There has been a huge advancement in the incorporation of Artificial Intelligence (AI) technology by various industries and institutions. Sectors such as health, construction, agriculture, and business are the frontier institutions embracing the new technology. The awareness of how this technology augments productivity and reduces the cost of operation is the major reason behind its acceptance globally.
Nowadays, AI is easily integrated into different tech devices to enhance their functionality. Even human communication has become more effective with the assistance of AI. According to a 2021 Truelist statistic,
The desire of many businesses to grow rapidly, increase their level of productivity and make more profits brought about the embracement of machine learning (ML), which is a subset of AI.
Machine learning (ML) technology emerged to produce humans with precise information, analysis, and prediction of outcomes of any task with the help of data. ML is a unique form of technology that allows computer systems – AI software – to learn, adapt, improve, and produce results without following explicit instructions.
In other words, ML can be described as a kind of AI technology capable of functioning and making decisions on its own without taking human instructions.
ML makes use of algorithms to process and analyze data and draw inferences. There are two major types of algorithms used by ML, these are Supervised Learning and Unsupervised Learning.
So many companies are keen on leveraging ML in their operation. Since their major focus has always been on how to make more profit, create more connections, attract more consumers, and stay above their competitors. Fortunately, these areas of business are best executed by ML.
Starting with how to gain customers, ML is being used by many businesses to analyze and predict the behaviors of their consumers; observing what they would like to buy, what will interest them most, and their financial strength.
Knowing how these factors influence the behavior of consumers is significant for any business that is ready to make sales. Another important focus of any business should also be fixed on understanding its consumer buying power.
The agenda of every business is to sell its products to the targeted audience and ensure the retention of such consumers for future patronage. To make sales, businesses focus on how they can present their products to the audience by hitting on their pain point. A sure way of achieving this goal is through observation of consumer buying power.
Consumer buying power can be assessed through socio-economic factors like inflation and recession in the consumers’ lives. Sales & marketing agents of many businesses fail a lot to observe the buying power of their consumers, and that affects their business sales and patronage.
According to Statista, the market value of AI/ML applications in enterprises between 2016-2025 is
Below are ways ML helps businesses and organizations grow and predict their consumer behavior:
Occasionally, businesses experience short patronage from their regular customers. The abrupt withdrawal of customers from purchasing a product or patronizing a service can be because of the hike in the price of the product, or maybe the customers are tired of the brand and want something else.
ML can help your company/business analyze the data of your customers and give insight into why some of them may stop patronizing your products and what you can do to retain those customers. If the issue is about the price of a product, the company can roll out discount offers to boost the interest of those customers from walking away.
ML also helps companies and businesses to examine the dynamic nature of the market and make suggestions on how your brand/products can be improved — by having flexible prices that consumers can afford — to defeat your competitors in the business.
It’s mostly hard for many businesses to determine what could interest a targeted audience to patronize their brand at first approach. That’s because careful observation of each consumer to learn about their preferences is needed. But ML enables data scientists to utilize classification algorithms to divide the consumers into personas-based specifications.
ML algorithms help in regrouping consumers based on their demographics, browsing history, and affinity, which enables businesses to tailor-out products & services that best suit the interests of consumers.
Machine learning also helps businesses to analyze the lifetime value of customers through the history of purchases they have made in the past. ML can help a business or company predict the amount of money a consumer can spend patronizing their brand.
This gives the business or company an overview of what it should be expecting from each consumer, and at the same time, supplies them with an insight on how they can maximize the value of their consumers.
Marketing is an important channel companies/businesses use to publicize their products and services to the audience. A good marketing strategy will help a company generate a lot of sales and profits. The incorporation of ML into the marketing process has enabled marketers to implement good marketing strategies that project what the consumers would find appealing and worth buying.
With the assessment of the consumers’ data, ML gets to predict which products should interest each consumer and how marketers can advertise them. ML assists marketers with its prediction power.
ML can project the outcome of each decision a business/company is trying to make, and this helps a company/business to look out for risks and avoid wrong decisions.
There are tons of institutions/organizations that are currently incorporating machine learning into their operation for effectiveness and productivity.
In social media services, companies like Facebook and Twitter have succeeded in utilizing machine learning to provide their users with the best service. Facebook has succeeded in embedding AI technology, chatbots,into its Messenger App, which assists businesses and consumers to have hassle-free interactions on the social App.
Twitter, on the other hand, makes use of ML algorithms to judge each tweet based on several metrics. ML algorithms also analyze the history of each tweet and recommend similar tweets users may like to see.
In the construction industry, companies like Plooto and Sitekick are changing the construction narrative.
In the healthcare sector, ML is being used in companies like Ciox Health and PathAI to assist medical practitioners with the treatment of patients.
With the market value of machine learning set to reach
The realization of the value ML adds to the growth of businesses will also inspire more business owners and companies to embrace the technology to enhance their ecosystem.