- Machine learning can help businesses develop software capable of understanding natural human language.
- Businesses can use machine learning to improve the efficiency of logistics and transportation networks.
- Machine learning helps businesses use preventative maintenance to decrease equipment breakdowns and increase profits.
- With machine learning, businesses can leverage consumer data to build useful customer profiles, increase sales and improve brand loyalty.
Machine learning is the most important technology for the business of the future. That's because AI-driven software is already helping companies increase efficiency, improve customer relationships, and boost sales.
Researchers estimate that machine learning has the potential to add $2.6 trillion in value to the marketing and sales industry by 2020, as well as another $2 trillion to manufacturing and logistics fields. The International Data Corporation estimates that spending on machine learning will reach $77.6 billion by 2022.
This is why companies of all sizes are collaborating with Python development outsourcing firms to source experienced data scientists as needed and develop custom data analytics software. Executives know that machine learning will soon help them increase manufacturing and logistics efficiency, improve sales, and create a better customer experience.
What exactly is machine learning?
Machine learning is an exciting new discipline that combines key parts of mathematics, statistics and artificial intelligence (AI) into a technology that is greater than the sum of its parts.
The basic premise behind artificial intelligence and machine learning is that engineers should be able to do more than write a program to carry out a specific task. They should be able to write an algorithm that can teach a computer how to write its own program.
Just as importantly, the program should be "intelligent" in a way that allows it to learn from past information and interactions. AI-driven software is capable of writing its programs, learning from past experiences, and offering proactive solutions for the future.
Businesses are using machine learning to utilize the huge amount of data that they've collected to develop actionable predictions that executives can use to invest resources and grow their company.
Here are four ways machine learning is helping businesses grow.
1. Natural language
One of the most insurmountable challenges that the tech industry has faced since its birth is creating a program that can truly understand natural language. Software has certainly improved over time – users can now type regular sentences into Google search rather than the unwieldy search terms of the past.
However, computer programs still have difficulty understanding natural language, or the type of speech that humans use day to day. Machine learning is beginning to change that.
AI-driven programs are capable of learning from past interactions and mistakes. This means that applications like search engines and voice-activated assistants are beginning to understand regular human speech enough to operate with confidence. Just as importantly, these programs improve their accuracy every day.
Voice-activated personal assistants like Google Assistant and the Nuance Intelligent Virtual Assistant are already helping executives and other professionals increase their efficiency and grow their business. They do this in several ways.
First, AI-driven personal assistants can complete many of the same tasks as administrative assistants. This includes making appointments, adding events to a calendar, booking flights and hotels, and more. They also work 24 hours a day and 365 days a year.
In addition, these personal assistants help employees save time throughout the day. For example, in the past, professionals had to manually look up historical data or crucial information. Today, executives can simply ask their assistant to recite sales numbers for a specific quarter or to provide information on interest rates.
The logistics and retail industries are rapidly becoming experts in the data analytics and machine learning fields. That's because their success is often closely tied to squeezing the last penny out of every item.
Machine learning helps companies improve their logistics through increased efficiency in every step of the shipping, storage and sales process. This technology also allows forward-thinking businesses to integrate autonomous driving into their fleets.
International shipping companies are using machine learning to increase profits. These companies are installing thousands of components on their cargo ships, long-haul trucks and smaller equipment. This helps managers identify breakdown patterns and establish preventative maintenance schedules that keep their ships and trucks in motion.
Retail companies like Amazon are also taking the lead with machine learning. The online retail giant is using machine learning to increase efficiency in its delivery network and to anticipate customer needs.
For example, Amazon created an "anticipatory shipping" protocol that allows it to predict the amount and geographic dispersion of orders for specific items before they happen. As a result, the company now sends popular items like phone accessories and household items to local distribution centers in anticipation of future purchases.
The manufacturing industry has already begun integrating machine learning technology into every stage of production.
That's because AI-driven technology can help businesses save money by streamlining inventory management, making production more efficient, and predicting equipment breakdowns before they happen.
One advantage that the manufacturing industry has is the massive amount of data generated every single day. Savvy companies like Seebo are using Python developers to create cutting-edge data analytics software. These programs use machine learning to predict annual manufacturing peaks and lull times and to suggest process improvements. They also create money-saving maintenance schedules that help companies avoid unplanned shutdowns.
McKinsey predicts that machine learning will help manufacturing businesses reduce material delivery times by 30% and achieve 12% fuel savings by optimizing their processes. The firm also estimates that companies can increase gross revenue by 13% if they fully integrate AI-driven technologies into their business.
The consulting firm Deloitte also calculates that machine learning can save companies millions of dollars through preventative maintenance. Deloitte estimates AI-driven programs can help businesses reduce unplanned downtime by 15% to 30% and reduced maintenance costs by 20% to 30%.
4. Consumer data
Executives are most excited to see how the rising collection and analysis of consumer data will impact profits and future growth. Businesses have spent the past several decades collecting billions of data points on their customers, including information like shopping habits, demographic identifiers, income and more.
AI-driven software is finally letting these companies utilize this data. Executives are collaborating with Python software development companies to build state-of-the-art data analytics software that can collect information and generate useful and actionable predictions.
For example, the online retail marketplace Etsy uses machine learning to improve its customer experience. The company utilized the technology to create individualized customer profiles, to improve search results and improve the user design.
The company's innovative use of data analytics is one reason why the company has reached annual revenues of $603 million while facing stiff competition from larger retail companies like Amazon and Target.
Netflix is another company that has used AI-driven technology successfully. The online streaming platform uses machine learning to build extensive view profiles that accurately predict which shows and movies users will be interested in. Customers interact with this program and provide useful data every time they scroll through new films.
Machine learning is helping businesses increase sales and plan for the future. That's one reason why companies of all sizes have begun collaborating with Python web development companies to find experienced data scientists and to build software that promotes growth through technology.
AI-driven software is already being used to increase efficiency and boost sales in the manufacturing and logistics industries. In addition, retail companies are working with Python development services to build custom software that analyzes consumer data to improve sales and increase customer loyalty.
Finally, developments in natural language are expected to have a major impact on consumer devices and businesses alike. AI-driven personal assistants are already helping corporate employees save time and increase the quality of their work.