Uber Freight Shipper allows smart shipping by streaming operations. This offers instant capacity, quotations, freight managament, and customer support.
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.
Property value and mortgage value assessment is the estimation of the future value of a particular asset for purchase, insurance, and more.
Unlike most other purchases, real estate tends to rise in value over time. This rise is influenced by economic and social trends, environmental conditions, and on governmental controls and regulations. These large-scale trends directly affect the general demand for property ownership, the scarcity of property for purchase, the utility of the property for potential owners, and the ease at which property rights can be transferred.
Posti Group Shipping & Logistics Data comprises e-commerce, parcel tracking, and traffic data to deliver parcels to millions every weekday
Uber Freight Shipper allows smart shipping by streaming operations. This offers instant capacity, quotations, freight managament, and customer support.
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.
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.
Customer lifetime value (CLTV) is the expected profit that a single customer brings to a company over the course of their lifetime. CLTV represents a shift in emphasis from quarterly or annual profits to the long-term relationships with customers.
Price optimization is the mathematical analysis by a company determines the response of potential buyers to different prices for its products and services. The aim is to meet a company’s objectives of maximizing profits and growing and retaining a customer base.
Property value and mortgage value assessment is the estimation of the future value of a particular asset for purchase, insurance, and more.
Unlike most other purchases, real estate tends to rise in value over time. This rise is influenced by economic and social trends, environmental conditions, and on governmental controls and regulations. These large-scale trends directly affect the general demand for property ownership, the scarcity of property for purchase, the utility of the property for potential owners, and the ease at which property rights can be transferred.
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.
Portfolio management is the management of investments to meet long-term financial objectives.
Today, machine learning models and external data are used in order to help companies and individuals better manage, diversify, and maintain their assets and take on less risk for higher reward.
Today, machine learning models and external data are used in order to help companies and individuals better manage, diversify, and maintain their assets and take on less risk for higher reward. Portfolio management models and use cases include any collection of investment instruments like shares, mutual funds, bonds, FDs and other cash equivalents, etc.
Exante Global Flow Analytics supports alpha generation and risk management by extracting comprehensive price signals from detailed capital flow analysis. Exante complements hard data and raw model outputs with timely, narrative-based content, focusing on key global thematics and risk scenarios. Additionally, Exante maintains dialogues with their clients, providing bespoke coverage and service.
Stirista offers data that politicians and advisors can use to reach out to constituents and donors. Stirista has (so far) 150 million registered voter details sorted into 360 data points, including donation history. With this contact, demographic, web, and behavioral information, Stirista Political Data enables targeted advertising and outreach.
Stirista can also provide historical campaign data at all levels to help politicians plan effective political strategies.
Acxiom Infobase provides customer insight data for targeted marketing campaigns in a wide variety of industries
Acxiom Personix offers people and customer lifetime value data as well as consumer behavior profiles
AnalyticsIQ’s BusinessCore Database provides B2B marketing data on 18 millions businesses and 60 million business professionals.
The BusinessCore Database collects company data and people data. The company data includes contact information, purchase drivers (price, for example), and transaction history. The people data includes personnel contact data, role in the company, and purchase transaction history.