Nowadays, the abundance of data and the advances in Machine Learning and big data applications reduce the need for top-down segmentation of customers. Smart customer clustering based on many commonalities help companies better address customer needs to provide the right experience and divide resources efficiently.
A store's location directly impacts supply, profits, marketing, and almost every other aspect of store performance. Much can be learned from the performance of different types of retail stores in different neighborhoods, countries, or even climate areas. Therefore, retailers use geospatial data machine learning models to plan store locations and predict profits.
Fair trade certification is the confirmation from an official organization that a product was produced and sold according to fair trade principles: mainly, fair compensation to farmers for their labor.
Additional goals of fair trade networks include environmental sustainability and women’s empowerment.
Precision agriculture refers to the management of farms with satellite and other data and technologies. The resulting maps provide highly detailed information about the topology and condition of farms, down to the individual plants.
Other common terms for precision agriculture include satellite farming and site-specific crop management.
Smart farming refers to the use of connected technology and artificial intelligence in the field of agriculture. It is also referred to as smart agriculture, agritech, agrotech, or even agro technology. However, the terms agritech and agrotech include the fields of horticulture and aquaculture.
Smart building technology arms a building’s component systems with the ability to communicate with each other and with management. Security systems, plumbing, electricity, waste management, temperature control, and more work exchange data constantly in order to improve the comfort and safety of people living or working inside the buildings.
Smart building technology works for both residential and commercial buildings.
Smart factory technology allows factory sensors to communicate with each other, with employee mobile devices, and with management's software platform. This enables employees to monitor equipment 24/7 and receive immediate alerts whenever there is a problem. The technology also enables the equipment itself to automatically adjust operations in order to keep the factory running smoothly.
A smart stadium uses IoT to collect, analyze, and act on data within a stadium. This data may come from the stadium itself or from the mobile phones of visitors. Some stadiums also collect data on surrounding areas, like parking lots.
A sea-faring vessel using a variety of sensors to manage its regular processes and navigation is a smart ship. Uses of this IoT technology range from single vessel to fleet management. However, even management of a single ship involves using massive amounts of data.
AI has been used to improve supply chain and demand forecasting for a couple of decades. Demand planning applications use data driven algorithms to take historical data and use it to forecast. Demand forecasting can include promotion planning or stock and sales forecasting. The machine looks at the forecast, compares it to actual shipments, and suggests alternatives and optimization options. Over time, many companies started doing more specific forecasting for specific regions, products or stores or for more granular points in time. Both retailers and their suppliers (CPG companies or 3rd party shipping and supply chain companies) use their data to help conduct automated decision making within the supply chain.
Targeted marketing is a marketing strategy which identifies an audience that is most likely to buy a product or service and subsequently creates a marketing campaign designed specifically to advertise said product or service to the target audience, using advertisements and promotional messages. This allows different companies to hone in on certain market segments, creating a "specialty" and possibly lowering competition with similar companies.
Cities produce large amounts of waste, from litter to sewage; managing this waste is a constant challenge for municipal authorities. Waste management as part of the smart city model involves the use of IoT technology and machine learning to run and to optimize city waste management.