Machine learning has been a buzzword in the technology industry for years. As it continues to explode in all aspects of business, it becomes more pressing for companies to adopt and implement machine learning. Otherwise, they will start to fall behind their competitors.
Machine learning is a segment of Artificial Intelligence (AI) that refers to the intelligence of machines instead of the natural intelligence that humans exhibit. Machine learning is the ability for computers to learn and improve from experience. Instead of explicitly being programmed, the machine can use its experience (lots of data) to make accurate predictions. This is all possible due to complex algorithms.
Although it sounds intricate, it’s most likely been a part of your daily life for a while now. For example, when your email predicts which emails are spam– that’s machine learning. And when you mark specific contacts as not spam, your email will put them into your primary inbox– that’s machine learning.
A few more common examples of machine learning would be Apple’s Siri, Amazon’s Alexa, Netflix’s recommendations, and even that chat-bot you used for customer service.
Why Machine Learning Is Important
Machine learning is one of the fastest-growing technologies in the world. Gartner predicts the business value created by AI will reach $3.9T in 2022.
It’s changing the world by automating tasks that take humans hours upon hours to complete. In addition to saving time and money, the machine is conducting a more in-depth analysis of the data, which leads to more accurate business predictions.
Even though new technologies with complicated, custom algorithms come with a price tag, the return on investment (ROI) is in your favor. According to Deloitte, 82% of enterprises adopting machine learning and AI have gained a financial return from their investments.
There’s one last piece of information that makes machine learning important. Its adoption rate. Most industries worldwide have already begun to adopt machine learning, which can mean one of two things. You’re ahead of the game, or you’re behind.
Let’s consider the financial industry, for example. Here’s an image showing its adoption rate by region.
For those financial institutions in North America that have yet to adopt machine learning, they are behind—in Europe, adopting it now before the other 36% could put a business ahead.
Ok, let’s get into the specifics of how machine learning can elevate your business.
6 Ways Machine Learning Can Elevate Your Business
Once the machine learning algorithm is in place, it can start learning about the business’s typical behavior. After the machine has learned typical behavior, it can begin monitoring network behaviors for anomalies in real-time. This gives the company more time to be proactive and prevent a full-scale intrusion, data leak, and/or service outage. Sometimes proactive measures can immediately be implemented by the machine. With the costs of data breaches averaging $3.92 million as of 2019, it would be worth splurging for the proactive protection machine learning can provide.
Increase Customer Satisfaction
Customer service is really important. Like, 96% of global consumers say customer service is a significant factor in selecting which brands they are loyal to, important. And it’s expensive to have a large customer support team that is well trained and can answer questions quickly and accurately 24/7. With machine learning, chatbots, and automated customer response systems can accurately identify customer needs and guide them to a solution. Not only is this automated, but it can be completed at scale, at a reduced cost, while keeping your customers satisfied.
Enhance Product Recommendations
Machine learning can be utilized to process customer data more precisely and identify even the smallest of trends. This, in turn, helps develop product-based recommendations. The machine learns customers’ purchase history and can provide similar recommendations based on what is in stock. Product recommendations account for up to 31% of eCommerce revenues.
Machine learning is helping marketers to understand their target audience faster and more accurately. Not only does this help marketers decide where to spend their ad dollars, but it also guides personalization. When there’s enough data on the customers’ characteristics, machine learning can help predict which customers are likely to convert and their behaviors, which can then be used to provide targeted, personalized marketing messages. 91% of consumers say they are more likely to shop with brands that provide offers and recommendations that are relevant to them.
Machine learning can be employed to detect trends in large data sets that are so small that humans wouldn’t be able to see. This can be in regards to most aspects of business, from marketing to sales to HR. For example, now more than ever, companies are analyzing data for hiring biases. Hiring data from resume to interview feedback can be imputed, and machine learning will identify trends that had gone unnoticed.
Analyze Large Data Sets
Analysis of large data sets is the perfect job for machine learning. Large data sets take a lot of time to get through, and humans still cannot extract all of the relevant information. Most machine learning benefits that have been discussed have explicitly been what to do with those data sets, but so much more can be done depending on your business needs. What information would help your business maximize efficiency? You can apply machine learning to extract that information. What information does your business need to help advise decisions, strategies, predictions, and risks? You can use machine learning to extract that information. The best thing about machine learning is it’s entirely customizable for your business’s needs. The algorithms are created specifically for your business and how it operates.
Machine Learning Sounds Awesome… Now What?
You’re convinced that machine learning is necessary for your business to start adopting. The next step is knowing if your current development team can write machine learning algorithms or if you need to outsource the work. You will most likely need to outsource the development unless you have a large, diverse team.
Before you begin your search, decide what’s important to you when outsourcing.
- Do you want an Agile team? (Spoiler: yes, you do.)
- Do you like working with large agencies where you are just a number to them or boutique agencies where you are one of their main focuses?
- Is a well-communicated project manager important?
- Onshore or offshore developers?
- Is there a specific project timeline you need to follow?
- Do you know precisely what you want machine learning to do, or do you need some consultation?
These questions can help you eliminate software development agencies from the get-go, so you don’t waste your time on sales calls.
Now you can start searching for a software agency to complete your project. You can begin by asking previous agencies you’ve worked with, business friends, or even a simple Google search.
Companies like UpCity are also a good option for qualified agencies with reviews.
Machine learning is a buzzword, and rightfully so. It is transforming the way the world does business. It’s increasing business efficiency while decreasing costs and improving customer satisfaction, cybersecurity, and the accuracy of business predictions. As industries slowly but surely transition to adopting machine learning, businesses have a choice. To get ahead of their competitors or be left behind.