How AI and Machine Learning Can Help Businesses in 2020 | Comidor Platform

How AI and Machine Learning Can Help Businesses in 2020

790 527 Comidor BPM Platform

Artificial Intelligence (AI) is at the core of the current technological revolution. From Machine Learning to neural networks, a host of techniques associated with AI is changing our world, profoundly impacting every industry and forever altering every area of human endeavor. 

Many believe AI and Machine Learning are the things of the future and still belong solely to the realm of science fiction. Well, they couldn’t be more wrong. AI is here, and it is here to stay. It allows businesses to improve their bottom lines and users to have a more enjoyable experience.  

What is Artificial Intelligence?

But, what exactly is AI? Essentially, what we call AI is a set of technologies that seek to teach machines to think like humans. In the early days, AI technology relied on hard-cord rules and algorithms. When you played chess against a computer, it decided by looking ahead at every possible series of moves and choosing the one with the best outcome. A person had to enter those moves ahead of time. This type of AI seemed intelligent, but it could not learn based on its own experience.  

What is Machine Learning?

Machine Learning turned that on its head. Instead of relying on rules to make decisions, a Machine Learning algorithm is trained by real-world data. It creates a model that looks for patterns between the data you supply and what you are try to predict. As it gathers more and more information, the algorithm’s accuracy invariably improves, reaching the point where it can predict things it has never seen before.  

And then, deep learning came around. A subset of machine learning, deep learning is inspired by human brains and has attracted attention due to its flexibility. But how do businesses apply these technologies? Let’s explore some of the ways AI and Machine Learning Engineers can help companies. 

Predicting Consumer Behavior with AI and Machine Learning

To get an idea of how AI is changing the world, look at the evolution of the e-commerce and retail industries. In a matter of years, shopping online has gone from mere novelty to an indispensable part of everyday life.  Thus, the e-commerce industry has grown into a multi-billion dollar industry.  

 This has been undoubtedly enabled by the rise of predictive marketing, a technique that uses data analytics to determine the best way to reach customers and strategies with the highest probability of succeeding. Predictive marketing occupies a vital place in the marketing technology landscape. 

It uses Big Data technologies to find patterns in consumer behavior that can be exploited to predict outcomes and trends. Companies can use the unique consumer insights to improve customer engagement and increase revenue. In short, it takes much of the guesswork out of marketing and empowers companies to conduct more accurate forecasting. 

 Businesses can also gain more sophisticated segmentation of data, identify campaigns and actions that are better targeted to customers, use marketing budgets more efficiently, and improve lead scoring.  

Many world’s leading e-commerce firms use predictive marketing in a myriad of ways. These firms use potent algorithms based on AI tech to predict consumer behavior accurately. These algorithms tell them what you want to buy even before you know it; they can then sell it to you with a personalized ad.   

Personalized Ads & Targeted Campaigns

This is a lot of information, so one way to pack it up all neatly and use it in concrete strategies is to cluster it into groups, what we call ‘data clustering.’ Data clustering helps businesses, separate potential customers, into distinct groups that can be targeted differently—the people in one group all share the same purchasing patterns.  

 Audience clustering improves how brands position themselves. By grouping consumers with similar psychometric, demographic, geographic, or socio-economic attributes, advertisers can enhance the flexibility and relevance of their marketing efforts. Furthermore, clustering is a highly versatile technique—algorithms can continuously update a given group with new relevant users. 

 According to a Boston Consulting Group report, retailers who use Machine Learning for personalization have seen sales increases of up to 10% compared to companies that do not employ these techniques. 

Online businesses can also use Machine Learning to implement dynamic pricing. Through this technique, companies can change and readjust prices by taking into account various factors all at once. These factors can be competitor pricing, product demand, and day of the week. 

 The next generation of marketing instruments is being powered by deep learning too. Deep learning enables machines to perform high-level thought and abstraction, including image recognition. The technique mimics the way that the human brain functions, using deep neural networks in which data is passed along. These networks adapt according to the information they are processing and make the necessary adjustments to become more efficient. 

This technique allows marketing professionals to improve ad personalization and conduct complex brand sentiment analysis. It is also behind applications like audience clustering and predictive marketing. 

bpm live comidor webinar on-demand | Comidor Digital Automation Platform

How do AI and Machine Learning Improve Customer Support

Businesses can also use these techniques to improve the customer experience

Companies can develop an AI platform and behavioral models to interpret human communication and detect psychological states automatically. Solutions like these can deliver in-call behavioral guidance to agents and a real-time measure of customer perception for every phone conversation. 

Conversational AI, more commonly known as chatbots, is another technology that is vastly improving the customer experience. Chatbots allow retailers to quickly and efficiently answer customers’ questions, doubts and problems.  

These chatbots are saving companies millions of dollars in salaries by allowing firms to reduce their staff. At the same time, they improve customer service and create a more personalized experience for visitors to their website. 

Other AI applications in the business world include personalizing online interfaces, tailoring product recommendations, and increasing search relevance.

Conclusion

As AI continues to evolve and its benefits become more evident, more and more companies are investing money in making machines think like humans.  

If you are interested in becoming an AI and Machine Learning Engineer, an excellent way of getting your foot in the door is to attend a coding Bootcamp, from Career Karma.

comidor blog | Comidor Platform

Are you interested in learning more about Artificial Intelligence?

