Top 12 Use Cases for AI-Based Contact Centers to Improve Customer Experience – Part 2

In the first part of this blog, we took you through six use cases of AI-based Contact Centers to improve customer experience:

• Order Management for CPG, Retail and Pharmaceutical industry
• Data Collection, Capture and Entry
• Improve Lead Generation and demo show-up rates
• Account and Membership Services
• Appointment Scheduling and Reservations
• Driving Registration and Participation for Events

This second and concluding part will highlight a few more contact center AI use cases to give you a complete picture. Let’s explore in detail.

There is no doubt that IVR has been one of the most revolutionary technologies in customer service. It became the lifeline of businesses for cost-cutting and customer call automation. However, long waits, complicated and multiple menus, and inability to understand voice prompts have resulted in frustrating customer experiences. A survey reveals that 61% of customers find IVR a poor experience and 51% of customers abandon the business. As a result, companies lose $262 per customer annually. Another research found that 83% of customers will avoid or abandon a business after poor IVR experience.

Since IVR runs on Automatic Speech Recognition (ASR) only, it can hear and respond only through pre-programmed options. On the contrary, AI combines ASR, NLP and machine learning to provide a natural, conversational and coherent experience to customers. It can recognize, transcribe and interpret the next course of action from a customer’s voice to provide an appropriate response. If human intervention is necessary, it will also automatically route the call to humans. Hence, AI is a smart replacement to IVR for customer service augmentation.

Let’s analyze a recent situation here.

COVID-19 put immense pressure on the contact centers of the airline and hotel industry. The number of calls surged in unexpected volume as people sought rescheduling, cancellation and refunds of their bookings. The limited manpower capacity in contact centers led to a delay in the resolution of customer queries. This resulted in the escalation of customer grievances and also adversely impacted the brand reputation of airlines and hotels.

AI-enabled automation could have easily and effectively helped salvage the situation and provide better customer experience.

Contact centers can deploy e-workforce to alleviate such high volume occurrences and extend support to the existing manpower. The e-workers or virtual agents can work 24/7 and provide an automated response to routine queries without human intervention. They can decipher the intent of query to deliver an intuitive and intelligent experience to customers just like humans do.

It is often argued that AI will replace humans in contact centers. Well, this is not true. AI agents will rather augment the capability of humans in the following ways:

• Relieve them of the redundant workload through automation of repetitive queries.
• Escalate the calls only when needed.
• Directing queries to appropriate departments or concerned agents.
• Gauge the intent of customers and help deliver the right resolution to customers.
• Extract data from various systems to provide accurate and relevant information about customers’ previous interactions.
• Provide real-time analytics to eliminate errors.
• Boost the productivity of agents.
• Allow human agents to focus on more strategic and complex customer service tasks.

It is estimated that 53% of companies expect an increase in their total contact volume in the next two years. 61% of companies expect an increase in the complexity of interactions. This raises serious challenges in manpower planning and capacity building. AI is the answer to navigate through these challenges and augment the capability of human agents.

AI has evolved as a technology that goes beyond routine business process automation in contact centers. Through its intelligent automation capabilities, AI can interpret contextual interactions to analyze customer behavior and predict their needs.

Let’s say, a customer called your hotel’s contact center. Based on customers’ demographic information and/or previous booking data, AI-based chatbot can predict customers’ needs, intent and preference. These predictive insights can be leveraged to provide value-added and personalized recommendations to customers. Bespoke experiences translate into higher customer satisfaction. This kind of AI-powered prediction can go a long way in reducing customer churn and retain their brand loyalty.

Did you know that product recommendations contribute to 10-30% of revenue? E-commerce retailers commonly use upselling and cross-selling strategy to enhance customer experience and drive revenues. Amazon is a brilliant example here. 35% of its onsite revenue comes from transactions through product recommendations generated by its algorithmic search engine.

In the context of contact centers, RPA can support upselling and cross-selling in two ways:

• Workload Sharing: RPA can automate repetitive tasks and handle a large volume of customer inquiries. With a lesser workload, human agents can spend more time focusing on customer interaction and making personalized product recommendations.
• Decoding Customer Buying Behavior: RPA can scan through calls, chat messages, emails, recent browsing activities and all customer touchpoints to detect customer’s buying patterns. By applying machine learning and predictive data algorithms to these patterns, you can offer highly targeted product recommendations to match customer needs.

In today’s fast-paced world, customers want quick assistance. They are open to self-help experience provided it expedites the resolution to their queries. They prefer to book/cancel an appointment, check the status of their credit card bill or register for an event on their own.

A survey found that 66% of customers use self-service before reaching out to an agent. Another study revealed that six out of ten U.S. consumers prefer digital self-service tools for simple queries. They sought self-help on the website, mobile app, voice response system or online chat before seeking out face-to-face or phone interaction with a real person.

You can provide self service to your customers through AI-based digital assistants. With their intelligent automation capabilities, they can find an easy correlation between customers’ problems and solutions. These digital assistants can also comb through your knowledge base, troubleshooting manuals, DIY tutorials and FAQs to help customers self-serve themselves. If AI agent senses that customers’ problem is too complex for self-service, it routes the matter to human agents.

AI-powered self service provides faster resolution, reduces customer escalations, improves customer engagement and lowers customer service costs.

AI-based contact centers will be a key driver in raising the bar of customer experience and ensure continued business success. AI adoption is no longer an option, rather it is the need of the hour to survive and thrive.

Thinking about Contact Center automation for boosting your customer experience? Set up a demo and consultation session with our automation experts here.