and choose the best distribution routes for their pickup and last-mile delivery processes.
The correlation between foot traffic patterns, visitation, sales, and the success of wholesale food distribution companies has been studied and proven, so the development of this type of analysis has become a priority in the process of site selection, supply chain process optimization, 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.
Location intelligence through techniques based on Big Data collects spatial data in order to improve the decisions made in logistics centers, allowing the use of location and its related data points, creating solutions and optimizing distribution routes.
This new technological tool finds its immediate application in space-dependent businesses, such as delivery and logistics companies. The data collected through infrastructure sensors, cameras and traffic mapping not only allows them to determine the best locations for their businesses, warehouses and centers, but also allows them to know why certain locations have a direct impact on the success or failure of a business.
Retailers can apply location intelligence techniques 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.
The correlation between foot traffic visitation, sales, and the success of retail apparel 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.
Foot traffic and location analytics help wholesale distributors maximize profits, allowing them to reveal where operational inefficiencies are and then implement solutions in problem areas.
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.
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.