8 ways machine learning will impact day-to-day customer interactions

8 ways machine learning will impact day-to-day customer interactions
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Advancements in artificial intelligence seem like they are happening constantly, with more products incorporating this technology every year as companies seek to gain access to the technology’s capabilities.

This means that it is important to understand the impact of AI and machine learning, as well as how to properly leverage it to improve your business — especially when it comes to interacting with or serving your customers. To find out more, we asked Young Entrepreneur Council members the following:

We’ve seen many advancements in AI and machine learning in the last few years. How do you expect that machine learning will affect your day-to-day interactions with your customers?

Here’s what they said:

1. Streamline and Minimize Troubleshooting

There are two ways I can see AI or machine learning changing my business’s customer interaction, both for the better. First, it will minimize the amount of interaction needed for troubleshooting, since many common or simple questions can be easily answered through a robust AI. The second is that it will streamline the process in which we address and resolve any remaining concerns. – Bryce WelkerCPA Exam Guy

2. Increase Self-Service Options

A lot of people don’t want to pick up a phone to call a company or even send an email and wait around for a response. Because of the advancements in AI, your customers will have more self-service options. They’ll be able to solve their issues on their own using AI-powered resources that you provide, like chatbots. This will not only save them time, but save you time and money, too. – Blair WilliamsMemberPress

3. Create a More Personalized Experience

As e-commerce continues to rise, companies are looking for ways to differentiate themselves from the competition. One of these ways is through AI improving the online shopping experience through personalization. Amazon does this well with their product recommendations to upsell customers and give them a more custom experience. – Syed BalkhiWPBeginner

4. Automate Customer Intake

AI can make it less tedious to handle initial customer conversations. When you focus on automating intake through a script, you are able to get the information you need to enhance the human touch with your customers later on. This may include conversations that spark new opportunities and ways to make your customers happy in the long run. The initial conversation is not important. – Sweta PatelStartup Growth Mode

5. Prevent Fraud

AI and machine learning help prevent fraud in unprecedented ways. Both have the potential to help businesses detect and prevent fraud and other nefarious activities (money laundering, for example) by leveraging big data — available in real-time and collected from a wide range of different sources — to discover patterns and trends. – Stephen UffordTrulioo

6. Evaluate and Escalate Customer Service Requests

I’m looking forward to having customer service reporting controls that are able to better escalate and evaluate emails and incoming support requests. I think there is a lot of improvement that’s possible in this area from AI and machine learning. – Nicole MunozNicole Munoz Consulting

7. Constantly Update Information

There will be more updated information and details provided about these customers and prospects than ever before thanks to machine learning. This will give us a greater understanding of how to personalize communications and campaigns, further than we’ve ever done. – Serenity GibbonsNACCP

8. Discover Data Trends

With the amount of data available to us in the digital marketing world, I see machine learning being a key to help identify data trends faster, so we can have a greater impact in our campaigns. Digital marketing is all about data and making course corrections based on what the data tells you. Machine learning will help us recognize and adapt to trends more quickly, which helps us be more efficient. – Joel MathewFortress Consulting

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