August 13, 2024 Five Ways AI Can Supercharge a Manufacturer’s CX

By elevating the customer experience, AI-driven contact center capabilities are proving their value to manufacturers.

By Matthew Marion

Manufacturer Y and Manufacturer Z are long-time competitors that often find themselves vying head-to-head for the same customers. The widgets they make are built for essentially the same application and they’re similar in quality and price. Historically, choosing between the two products and companies has been a Coke vs. Pepsi type of proposition — a matter of personal preference, all other factors being equal.

Lately, however, a noticeable disparity has begun to emerge between the two competitors. The quality of the competing widgets hasn’t changed, nor has the price. But Manufacturer Y has made one critical change, shifting its traditional customer sales, service and support systems to a unified, multichannel, cloud-based contact center solution equipped with artificial intelligence-driven features, while Manufacturer Z has stood pat, believing its existing systems for customer interaction, as well as they have served the company over the years, are good enough.

After implementing its new contact center in the cloud, Manufacturer Y begins noticing a gradual uptick in widget sales, particularly to former customers of Manufacturer Z, which itself can’t help but notice a corresponding drop-off in sales of its own widget. Even dropping widget prices below those of Manufacturer X’s product in response fails to bolster sales. It’s time, Manufacturer Z decides, to pursue a contact center upgrade of its own. However, the damage — customer defections, lost revenue — is done.

Stories like this abound in a world in which the quality of the customer experience (CX) matters as much as the quality of the product itself, and a manufacturer’s customers expect a seamless, intelligent, multichannel journey like they are accustomed to everyday as consumers. With a new generation of AI-driven capabilities, manufacturers now have the ability to consistently deliver these kinds of rich, highly personalized customer experiences to differentiate themselves from the competition. In many cases, tapping into these capabilities is a matter of shifting away from legacy, manual-intensive and poorly integrated contact center systems, to a cloud-based approach that integrates channels within a contact-center-as-a-service (CCaaS) solution that gives customers nuanced, highly personalized support across channels, preserving the context of each interaction and delivering natural conversations and interactions that can effortlessly jump between text, voice, Web, chat and email. Here are five CX-focused areas where AI-driven contact center capabilities are really proving their value to manufacturers:

1. Eliminating common CX pain points. With AI-powered chatbots and assistants to engage with customers from the outset of an interaction, they won’t have to contend with issues like long wait times, repetitive authentication processes and a lack of context from one channel to another. AI tools can manage intake information, route and answer inquiries, and generally turn what can be disjointed, off-putting interactions into positive experiences.

2. Fast, easy issue resolution. AI can be a highly effective and efficient initial gatekeeper, identifying interactions that don’t require agent contact, and flagging more complex cases that do require a human being to resolve, using predictive, dynamic routing to the appropriate agents for resolution. In these interactions, AI gives agents the complete picture of the customer, from communications channel preferences to past interactions to buying history with the company. During each interaction, AI listens and feeds agents with contextual resources and information, recommending follow-up questions and best next actions, all in real time, so agents have everything they need, in the moment, to resolve issues better and faster. The AI assistant also can be trained to understand and use industry-specific terminology when interacting with customers, so they feel like they’re dealing with a subject-matter expert.

AI-powered sentiment analysis capabilities also come into play here, with the ability to take the temperature of an interaction and even identify tonal nuances like sarcasm. Based on what it detects in a customer’s demeanor, it then can produce in-the-moment best-next-action recommendations to the agent to help them de-escalate a situation in the case of an unhappy customer, for example.

3. Richer, personalized interactions. Not only can AI develop recommendations based on a customer’s past clicks and order history, it can deliver those recommendations in the moment, from a web site, during a virtual assistant or chatbot interaction, or to an agent during a person-to-person conversation. Agents have a full 360° view of a customer’s journey with the company to that point, so they can tailor their recommendations accordingly.

4. Automating ordering. An AI virtual agent can accept and process full customer orders, without the aid of a human, and through integration with an inventory management system and/or customer relationship management system, provide details on expected delivery, and alert the customer if an item is out of stock, suggesting an alternative item where relevant.

5. Strengthening quality management for continuous CX improvement. In a QM context, AI-driven sentiment analysis tools, coupled with customer interaction analytics, excel at gleaning insights into high-level contact center quality trends across channels, as well as trends in customer queries, with predictive capabilities that can identify emerging customer issues quicker than they otherwise would have been spotted, then alert managers accordingly. What’s more, rather than supervisors having to manually review recorded customer interactions themselves, a tedious and time-consuming process, natural language processing tools can review, summarize, analyze and pull trends from those interactions, reducing the cost, time and effort required to evaluate agents.

Collectively, AI capabilities like these support a lean, cost-efficient contact center operation, without compromising quality. They can help organizations better manage their contact center workforce and avoid labor shortages by analyzing historic data to make scheduling recommendations, for example. And through automation and more efficient use of resources, they can relieve organizations of some of the pressure to hire and retain customer service talent. In a world in which organizations are increasingly judged by the quality of the digital experience they provide, all this adds up to a true, CX-driven competitive advantage.

As senior principal, CCaaS + Contact Center Services, at Windstream Enterprise, Matthew Marion is responsible for the Windstream Enterprise XCaaS product suite, including development and lifecycle management. He has extensive experience managing various products and services, from SIP Trunking to Hosted VoIP. He joined Windstream in 2016 and held previous product and marketing management positions with CenturyLink and DISH Network. https://www.windstreamenterprise.com/

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