How Companies Use Machine Learning

Day-by-day Machine Learning is becoming popular among industries, and business owners have finally started to believe that it can bring a colossal change in their business’s efficiency. Many experts say that Machine Learning is a breakthrough as big as the internet and the personal computer. Since the past decade, people have started to learn about ML and understand what it can bring to the table when implemented in their business. ML is not a completely flourished technology, but people are giving it a chance because it can provide a huge boost to their businesses. Still, a large number of audiences are not aware of what Machine Learning actually is even though they have been using it for the past 5 years in the form of Siri, Cortona, Google Maps, and even the recommendations while shopping online. A lot of businesses are still figuring out the application area of ML in their business. Even if they want to implement ML in their business, they are not completely educated about the process of ML adoption.

The need for ML is seen by organizations and these are the points that assure us on why they are ready to adopt this technology:

1. Growing Data and Cheaper Storage

The growth of cloud computing has provided one important thing, which is the storage function. Data generated by organizations is huge and to store it in a safer manner is an important decision. ML makes use of data for deriving decisions and when data is stored in the cloud, it is easier to refer the data for analytics purposes. As the service offered by cloud computing is cheap, organizations use cloud services for their data storage needs as it provided optimum security and accessibility through remote locations.

2. Data Libraries

Data libraries are open to everyone and they also provide cutting-edge algorithms to data scientists who make use of an organizations data to analyze upcoming opportunities.

3. High-End Platform

Cloud technology is one such platform that provides powerful hardware and customization options that can be highly suitable for ML algorithms. Due to powerful processing capabilities, ML on the cloud can be a good match for any organization.

These are some of the basic points that drive an organization’s decision towards the adoption of ML in their businesses.

Further, we will see how companies use ML in their day-to-day business functions to get the most out of their investments. I will shed lights on the below points which are important while using ML:

1. Intelligently Acquiring Customers

Anyone will agree with how vital it is to acquire new customers because every business needs a huge customer base. To acquire new customers, there are three steps to go forward with which are; understanding the need of the audience, engaging them with your products and services and finally converting them into your customer. ML algorithms make use of such customer data and recommend the suitable prospects who can potentially become your customers. For example, Amazon’s website uses Machine Learning to recommend products to their website visitors while they are searching for a similar product. Here, ML understands the customer’s choices and recommends products accordingly. The customer is kept engaged and there is a good chance that he/she will purchase a certain product.

2. Top-Level Customer Support

Serving a customer does not end after the sale is made but the real support starts after the sale is made. The problem faced by many companies is that they are not able to retain many of their customers due to a lack of support when their customer was facing certain issues with the product or a service. An organization gains the trust of a customer only when they have helped him/her through the problematic phase and provided them with an optimum solution. With ML in the scene now, users are managed and supported way more efficiently than ever before due to fast problem-solving time and handling multiple queries at once. High-level solutions are provided to the customers through chatbots which have proved beneficial for the organization by keeping the trust and customer retention intact.

3. Business Forecasting

Every owner forecasts multiple areas in his/her business which gives an idea about the needs which can arise in the future. To anticipate situations which are unplanned, organizations stay one step ahead to predict outcomes. Through the help of ML, forecasting can be made easy in order to be prepared for any uncertain demands which might arise. Inventory and sales are the two most important examples which are predicted in order to never fall short supply. Sales performance can be tracked through forecasting by ML integration.

4. Managing People

To hire the right person for the right profile is being taken care by the Human Resources but they can take help of ML to find the right candidates for the right job by past hiring decisions, resumes and job description. There can be human errors in any field and HR is not an exception and that’s why ML can track the precise candidates which were overlooked by the HR in the first place.

Conclusion

Organizations are already hugely benefiting from implementing Machine Learning in their businesses. Many processes have improved through the expertise of this technology. In the future we hope that ML algorithms upgrade and help in each and every department of the company.