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SmartData Collective > Business Intelligence > Artificial Intelligence > AI-Automated Customer Service is the Future
Artificial IntelligenceMarketing

AI-Automated Customer Service is the Future

Rehan Ijaz
Rehan Ijaz
4 Min Read
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Contents
Deliver Relevant and Targeted ContentOffer Timely AssistanceProvide Seamless Omnichannel Customer CareDeliver 24/7 Customer ServiceImprove Resolution TimeConclusion

The future is now when it comes to using AI-automated customer service, which is the key to increasing customer satisfaction and improving cost-efficiency. In fact, customers will manage 85% of their relationship with businesses without interacting with a human.

Here’s how AI-driven automation technologies are changing customer service by delivering faster and more accurate assistance:

Deliver Relevant and Targeted Content

AI-technologies can combine customer information from your existing database (e.g., purchase history, demographic information, preferences) with real-time behaviors to predict customers’ needs and deliver the most relevant content that will drive engagement and increase conversion.

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For example, you can use analytics to derive insights for implementing personalization strategies. The information can guide agents to interact with customers in the most appropriate manner and resolve issues expediently.

Offer Timely Assistance

Use AI-automated applications to monitor online or in-app activities for distress indicators and use the insights to inform pre-emptive actions.

For instance, you can provide customers with appropriate assistance such as real-time support through FAQs or virtual agents on various platforms and devices. A chatbot can be used to answer product-related questions or guide a customer through the checkout process to lower cart abandonment, reduce customer complaints, and increase sales.

Provide Seamless Omnichannel Customer Care

Consumers expect to communicate with brands via a variety of channels (e.g., phone, email, live chat, SMS, social media, messaging apps) and have the ability to switch platforms midway through a conversation without missing a beat.

AI-powered technologies can automate many of these interactions, sync up contact histories in real-time, and display the most relevant information for agents to pick up the conversation exactly where the customers have left off to improve productivity while minimizing frustration.

Deliver 24/7 Customer Service

AI-automated customer service software isn’t constrained by time zones or holidays. It allows you to deliver always-on customer care, provide users with prompt responses, and resolve issues immediately. It can also be integrated with various self-service tools (e.g., knowledge base) to help customers find the answers they need when they need it.

Also, by handling simple customer inquiries automatically, you can free up agents to focus on resolving more complex issues and building customer relationships that will increase loyalty and retention.

Improve Resolution Time

Even if a human agent is needed to handle a query, AI-driven automation technology can set expectations on the turnaround time, gather relevant information from the customer, and route the query to the appropriate team member based on a variety of factors, such as skills and availability.

AI-based omnichannel routing can be applied to calls, inbound chat, social media, and email to lower the response time, improve first contact resolution rate, increase agent productivity, and improve customer satisfaction.

Conclusion

AI-automated customer service applications are essential in today’s marketplace, in which customers demand speedy resolution of their queries. These technologies can be used on the front line to handle simple questions and route calls to the right team members to improve customer experience. In addition, they can be paired with human agents to facilitate access to real-time data and relevant information so you can improve productivity and customer satisfaction.

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ByRehan Ijaz
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Rehan is an entrepreneur, business graduate, content strategist and editor overseeing contributed content at BigdataShowcase. He is passionate about writing stuff for startups. His areas of interest include digital business strategy and strategic decision making.

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