How Conversational AI empowers Your employees and Customers

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robot coming to greet a man that is leaning over

For many customers “self-service” really means “self-annoyance.” Tools such as FAQs, simple chatbots, and other knowledge bases can provide some information, but it’s often disjointed. It might provide the customer with an answer that’s 75 percent relevant, but that’s not enough. The customer will then either push to speak to a human agent or they’ll abandon their inquiry and potential sale due to frustration. Combating this dynamic requires firms to use new technology that automates various customer and employee processes with intelligence and speed. With the pandemic accelerating digital transformation and most firms shifting to digitized experiences, there’s a pressing need for brands to offer self-service tools that serve the customers’ needs.

Limitations of Current Self-Service Tools

The roadblock for AI platforms is the current tools often create more work for the customer and headaches for employees. For example, a traditional chatbot might recognize certain phrases, doesn’t understand context or sentiment. It would provide users with a few answers/pathways, but these were presets, programmed in by someone in a “if/then” structure. These types of service tools work on what’s known as supervised guided flows. The “supervised” means it follows a type of script and cannot operate outside of those parameters.

Conversational AI allows for unsupervised guided flows, where the automation recognizes patterns and then corresponds with a relevant action or answer. It enables automated tasks in response to inquiries, not just stock answers that might not move the customer forward in their journey. Working with unsupervised guided flows is the core capability of conversational AI, a new type of technology that relieves stress from both the customer and employee experience.

The Conversational Intelligence Opportunity

Improving self-service tools that can enhance the customer experience requires new technology innovations. At the core of realizing this goal is “conversational AI” a type of artificial intelligence that understands human context and sentiment. It uses natural language processing (NLP) and machine learning to better understand spoken and written communications. It’s like Alexa or Google Home, where the technology excels at recognizing what people want.

Removing Mundane Tasks from Employee

A core benefit of conversational AI is to remove mundane tasks from human intervention. It’s intended as a complement to these jobs, not a replacement. It streamlines workflows for customer service and IT teams by automating many answers with relevant intelligent answers. The more the industry keeps investing in this, it keeps very complex problems within human’s resolution. By offloading many mundane tasks away from workers, it can provide them with more opportunity to add value through personal customer interactions. Staff can also focus on how they can improve the customer journey.

The information that informs the conversational AI platform comes from multiple sources. Advanced platforms can pull data from ServiceNow, Salesforce, and other platforms, as well as previous chat transcripts, website content, and other sources. The ability to pull from various knowledge bases (instead of using pre-set responses) vastly expands the platform’s ability to delivery relevancy at speed and scale. Companies can also connect existing communications channels like Slack and other back-end systems to an AI solution. This provides another layer of intelligence for the AI platform, where its users historical service tickets and documentation to develop a pattern of continuous learning. These benefits extend beyond customer interactions, where staff can draw from a broad knowledge base to learn more about the company’s products and latest announcements, so they develop a deeper understanding of their brand.

Conversational AI can transform internal-facing platforms such as IT service desks. With these platforms, instead of IT departments spending a lot of time on password reset inquiries or software provisioning, they can focus on their role in improving the customer experience. IT can instead devote resources to revenue generating projects, like a new CRM platform, or streamlining the UI of various customer-facing apps

Adding Actions into the Mix

Conversational AI’s promise gains tremendous power when paired with action. Some providers such as Aisera pair together a conversational AI platform with robotic process automation, or RPA. With RPA, a self-service platform can become a full transactional system. RPA reviews humans performing tasks and then is programmable to repeat those same tasks without requiring humans. For example, subscription renewals present brands with a repeated and time-consuming tasks. A customer sends a chat, email, or calls to renew their subscription, and a human agent typically needs to confirm all their contact and payment information through a manual process.

With an RPA and conversational AI program, if a customer sends a note about renewing their subscription, the platform intelligently recognizes their intent and then prompts an automated renewal process. And if the customer’s data does not match into that process, the system knows to route the issue to the right human agent.

It’s like an autonomous car for customer service support and IT help desks. In the past 10 years driverless cars came into the market, and automated driving features will become standard soon. If cars can remove so much human interaction for a process as complicated as driving, there’s no reason a self-service platform can’t automate most inquiries and perform an array of complementary actions. 

Conversational AI remains in the “first inning” in terms of innovation and adoption. However, despite this early-stage market, it will quickly become a necessity for brands that want to thrive in the digital age. Without conversational AI, firms will offer a disconnected customer service experience through overworked and underutilized agents. Instead, they need to leverage this technology and add RPA to streamline self-service and pair it with automated actions that benefits customers, workers, and the bottom line.

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