Not that long ago, the main way a business could succeed was through the hard work of the owner and team of employees. Now, thanks to the advent of machine learning, companies can also use computing technologies to help power and improve their business. Machine learning is a type of artificial intelligence (AI) that is based on the idea that machines can learn and adapt through experience. While past AI relied on mostly pattern recognitions, machine learning is evolving to take additional data and adapt. Let’s take a look at four ways that machine learning can help business owners and their companies succeed:
Help Keep Employees Organized
For companies whose employees rely on their smartphones for a variety of work-related tasks, machine learning may allow them to be more organized and efficient. For example, if the mobile devices are powered with Qualcomm Snapdragon mobile platforms — which are now enhanced with built-in machine learning — the smartphones will adapt to everything the employees are doing on their devices. From high-quality connections and real-time, on-device processing of information, machine learning will help smartphones live up to their name more than ever, which in turn will make for a more productive and organized employee.
Personalize Customer Service
Another way that machine learning can help businesses to succeed is through its impact on personalizing customer service with improved “chatbots.” Machine learning can combine the customer service data from a business along with natural language processing and algorithms that will learn and adapt from customer interactions to create even better “chatbots” that can answer questions from customers and provide accurate and helpful answers.
Encourage Customers to Stay with a Company
If you have ever had a website recommend certain items to you based on your past purchases, you have already experienced machine learning in the world of retail. In addition to encouraging shoppers to check out certain products based on what they seem to like, machine learning can also use data related to transactions and customer actions to determine who is at risk of going elsewhere to shop. Shoppers who are labeled as less loyal may then receive customized offers to them that are extra enticing. A great example of this machine learning is a smartphone company that understands that as teens grow into young adults, they often want to switch to a different cell phone carrier than the ones their parents use. Machine learning will mine customer interactions and other data to anticipate this scenario, and then make customized offers to the young adults to encourage them to stay. One example of software that uses AI to improve the customer experience is ReSci.
Banks and other companies in the financial industry are already using machine learning to help prevent fraud. For instance, data mining can be used to identify clients who have high-risk profiles, and algorithms can catch unusual and suspicious occurrences of transfers of funds between certain individuals and corporations. But you do not have to be president of a bank or investment corporation to be concerned about preventing fraud; the average organization loses 5 percent of its revenues each year to fraud. Any type of business can use machine learning algorithms and pattern recognition to notice any atypical transactions.
As time goes on, it will be interesting to see the other ways that machine learning will help power businesses and improve their bottom lines. We have only scratched the surface of this amazing AI technology and its positive impact on companies.