In order for retailers to stay ahead of digital competition, they must overcome cost and flexibility disadvantages; it's necessary to have real-time insight into what is happening inside and outside the point of sale.
Retailers must begin to take immediate action on unforeseen events at their physical points of sale, such as lack of inventory, shelf problems, environmental impacts, local events, loss of merchandise and customers, among many others, as they generate a significant loss for their business.
In the digital era, data is being created at a speed never seen before, and its proper application in business intelligence is already generating incalculable value for businesses
It seems irrational to suggest that a concept like data could be more valuable than an established and indispensable product like oil, but as the years have gone by, this already seems like a reality.
Through data analytics it's possible to improve vehicle performance, reduce costs, improve processes, establish strategies, optimize routes and times, and foresee and identify problems, among others.
Transportation analytics takes a variety of data ecosystems, helping industry leaders to use advanced analytical techniques such as machine learning, Big Data and geospatial data to optimize business strategies in the sector.
New data management methodologies now allow retailers to take advantage of even the smallest piece of information to generate valuable insights that help optimize their marketing and customer loyalty strategies.
What promotions do we do to get more customers to the point of sale?
How do we make them stay longer in the store?
How do we improve the customer experience so that they buy more at each visit?
The process of data monetization, a concept that until recently was present only in conversations between technology experts, is now one of the recurring topics in strategic meetings at the management level in companies.
What is Data Monetization?
The concept of data monetization refers to the process of extracting, cleaning and analyzing the millions of data generated within a company, with the purpose of obtaining a benefit or economic value. This value can range from using the information to create performance indicators of the company's own business and use them to optimize processes and make better strategic decisions, use it as input in the creation of other products or services, market it to third parties, share it with business partners, among others.
New technological tools improve logistics processes by generating visualizations that map in detail thousands of assets identifying cost trends, performance along maritime, land and air routes among others.
New technological tools, such as GIS, Big Data, mobile devices, and artificial intelligence, accumulate huge data sets within the logistics processes of any business, so using the right techniques, it is possible to improve operations and generate visualizations that can show a detailed mapping of thousands of assets worldwide, thus being able to identify cost trends, yields along maritime, land and air routes, compare historical arrival and departure times of carriers, among many others.
Artificial intelligence is the main driver of the change that companies are beginning to experience, which are already optimizing their business decision-making processes and strategies with algorithmic and predictive models.
The times are long gone when the term artificial intelligence was used and understood only by professionals in the technology world.
Many decision makers in the construction industry don't know what to do with the vast amount of data they have available, as they don't have the right tools to analyze it in a way that will have a meaningful impact on their projects.
Predictive modeling, Big Data analytics, machine learning and artificial intelligence unlock the ability to leverage the data coming from projects to organize and interpret it and thereby discover patterns more quickly. These tools reduce problems, lower costs and mitigate the risk of different processes in construction projects by making the work more predictable and efficient.
Thanks to advanced Big Data techniques that make it possible to collect and analyze large volumes of mobility data, it is possible to establish where consumers live and where they go before visiting a shopping mall or supermarket.
Today, business leaders have access to Business Intelligence solutions that are based on millions of anonymized data generated every second by cell phones, records that allow increasingly accurate estimates of the levels of affluence received by commercial establishments.
Analyzing the number of consumers who visit the establishments of any retail company, establishing the days and hours of greatest affluence and comparing it with competing sales points, is possible with Big Data techniques that allow the collection and analysis of large volumes of mobility data.
The millions of anonymized data generated every second by cell phones in all markets around the world make it possible to make increasingly accurate estimates of the levels of customer traffic received by commercial establishments.
Using today's technology, it is possible to know and accurately monitor consumer mobility, identify the places they visit, how often they do so, at what times and on what days, and transform this mobility and pedestrian flow data into solutions for optimizing commercial and marketing strategies.
People mobility is a concept that covers much more than just movement.
Through information solutions based on the use of satellite photos, the application of classification models and the implementation of machine learning algorithms, it is possible to optimize the management of large plantations and minimize the risks faced by crops that affect profitability per hectare planted.
The growing availability of data that exists today is leading companies to seek new ways and tools to take advantage of this huge wave of information that is being generated in different business sectors.
By collecting and analyzing the information that Internet search engines store on the queries that consumers make, it is possible to know with a high degree of precision what their interests are and to look for patterns or trends that help to measure performance indicators for a specific topic.
Through systems that provide real-time monitoring of changes in consumer interests and preferences in different countries, it is possible to project short- and long-term demand trends for the different products, services, sectors and markets operating in the regions.
With the technologies available it is possible to use satellite photos to detect types of surfaces and roofs, objects, land use and variance in farmland, and then analyze the results and transform them into useful data for business decision making.
In the past, it was possible to establish whether an area was industrial, commercial, residential or agricultural by analyzing aerial images, but today, with the use of high-resolution satellite images, more information can be obtained.
Honda Center, a service shop located in Guatemala City's Zone 10, has a potential market of 93 thousand consumers between the ages of 25 and 60 years old, of which 66% are interested in vehicle-related topics, within a 15-minute drive.
Using the Geomarketing solutions we have developed for our clients, CentralAmericaData's Business Intelligence team analyzed the environment of some of the main automotive repair shop locations operating in Central American countries. Below is an excerpt of the study's findings.