Machine learning (ML) is the method a software application uses to actively learn from imported data sets, using it similar to the way a human would as part of their learning process. Machine learning has become popularly adopted across the world and many businesses have already included ML in their sales and marketing efforts. This is due to the close ties ML has with data mining and predictive modeling.
Meanwhile, Business intelligence (BI) deals with the processes that rely on technology to acquire, store and analyze business-related data. The aim of BI is to help businesses make better data-driven decisions and it deals with several different aspects like analytics, predictive modeling, performance management, data mining etc.
When dealing with processing large amounts of data, machines are capable of doing far more than humans. This makes ML an ideal and potent tool which BI can potentially greatly benefit from.
Boosting Sales and Marketing
There are a lot of insights a business can gain from a (potential) customer’s online purchasing behavior. ML allows businesses to get a poignant understanding of their target audience and their needs, thus providing businesses with valuable insights that can be utilized to boost sales or change their marketing strategy.
The data used by businesses is usually collected from personal profiles(browsing searches, realized purchases, personal details) is extremely valuable and powerful information that a company can use to predict, for example, the impact of a new product in the market, elements to consider when making a new product, what the customer needs are and even how the product should look.
Improving Employee Safety
ML also improves employee safety, providing protection or replacing individuals working in high-risk environments. High-level monitoring working together with predictive analysis can help prevent malfunctions or system failures that can potentially endanger lives or even avoid accidents before they occur. Using data, ML can even understand and remember the causes that led to previous malfunctions. This ability to identify potential threats and risks in a timely manner greatly benefits businesses in the long term as both, humans as well as business systems and infrastructure are kept safe.
Enhancing Customer Experience and Loyalty
ML also creates a significant and meaningful impact on customer experience. Businesses want to reach more people and gain their purchasing loyalty and many use ML to help in the process. For example, information users leave on social media sites can be collected and analyzed using ML. ML applications create personalized and customized sponsored posts and ad suggestions to the user based on their age, gender, location and this behavioral history on the platform.
Customer service predictions made by ML are also commonly used in hospitals and clinics: analyzing information about ER layout, department charts, staff information, patient data as well as the wait for the emergency rooms can all be predicted accurately.
Streamlining Operational Processes
Let’s look at a few business processes that have already been considerably improved by the application of ML processes.
- Managing customer service,
- Managing risks and compliance,
- Managing financial resources,
- Developing and managing business capabilities, and
- Marketing and selling products and services.
ML has the ability to store and use data collected from every aspect of the business. This allows it to create successful pathways for automation for many business processes and workflows. This is commonly known as intelligent IT automation.
One of the most vital aspects of ML is the ability to streamline operational processes. Using intelligent IT automation, businesses can boost productivity massively and this is why many businesses consider implementing machine learning.
What was once vague and futuristic, AI and machine learning are now, fast-developing technological tools that are capable of carrying out numerous processes that we can encounter on a daily basis. From making suggestions of friends on social media to refining search engine results, suggesting product recommendations to filtering emails, machine learning has become an increasingly active part of our lives. Businesses have already improved many BI processes using ML and it is expected to become even more potent as the technology evolves further.