You’ve probably heard about how AI is expected to change the world. But if you’re like most people, you’re probably more concerned about what it personally means for you and your business.
Machine learning solves data-rich and complex problems. For example, deep learning can interpret medical images and diagnose cancer earlier than humans. It can also control self-driving vehicles and help visually impaired people with their sight.
Eventually, machines will be able to make decisions the same way that people do. Here are some of the important business problems that are already being solved:
Duplication and inaccuracy in data are major problems for businesses hoping to automate their processes. Predictive modelling and machine learning algorithms can help significantly.
Machine learning programs can also learn to perform time-intensive data entry and documentation tasks.
That means employees don’t need to spend hours hunched over their keyboards doing mind-numbing data-entry work. Instead, they can spend their time on high-value problem-solving tasks.
Customer segmentation, customer lifetime value, and churn prediction are big challenges for any marketing team. Businesses now have more data than ever, from website visitors, social media, email campaigns, and lead data. Machine learning and data mining allow you to form accurate predictions for individual incentives and marketing offers.
By using machine learning, you can eliminate the guesswork from data-driven marketing. For example, you can look at the pattern of behaviour by a certain user during a trial period, and the past behaviour of other users. This means you can identify the chances that they will convert to a paid version and trigger customer interventions accordingly.
Machine learning is currently being used for financial analysis. This is due to the large volume of data, accurate historical data, and quantitative nature of data.
PayPal has cut its-false alarm rate in half while blocking fraudulent payments. Machine learning is being used for loan underwriting, fraud detection, portfolio management, and algorithmic trading.
According to Ernst and Young, machine learning will be able to continually assess data to detect and analyse nuances and anomalies. This will improve the precision of rules and values. And we can expect machines to replace a number of underwriting positions. Future applications of machine learning in finance include conversational interfaces and chatbots for sentiment analysis, security, and customer service.
Machine learning can identify any outliers and ward off any future issues. These predictive analytics features identify anomalies within unstructured data from user behaviour and machine logs on mobile apps and websites.
Traditionally, when data scientists would review large amounts of unstructured and machine data for outliers, they would need to set static thresholds. These would be either too low- meaning too much noise to work with, or too high to identify any abnormalities.
Machine learning does the hard work for you, making it easy for your team to predict potential problems before it happens.
You’ve probably noticed that “contact us” forms have been slimming down recently. This is another good example of how machine learning is streamlining business processes. Usually, customers have to choose their issue before filling out numerous form fields. But these machine learning processes analyse the main issue within each request before routing them to the right place.
Sure, this is a small win. But ticket tagging and efficient routing can be massively expensive for large companies. Ensuring a complaint is sent straight to the customer service queue or a sales enquiry heads to your sales team? This will save businesses significant money and time while ensuring all issues are solved ASAP.
The above examples are just a few ways that machine learning is changing the game for businesses everywhere.
The key fact to remember is that learning is adaptive. This means that machine learning is only going to get better, and will soon be able to solve even more problems within your business.
Large companies are already investing in AI and machine learning- not because it makes them look like they’re cutting-edge, or it’s a fad. They’re investing because they’re seeing positive ROI. And that’s why you should consider investing too.
Need some help navigating your machine learning problems? We can help you get it sorted. Get in touch today and let’s talk.