Why Every Business Should Use Machine Learning?

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benefits of machine learning

In just 2018, the total number of deals related to machine learning 91 with a business of $16.9 billion as a whole. From the organization’s point of view, 76% of total leaders from one survey accepted that they got higher sales growth just because of using machine learning for predicting user behavior and preferences. As of now, some of the banks from Europe have already implemented machine learning which improved their sales by 10% and decreased the churn by 20%.

These are the reasons why machine learning is of great interest to businesses, organizations and the corporate world. In any organization, from executives to managers to CEOs have to find their own use of machine learning. Employees at lower positions are using to understand the pattern of their customers while a person at higher positions is using it for taking the crucial decisions.

Importance of New Data & Data Cleaning for ML in Businesses

Data Science

The most common phrase among the data scientists is “Clean data is better than big data”. If you have a collection of huge business data from years ago, then probably today, it wouldn’t have any relevance, especially, if your business involves the processes which significantly change with time. One of the most classic examples for this type of business is mobile e-commerce industry. Even if you are not belonging to the same industry and have the pool of disjointed and unstructured data then also, you might end up with too much data cleaning which can waste your valuable time. 

Always remember that in a field that changes significantly, newer data becomes very essential. For instance, suppose you are running a door to door delivery service for home supplies then your prices, app, service areas and product offerings might have changed drastically in just the past six months. In these types of cases, the need for more recent data becomes very essential to learning from and getting valuable insights for making the predictions.

Read More: Python Programming For Data Science And Machine Learning 

Major Benefits of Machine Learning for Business

As now it is clearly understood that machine learning helps in extracting clear, precise and meaningful information from large datasets. If implemented correctly, machine learning can be the game-changer for a variety of businesses by providing solutions to their complex problems. Also, along with other organizations, some major tech giants like Microsoft, Google, Amazon, IBM and others are already using it for their own interests. Some of the essential ways by which it can help your businesses are as follows:

1. Customer Lifetime Value Prediction

Customer segmentation and their lifetime value prediction are the major challenges that marketers from all the generations have faced. Today, the majority of the companies or organizations have access to a huge amount of data that can be used effectively for deriving insights that are precise and meaningful. Data learning and machine learning can help businesses to predict their customer’s purchasing patterns by analyzing their behavior which will help in sending best and relevant offers as per each customer. It can be totally based on their purchase histories and browsing the products.

2. Detecting Spam

For quite some time, experts are using machine learning for detecting spams. Earlier, email service providers were using pre-existing rule-based techniques for filtering all the spams. Now spam filters are responsible for creating new rules which use neural networks for detecting phishing messages and spams.

3. Eliminating Manual Data Entry

Machine Learning

Thanks to the advancement in machine learning, now the most time-consuming and boring job of manual data entry are now automated. Earlier, inaccurate and duplicate date were some of the biggest problems which businesses used to face. But with machine learning algorithms, these processes can now be made better by using discovered data which allows employees to focus more on carrying tasks that add value to their business.

4. Predictive Maintenance

Often manufacturing firms are required to follow corrective and preventive maintenance practices, which are more inefficient as well as expensive. But by using machine learning, now these firms can discover meaningful patterns and insights hidden in their factory data. It is also called predictive maintenance. This helps in reducing the risk related to unexpected failures along with eliminating the unnecessary expenses. For this purpose, machine learning architecture can be easily built by using historical data, a flexible analysis environment, a feedback loop and a workflow visualization tool.

5. Financial Analysis

Now machine learning can also be used for financial analysis because of the large volumes of accurate and quantitative historical data. Already people are using ML-based algorithms in finance for algorithmic trading, portfolio management, fraud detection and loan underwriting. However, in the near future, machine learning promises more advanced applications in finance sectors such as chatbots, customer service, sentiment analysis and other conversational interfaces for security.

