Machine learning employs artificial intelligence to enable systems to automatically learn and get better in their work without being explicitly programmed. That allows the systems to adapt to the highly changing and uncertain world by using experience. The basis of machine learning is algorithms.

With business facing many challenges—competition, customer demands, and others—they need solid solutions to keep operating profitably and meet all of their obligations. Machine learning comes in to offer that much-needed help.

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Here are some ways of applying machine learning to business problems:

Detecting fraud

Since fraudsters are devising new methods to commit fraud every day, it is difficult to rely on concrete rules to arrest perpetrators. The systems must be in a position to make arrests in fraud cases in real time by picking out the various signals linked with fraud. A good case in point is PayPal, who incorporated new algorithms into their transaction process in a bid to curb money laundering to and from innocent and unsuspecting customers. The recently added algorithms pick out data points that are suspicious such as the amount of money spent, first-time transactions, the location of the sender and receiver, and other factors. Once the automated and filtered system flags a particular transaction, the next step is for humans to comb through them for fraud.

Online advertising

Online advertisers, social platforms, websites, and others doing marketing online cannot determine what advertisements a certain user or visitor to a site will click on. But thanks to machine learning, it is possible to observe the activities of users and identify certain trends in the users’ behaviour. With such information, it is possible to tell which ads are most likely to be relevant to the specific user. Businesses seeking to advertise online to remain competitive and solve a myriad of other issues need to work with machine learning experts like ActiveWizards to get the most from their efforts.

Recommending products to customers

While working with customers’ purchase history and a huge inventory of merchandise, machine learning can help to identify the products that certain customers could be interested in and may purchase. The focus of the algorithm is to unravel hidden patterns among the merchandise bought and then group related products into clusters. This model enables a program to give recommendations to customers and encourages purchasing. The application of this capability is evident among e-commerce businesses like Amazon. Facebook also applies machine learning together with location details and other such details to recommend friends and other things to users.

Lifetime value prediction of clients

Marketers face some challenges like customer lifetime value prediction, churn prediction, market segmentation, and others. With the wealth of data from various sources such as marketing email campaigns, site visits, and others, a business can use data mining and machine learning to make highly accurate predictions of achievements from specific marketing offers and incentives. It is possible, for instance, to follow the behavior pattern of a user during the trial window and the previous behavior of all other users to determine the likelihood of the users buying the paid version of a product. With such knowledge, marketers can put in efforts to encourage the customer to convert early or give the trial version a chance.


Machine learning can be a game-changer for a business in the current highly competitive environment. It can help to tackle various business problems such as detecting fraud, enhancing online advertising, recommending products to customers, and predicting the lifetime value of clients or the likelihood of conversion.