Artificial Intelligence and Machine Learning ceases to be a miracle of science fiction and gradually becomes a part of our daily life. However, lots of us still do not fully understand what Machine Learning is and why it is so important.
What is Machine Learning?
Machine Learning is a process in which the system processes a large number of homogeneous information, identifies patterns and uses them to predict the characteristics of new data. It is the idea of the existence of common algorithms that can tell us something interesting about the data set without having to write a code specific for the problem. Instead of writing the code, you pass the data to a common algorithm, and it builds its own logic based on them.
The main thing here is an algorithm. The algorithm decides what to show you first in your search results; when you buying something the algorithm set the most appropriate price for you; when you are using ATM the algorithm is controlling your transactions or fraud, etc.
This algorithm is built by collecting a huge amount of data, then professional write a code which makes the selection of necessary data and separating irrelevant information.
Advantages of Machine Learning
Get information faster. With the help of Machine Learning, you can get complete necessary information about products and the audience faster. Forming a strategy and deciding on which target audience to produce specific proposals much faster and more efficiently.
Avoiding risks. Business is always a high risk. Machine Learning can make decisions by analyzing the information without emotions and manual work, minimizing possible risks.
Strategies that win. Machine Learning is able to build the most profitable and effective strategy without long and expensive marketing analysis made by employees.
Accelerating decision-making. Learning algorithms can determine priorities and automate decision-making process. They can also indicate opportunities and prompt actions that need to be taken immediately to achieve the best result.
Deeper analytics. The technology can analyze large, complex and streaming data, finding valuable, predictive information, which human intellect is not capable of achieving. Analytical results can be successfully used for further operations and strategies.
Efficiency. Intellectual business processes based on Machine Learning can significantly improve efficiency. Make accurate plans and forecasts, automate tasks, reduce costs and eliminate errors related to the “human factor”.
The efficiency of work is the key to success of any business. Assigning tasks and distributing responsibilities will become much easier with the help of Machine Learning. The learning algorithm is also affecting the work performance, raising it to a new level, for a number of reasons:
· Machine Learning does not have emotions;
· The calculation is based on a mathematical formula;
· All the possibilities are translated into numbers;
· Responsibilities and tasks are distributed based on the analysis of the employee’s potential and minimization of risks.
Examples of using machine learning for business:
Making advertisement better. Machine algorithm can learn to recognize areas of users’ interest. Feedback forms and the content on the landing page, which fully corresponds to the user’s request can be improved with the help of Machine Learning. It will give the possibility to leave forms of feedback aside and to show the user only those content blocks that are most relevant to his query. That will significantly increase the conversion of the marketing campaign.
With the help of self-learning algorithms, it can be determined which content is unusable and which is valuable. This information will filter content in the future.
For example, Pinterest, already uses Machine Learning, to present more interesting content. Yelp uses the Machine Learning algorithms to sort users’ photos.
Accelerating the search process. The ability to select the most relevant result is one of the advantages of Machine Learning. The company Home Depot offers their users smart results, for example, when they need to pick up an ideal bath for the bathroom. The same way goes Apple, showing relevant applications in the App store.
Successful e-commerce startups, like Lyst and Trunk Archive, use Machine Learning to show high-quality production content to their users.
Understanding customer behavior
The use of Machine Learning in the analysis of emotional coloring of utterances is growing. It’s not a secret that a work with public opinion is very important in marketing. Machine Learning is able to analyze information from social networks, history of user orders and search queries in the search engine and, as a result, predict the client’s desires and offer him only the necessary information.
Machine Learning methods are often used to predict events in a client database. Nowadays, for example, insurance companies use Machine Learning to predict which of the clients will soon seek expensive medical care. Having such a forecast, the company pre-connects with “high-risk” customers and takes preventive measures: for example, offers to undergo a client’s medical examination or arrange a consultation with a more qualified doctor. Clients start to receive in advance the qualified help, without waiting for an acute phase of illness. In such a way the insurance company reduced expenses on for hundreds of thousands of dollars a month!
Selling systems for online stores. Sales department solves the task of analyzing user’s behavior and his purchases on the website, offering him additional products, which he is more likely to buy. A program on the basis of Machine Learning uses an algorithm that analyzes a huge amount of data about purchases in various online stores. Then the result produces fairly accurate predictions for new customers. Practice shows that a good system of recommendations can ensure revenue growth of the online store to 50%.
Machine Learning allows to optimally organize the supply of goods to retail chains. Self-learning systems help network retailers to create an order for the supply of some kind of goods to the stores of the network. The program takes into account the dynamics of sales, weather forecast, season and other factors, allowing to avoid overstocking or, conversely, shortage of goods in the store.
Learning programs effectively address the tasks of not only forecasting but also segmentation. The most understandable example is the search for clients. The companies use ML for client segmentation from the huge database. They took customers who recently ordered some kind of service and based on this data, using methods of Machine Learning, then identify the entire clients’ database the possible buyers of this service. Such smart segmentation allows reducing the cost of cold calls.
Artificial Intelligence has totally changed the working process. It’s hard to be successful without modern technologies today. Almost every business industry can benefit from Machine Learning. It can provide customer service, forecasting, fraud detection, and even recruitment. Learn more how to help your business to grow with us.
Source: Deep Learning on Medium