Company Data

Network segmentation refers to the act of dividing different parts of a network into separate segments or subnets. This is done either physically or technologically, usually as part of a network access control system that limits who can access what parts of the network.

Once organizations have identified subnetworks, they establish virtual fences around them using a variety of techniques, including VLANs, SDNs, and firewalls.

Taking the place of an in-person managers, a financial robo-advisor provides personalized investment and wealth management services to individuals as well as small and medium-sized businesses.

Robo-advisors use deep learning and other artificial intelligence techniques to offer advice and even automate trades in a variety of industries and account types, from individuals with retirement accounts to small businesses with equity finance plans.

Employee onboarding refers to the process of welcoming and training new employees. This includes setting up their details in the HR system, providing them with security clearances, training them in the company’s policies and the duties, and integrating them into the social life of the company.

Survey after survey shows that effective onboarding is crucial to employee retention and company reputation, but few organizations set up a well-planned, data-based system.

Remote employee management refers to the methods of managing remote workers. Whether they are seasoned in-field professionals or office workers newly adjusting to working from home, the approaches may be different but the data collection and analysis will be similar.

In these fraught times, especially, managers must take special care to account for their employees’ mental states.

Brand repositioning refers to the process of changing the associations that people have with a brand.

More than a superficial change like a logo redesign, a repositioning strategy represents a radical change in a company’s marketing and identity. Rarely do companies reposition themselves without great need.

Share of voice (SOV) refers to the amount of engagement your brand receives within your target market. It also specifies the sentiment behind the engagement—that is, whether people feel positively or negatively about your company.

More than a static budget sheet in Excel, an AI financial planning program helps users set budgets and analyze their spending behavior. With a good ML program, company and personal budgets perform better—faster than via traditional methods.

Competitor analysis is the process of understanding your competition in order to succeed in the marketplace. With a proper competitor analysis model, you can benchmark your progress against more established competitors, identify your target market, and even anticipate new products or services from your competition.

Brand affiliation measures people’s identification with a certain brand. More than recognizing a brand or liking their products, affiliation refers to a personal connection, where customers feel like the brand represents them.

Most employees do not feel engaged or motivated at work.  To deal with this issue, many companies are turning to data-driven solutions like AI machine learning models.

Organizations must satisfy the unique demands of their customers. The good old days of mass marketing and predictions on limited mixture of products in one location are gone. Conversely, the use of artificial intelligence in inventory generates huge dividends to companies willing to reshape their supply chain orders.

This technological development results from the availability of massive amounts of real-time data now routinely generated by enterprise software systems and smart products. By collecting this data, organizing it, and interpreting it, artificial intelligence and machine learning have introduced an entirely new level of data processing leading to deeper business insights.

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.