6. Image Recognition

Face Recognition

Image recognition is also known as the computer vision and it has the capability for producing symbolic and numeric information from images or any other high-dimensional data. This involves machine learning, data mining, pattern recognition and database knowledge discovery. Here, machine learning plays a very crucial role and is used by numerous companies from various industries including automobiles, healthcare and others.

Read More: Deepfake- The Black Mirrorish Application of AI

7. Product Recommendations

For developing product-based recommendation systems, unsupervised learning can be used. Today, a majority of the websites are already using machine learning for making precise product recommendations. For this purpose, a customer’s purchase history can be used by machine learning algorithms which then matches it with the product inventory for identifying the hidden patterns. It then groups similar products together which is suggested to the customers ultimately, motivating them to purchase it.

8. Medical Diagnosis

Even for the medical diagnosis, machine learning has become effective by helping organizations for improving the patient’s health. Moreover, it also plays a crucial role in minimizing the healthcare costs, effective treatment and usage of superior diagnostic tools. 

Machine learning is used by several organizations and hospitals for making a near-perfect diagnosis, recommending the right and effective medicines, identifying high-risk patients and predicting readmissions. All these predictions are made using datasets and the patient’s records along with the patient’s symptoms.

Read More: Current Scenario of Machine Learning in Healthcare

9. Improving Cybersecurity

With the rise of technology and the data, cybercrime has become one of the major threats to humankind. For this, experts are using machine learning for solving and increasing the security of different organizations. Machine learning is now become essential for building the latest technologies that have the potential to effectively and quickly detect unknown threats.

10. Increasing Customer Satisfaction

Machine learning is now used for ensuring customer experience which ultimately improves customer loyalty. It is achieved by analyzing the customer’s behavior by using previous call records. It helps in assigning the most suitable customer service executive as per the client requirements which reduces cost and time invested in managing customer relationships significantly. 

Read More: 10 Ways to Grow Businesses By Integrating AI

Various Companies Using Machine Learning in Cool Ways

Machine learning for business improvement

Pinterest- for improved content delivery

Whether you’re using Pinterest for years or just starting, it is one of the most curious social platforms ever created. As Pinterest’s primary goal is of curating content which already exists, it always invests in the technologies which make this process more advanced, precise and effective. 

It was the year 2015 when this company bought another company called Kosei which specializes in the using of machine learning technology for commercial purposes. To be specific, it more focusses on algorithms’ recommendation accurate content delivery.

pinterest

Fast-forwarding to the current situation, you can find almost all the aspect of Pinterest is based on the applications related to machine learning technology. From content delivery to business operations to spam moderation, everything revolves around machine learning. Not only these but even reducing the churn of email newsletter subscriber and advertisement monetization also based on machine learning.

Yelp- curating image at scale

Yelp LOGO

The main reason behind Yelp popularity and usefulness is that it not just gives reviews to businesses or restaurant but also let you compare than just complaining about it online. Though, it’s not a purely technology-based company but is still using machine learning for improving their user’s experience.

For Yelp, images are equally important than the reviews given by the users. Because of this, it is no surprise that they are always ready to explore different technologies for handling image processing. And due to this reason, they turned towards machine learning for picture classification technology. Machine learning algorithms that Yelp are using help their employees to categorize, label and compile images more efficiently which initially can take a lot of valuable time considering millions of images.

Facebook- a company looking for creating a chatbot army

TipsforStayingaheadofYourCompetitiononFacebook

Though Facebook’s Messenger is still highly debated and questioned, it is one of the most crucial parts of the world’s biggest social media channel. Many believe it’s largely because of the Facebook decision-makers have decided to make it a testing product for chatbots.

Facebook Messenger lets any developer make and submit their chatbot for its inclusion in the same platform. For sure, that is not the only application of machine learning in which Facebook is currently showing their interest. Other machine learning applications like computer vision algorithms with the capabilities of reading images for the visually challenged humans and filtering the poor content or spam are other things which are currently at high focus behind the Facebook management.

