• Machine Learning
  • 4 MINUTES READ

Top 10 Machine Learning Applications to Unlock Business Success

  • POSTED ON
  • June 12, 2020
  • POSTED BY
  • Aayan Arif
  • POSTED ON June 12, 2020
  • POSTED BY Aayan Arif

Machine Learning is no more part of fictional stories, as it is now unlocking value and success across multiple industries and businesses. Different industry verticals are using Machine Learning (ML) technologies. Organizations are putting ML to work for their different functions, as this subset of artificial intelligence utilizes data to learn, identify patterns, and helps

Machine Learning is no more part of fictional stories, as it is now unlocking value and success across multiple industries and businesses. Different industry verticals are using Machine Learning (ML) technologies. Organizations are putting ML to work for their different functions, as this subset of artificial intelligence utilizes data to learn, identify patterns, and helps to drive multiple solutions.

Before we dive right into the applications of ML for businesses, let’s briefly go through the contemporary popular applications of Machine learning in different fields.  It is revolutionizing diverse sectors within the business of medicine, travel, business, energy, hospitality, manufacturing, and logistics.

The future world of innovations, possibilities and Machine Learning

Making the impossible possible seems to be the new mantra. But we believe in a world where we can create new and value-based innovations to serve humanity at large.

Many organizations that focus on the innovative and service-oriented side are putting ML to good use. It empowers organizations to reduce errors, increase efficiency, and drive faster and correct results. Hence businesses are using this opportunity to make their mark in the market place. Automation is good, especially when it adapts to the changing conditions in the world.

10 applications of machine learning to deliver business solutions

1.Humanized Chatbots

To bridge the communication gap, humanized Chabot agents play an integral role in allowing businesses to converse with people. These agents can take queries and requests to fulfill the demands as per request. Earlier it was just the scripted versions, but now natural language processing has allowed AI-based products to offer real-time responses. So, if you are running an online business, then you can replace traditional Chatbots with machine learning-based newer ones, who respond in a more human-like manner. It offers a clearer and more real conversation to provide the best services and attract more customers.

2. Decision Support System

This is where machine learning gives you multiple possible solutions and actionable recommendations for the business problem. You can scale up your business after running an analysis of the existing data and make decisions based on the results after evaluation. It helps businesses to make conscious and right decisions across industries.

For example, improving the healthcare system, finding solutions for climate, analyze natural resources, and their preservation. There are many management and decision support tools that can be built with the help of machine learning.

3. Customer Recommendation Engines

You can enhance the customer’s experience by providing a personalized way of buying. Your customer needs to feel special, and purchases can be made more personalized by first analyzing the data sets with ML. This allows you to recommend certain products and services to the customer based on their history. This recommendation engine technology is empowered with ML to recommend your customers with things, stuff, and products as per their needs and taste.

4. Customer Churn model: Prediction, Analysis, and Prevention

The customer churn model is used by companies with the use of Machine learning to revive their relationship with old or existing customers. Historical data, sales data, and algorithms help to identify the losses and customer-related problems. It helps a lot of businesses to avoid risks and stop their customers from leaving.

Customer churn modeling is used as an indicator for the performance of any business, and hence they can use it to increase revenue. Netflix and Amazon use ML applications for this purpose.

5. Dynamic Pricing

Businesses can equip themselves with Machine Learning to understand different pricing variables and devise dynamic pricing. Companies can maximize their profit because ML software and tools use algorithms to learn from market data and consumer information. Its simple example is evident in the transport industry and how companies strategize “demand pricing.” Uber has used that pricing strategy keeping in view the conditions in general.

 6. Research, Market Strategy and Customer Segmentation

Machine learning makes it easier for businesses to deliver the right products to the right customers. It helps in inventory management, catalog management, and customer segmentation. It predicts the strategy after analyzing data that includes customer details, region, demographics, and social media trends. Businesses gain deep insights into customer’s behavior, buying patterns, and groups of shoppers. Hence, ML identifies the needs and you can design the strategy to target the right segment.

7. Detect Fraudulent Activity

ML tools aid to identify and find anomalies and detect any kind of fraudulent activity. Its use is prevalent across industries that include finance, IT, Gaming, Travel, Education, Retail, etc. You can easily check the legitimacy of transactions and customer activity with Machine Learning. ML enables you with the power to detect doubtful behavior by analyzing tons of data within a matter of seconds.

8. Image Recognition/ Classification

Machine learning technology along with deep learning and neural networks has enabled businesses to identify and recognize images. It is used on social sites like Facebook to tag people in photos, and also it can be used for security purposes to identify criminal activities.

Retailers are using machine learning to determine the items in stock or identify any missing ones. Using this technology for scanning, purchasing, and selling to analyze the items. Organizations and companies are using their applications for workplace safety and to catch shoplifting.

9. Operational efficiencies

You can use machine learning for highly specialized organizational functions such as huge business transactions and maintenance of software development. It helps you save time, resources, and speeds up the work, resulting in more ROI.

You can use ML tools for monitoring equipment, fixing errors, and using for maintenance purposes. So, now you can avoid any unexpected disruptions at work. That’s too at much lower costs.

10. Easy Data Extraction

With the help of Machine learning and NLP, you can identify the important data and information that you need to extract from the documents and files.  It is becoming an emerging practice across industry especially when it comes to legal contracts, tax files, and invoice documents. It brings efficacy, productivity, and ensures accuracy freeing your business from the risks of “human error.” It’s understandable that you won’t need so many humans, but it’s of real value.

Create Value and profit for your Business with Machine Learning

Machine Learning can help businesses to grow their wings with an increase in profit. You can automate your operational functions, streamline databases, and use all the best tools to avoid risk. Artificial Intelligence and Machine Learning are the future of business. It adds more value to your business’s name but also enables you to create tangible profits and solutions for your business.

If you are looking to revise your business strategy or increase productivity. You can hire an AI engineer to build machine learning-based tools, apps, software, and projects. If you have any idea that been on your mind. Let’s hear and figure it out because we at vteams value knowledge and innovative ideas more than anything.

ABOUT THE AUTHOR

Aayan Arif

Content Strategist at vteams - Aayan has over 8 years of experience of working with multiple industries.

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