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Hedge fund investments use several different strategies to achieve returns in both domestic and international markets. They are often aggressively managed and trade in land, real estate, stocks, derivatives, currencies, etc. markets.

The most lucrative hedge funds also have a diverse portfolio—which means investors need to analyze large amounts of data to make investment decisions.

Most if not all companies and organizations seek to establish themselves in social media platforms such as Facebook, Twitter, and Instagram in addition to their official website. Online and social media performance tracking is meant to analyze the effectiveness of a company’s social media presence. Are they generating new leads? Are they promoting brand awareness? These questions are important to assess the efficiency of the use of these social media platforms.

An online recommendation engine is software that analyzes available user data to generate suggestions for something the user may also be interested in. Such engines are used in an advertising capacity to promote products or services or for the purpose of recommending similar content to the content the user has consumed in the past, such as in streaming services and online shopping services.

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.

Promotional planning is the process of optimizing marketing tools, strategies, and resources to promote a product or service to generate demand and meet set objectives. Artificial intelligence (AI) can be used to effectively plan promotional events, measuring their outcomes, and adjusting as necessary to achieve growth.

Remarketing campaigns show ads to people who have visited a business’s website or downloaded one of its apps. Remarketing identifies people who have shown interest in a company in order to prompt them to recall the business, increasing the odds of them converting.

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.

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.

Algorithmic stock trading—aka “algo-trading”—uses machine learning algorithms to make stock market trades faster than a human could, calculating the best time, price, and amount to trade in an instant.

Any account management, customer success and support team has one key goal — to reduce and minimize churn. Churn prediction is the process of identifying segments or specific customers that are at risk of churning, i.e discontinuing their business, within a short amount of time in order to deal with the customer health issue as much in advance as possible. 

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.