Twitter- for curating timelines

Twitter Campaign

It is another social media platform that has raised several eyebrows and was in the center of various famous controversies around the world. But recently, the major change which all its users have observed was the fact that Twitter moved toward an algorithmic-based feed.

Whether you want Twitter to display your timeline in chronological order or the best tweets, all are because of its machine learning technology. The AI used by Twitter evaluates and scores each tweet in real-time as per the various set criteria. This results in displaying the tweets which are expected to attract high engagement. Moreover, this process is performed on an individual basis. Isn’t it amazing? Its machine learning algorithm makes all these decisions based on every single user’s preferences. 

Google- a neural network for creating machines that can dream

google

All of those who show their interest in Google already know that it is one company that has shown its interest in artificial intelligence and machine learning since the dawn of this technology. Its ambitious projects like medical devices, neural networks or anti-aging technology, all revolve around AI and machine learning.

As of now, the most remarkable work by Google involving machine learning is its research in the neural network for developing DeepMind Network i.e. making the machine that can dream. As per Google, the company is also researching various other aspects of machine learning which focuses on different applications like speech translation, search ranking, natural language processing and prediction systems.

Edgecase- efficiently improving eCommerce conversion rates

edgecase.ai-logo

Check every single page of Ecommerce history, you’ll find that most of the time retailers have struggled to find the difference between shopping online and shopping in stores. This is the reason, numerous Ecommerce websites are still performing poorly despite having all the advanced technology.

Here Edgecase which was formerly called Compare Metrics has come to rescue with its promising machine learning algorithm which can help eCommerce retailers to provide an improved and effective user experience.

Moreover, this company also promises to streamline the whole eCommerce experience which will improve the conversion rates. It will be possible by analyzing certain actions and behaviors of the customers which will give a clear picture of a customer’s intent. In simple words, it will transform the user’s casual online browsing into the more traditional retail experience.

Baidu- for the effective voice search

Baidu-logo

Google is not the solo player in the search industry which is exploring the world of machine learning. Another search giant from China called Baidu is also pouring its money heavily in this technology. Because of this, their R &D labs have now successfully created something called Deep Voice which is considered as one of the most interesting applications of machine learning.

Deep Voice is the application which uses deep neural network for generating completely synthetic human voice which cannot be distinguished from any genuine human speech. Their network has the ability to learn the complex subtleties of human voice such as accent, pitch, cadence and pronunciation for creating unimaginable precise voices. Now, its latest technology called Deep Voice 2 is already being implemented for various voice search applications, biometric security and real-time translations.

HubSpot- making smarter sales

hubspot

It is one of the few companies which always had an eye for modern and emerging technologies. This theory has been again proved by HubSpot when they choose to acquire a machine learning firm called Kemvi. 

As per their plans, they are ready-to-use Kemvi’s machine learning technology for different applications like DeepGraph machine learning and NLP for its CMS or content management system. It will help HubSpot to effectively pitch prospective clients and serving existing customers.

IBM- an initiative towards a better health

IBM Story- featured image

The inclusion of this tech giant form this list might have seems a little strange to our various readers. Without any debate, IBM is one of the biggest and oldest technology-based companies that has always moved from its older business models to the newer ones. The latest IBM product based on AI & ML called “Watson” is one of its biggest examples.

Recently, this technology has already been deployed in numerous hospitals and medical centers for making super precise recommendations for treating different types of cancers. Not only this, but Watson also showed its huge potential in the retail market. It can help both healthcare industry along with the shoppers. 

Read More: Artificial Intelligence Vs Business Intelligence

Wrapping It Up!

With the above list on the different businesses which are using machine learning, we will summarize this article. Indeed, machine learning is essential for many fields, but don’t forget, like any other thing on this planet, it also has certain cons. Nevertheless, that’s a discussion of later. So don’t forget to tell your views on the same topic and do mention the companies which we might have left out from this list.

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