Artificial Intelligence (AI) is at the core of the current technological revolution. From Machine Learning to neural networks, a host of techniques associated with AI is changing our world, profoundly impacting every industry and forever altering every area of human endeavor. 

Many believe AI and Machine Learning are the things of the future and still belong solely to the realm of science fiction. Well, they couldn’t be more wrong. AI is here, and it is here to stay. It allows businesses to improve their bottom lines and users to have a more enjoyable experience.  

What is Artificial Intelligence?

But, what exactly is AI? Essentially, what we call AI is a set of technologies that seek to teach machines to think like humans. In the early days, AI technology relied on hard-cord rules and algorithms. When you played chess against a computer, it decided by looking ahead at every possible series of moves and choosing the one with the best outcome. A person had to enter those moves ahead of time. This type of AI seemed intelligent, but it could not learn based on its own experience.  

What is Machine Learning?

Machine Learning turned that on its head. Instead of relying on rules to make decisions, a Machine Learning algorithm is trained by real-world data. It creates a model that looks for patterns between the data you supply and what you are try to predict. As it gathers more and more information, the algorithm’s accuracy invariably improves, reaching the point where it can predict things it has never seen before.  

And then, deep learning came around. A subset of machine learning, deep learning is inspired by human brains and has attracted attention due to its flexibility. But how do businesses apply these technologies? Let’s explore some of the ways AI and Machine Learning Engineers can help companies. 

Predicting Consumer Behavior with AI and Machine Learning

To get an idea of how AI is changing the world, look at the evolution of the e-commerce and retail industries. In a matter of years, shopping online has gone from mere novelty to an indispensable part of everyday life.  Thus, the e-commerce industry has grown into a multi-billion dollar industry.  

 This has been undoubtedly enabled by the rise of predictive marketing, a technique that uses data analytics to determine the best way to reach customers and strategies with the highest probability of succeeding. Predictive marketing occupies a vital place in the marketing technology landscape. 

It uses Big Data technologies to find patterns in consumer behavior that can be exploited to predict outcomes and trends. Companies can use the unique consumer insights to improve customer engagement and increase revenue. In short, it takes much of the guesswork out of marketing and empowers companies to conduct more accurate forecasting. 

 Businesses can also gain more sophisticated segmentation of data, identify campaigns and actions that are better targeted to customers, use marketing budgets more efficiently, and improve lead scoring.  

Many world’s leading e-commerce firms use predictive marketing in a myriad of ways. These firms use potent algorithms based on AI tech to predict consumer behavior accurately. These algorithms tell them what you want to buy even before you know it; they can then sell it to you with a personalized ad.   

Personalized Ads & Targeted Campaigns

This is a lot of information, so one way to pack it up all neatly and use it in concrete strategies is to cluster it into groups, what we call ‘data clustering.’ Data clustering helps businesses, separate potential customers, into distinct groups that can be targeted differently—the people in one group all share the same purchasing patterns.  

 Audience clustering improves how brands position themselves. By grouping consumers with similar psychometric, demographic, geographic, or socio-economic attributes, advertisers can enhance the flexibility and relevance of their marketing efforts. Furthermore, clustering is a highly versatile technique—algorithms can continuously update a given group with new relevant users. 

 According to a Boston Consulting Group report, retailers who use Machine Learning for personalization have seen sales increases of up to 10% compared to companies that do not employ these techniques. 

Online businesses can also use Machine Learning to implement dynamic pricing. Through this technique, companies can change and readjust prices by taking into account various factors all at once. These factors can be competitor pricing, product demand, and day of the week. 

 The next generation of marketing instruments is being powered by deep learning too. Deep learning enables machines to perform high-level thought and abstraction, including image recognition. The technique mimics the way that the human brain functions, using deep neural networks in which data is passed along. These networks adapt according to the information they are processing and make the necessary adjustments to become more efficient. 

This technique allows marketing professionals to improve ad personalization and conduct complex brand sentiment analysis. It is also behind applications like audience clustering and predictive marketing. 

bpm live comidor webinar on-demand | Comidor Digital Automation Platform

How do AI and Machine Learning Improve Customer Support

Businesses can also use these techniques to improve the customer experience

Companies can develop an AI platform and behavioral models to interpret human communication and detect psychological states automatically. Solutions like these can deliver in-call behavioral guidance to agents and a real-time measure of customer perception for every phone conversation. 

Conversational AI, more commonly known as chatbots, is another technology that is vastly improving the customer experience. Chatbots allow retailers to quickly and efficiently answer customers’ questions, doubts and problems.  

These chatbots are saving companies millions of dollars in salaries by allowing firms to reduce their staff. At the same time, they improve customer service and create a more personalized experience for visitors to their website. 

Other AI applications in the business world include personalizing online interfaces, tailoring product recommendations, and increasing search relevance.

Conclusion

As AI continues to evolve and its benefits become more evident, more and more companies are investing money in making machines think like humans.  

If you are interested in becoming an AI and Machine Learning Engineer, an excellent way of getting your foot in the door is to attend a coding Bootcamp, from Career Karma.

comidor blog | Comidor Platform

Are you interested in learning more about Artificial Intelligence?