How will machine learning affect your day-to-day interactions with your customers?
The Young Entrepreneur Council (YEC) is an invite-only organization comprised of the world’s most promising young entrepreneurs. In partnership with Citi, YEC recently launched BusinessCollective, a free virtual mentorship program that helps millions of entrepreneurs start and grow businesses.
1. Providing Answers at All Hours
Machine learning allows us to provide higher quality customer service at a lower cost. In the past, we had to direct customer questions to a static FAQ during off-business hours. Now we can use bots to help provide “live” answers to customers 24/7. We route questions we cannot address easily with machine learning to our human customer service team for the best experience.
2. Anticipating Needs
This will enable huge amounts of data to be examined rapidly, with the aim to uncover hidden patterns, unknown correlations, market trends, customer preferences and other useful business info. Ultimately, this could lead to providing better financial services for our clients by anticipating their needs and wants, as well as identifying and mitigating problems before they arise.
3. Better Targeted Marketing
Machine learning will provide computers with the ability to learn more about a target audience and change the conversation when exposed to new data. This will help marketing efforts by offering highly customized information based on what the computer has learned about prospects and customers, and their desires, needs, fears and wants.
4. Shifting Staff to Answer Complex Questions
By automating part of the customer service process, like using a help desk to cover easy questions, there’s more time to proactively contact customers and ask them if they need anything. It’s also a way to free up time to handle more complex customer problems and put in face time that could save relationships.
5. Applying Results of Research
Machine learning will take a lot of the grunt work out of auditing and research so that we can get to answers and high-level thought much more quickly. Without having to dive into the data ourselves, we’ll be free to use our brains for higher-capacity learning and apply whatever the results teach us.
6. Tailoring Campaigns via Clustering Techniques
One of the hottest research areas in machine learning is clustering customer data. This kind of approach automatically groups related customers according to the way they interact with your business. Clustering techniques extract information to tailor campaigns and promotions to each target audience with fewer costs involved.
7. Giving Specific Answers to Clients
Machine learning will allow us to process bulk quantities of data from different sources, and will allow us to make decisions more quickly that will directly impact how we communicate and interact with our customers day to day. For example, instead of giving subjective answers and estimates, we’ll be able to say things with greater certainty and predict performance with better accuracy.
8. Generating User-Specific Search Results
For e-commerce businesses, search is one of the most important technologies affecting how customers will interact with you. As machine learning becomes more sophisticated, advances will be made to display results that are more relevant to the individual user. Giving the customer the power to find what they are looking for will reduce the need for direct customer interactions.
9. Discovering Need, Then Providing Better Products
The age-old problem for businesses is figuring out exactly what customers want and then either delivering it to them or building great products. Data allow businesses to find out exactly what customers are using, and what they want so that they can build those products.
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