Boost Contact Center Value with Conversational AI for Customer Service

For most of its history, customer service has remained a difficult nut to crack. Several factors amount to these challenges, like the wide range of customer queries, significant skill gaps among customer service agents, and the need for constant monitoring and control.

With advancements such as conversational AI for customer service, these challenges can soon become a thing of the past. Conversational AI contact center solutions, simply referred to as CCAI, are the next-gen revolution set to transform CX and drive revenue growth opportunities.

Conversational AI is a technology that enables machines to understand and respond to natural language in a human-like manner. These technologies use Natural Language Processing (NLP), machine learning, speech-to-text, dialogue management, speech recognition, and intent recognition to enable humanlike interactions.

CX leaders are deploying it for chatbots, IVRs, voice assistants, and virtual agents while supporting human agents to perform.
The need for these technologies is emerging due to several factors, including staff shortages, preference for fast, convenient, and knowledgeable assistance, and surging labor costs.

CX leaders have worked using AI in customer service for a long time. Chatbots were a result of its early development. However, in today’s competitive landscape, AI-native customer service is essential. An AI-native contact center is designed from the ground up to incorporate AI, making it a fundamental part of its structure and operations. This allows for better optimization and scalability.

For instance, a conversational AI chatbot goes far beyond the scope of normal chatbots. It can understand user inputs in a contextually relevant manner, enabling more natural and dynamic interactions. It can also be used in other channels and facilitate omnichannel support in a consistent and branded fashion. Meanwhile, normal chatbots are preprogrammed, limited in options, and are not dynamic.

Conversational AI and CCAI are quickly emerging as the most promising and transformative innovations in the call center and customer service domains. According to a Gartner prediction, contact centers spent nearly $2 million on conversational AI in 2022. These investments are expected to generate $80 billion in value via labor cost reductions over the next four years.

Besides, a recent PWC survey discovered that 80% of American consumers prioritized speed, convenience, knowledgeable assistance, and friendly service as key elements of positive CX. These transformations have significant potential as AI-powered virtual agents, a key use case of conversational AI for customer service, can eliminate human interaction in up to 70% of calls, saving approximately $5.50 per call.

An AI-powered contact center can also provide multilingual support, thanks to advanced LLMs like ChatGPT. An AI-based call center using a ChatGPT conversational AI model can benefit from this, as about 68% of customers are willing to switch to a brand that provides customer service in their native language. Furthermore, about 64% are willing to pay for multilingual AI contact center solutions.

These CCAI trends can lead to improved customer experience for your target audience and significant cost savings for your organization. About 63% of CEOs have already deployed generative AI automation to help their agents, including agent training applications.

A contact center CX AI positively impacts your organization in many ways. It contributes to good CSAT scores and significant cost savings in your call center, making it a strategically important technology. Some of the key benefits of conversational AI for customer service include:

• 24/7 Availability: Unlike human agents, virtual agents built on conversational AI models can assist round-the-clock without delay or fatigue. CCAI also frees up human agents for more complex tasks, reducing their stress levels and improving their work quality.
• Omnichannel Support: Contact center AI services can provide consistent and branded CX across all channels. An omnichannel customer support strategy can deliver contextual conversations to customers across all platforms.
• Positive CSAT: CCAI can boost customer satisfaction with multilingual support, improved self-serve models, and faster resolutions through meaningful interactions.
• Sentiment Analysis: AI call center solutions can extract accurate transcriptions and conduct sentiment analysis while your agent engages with a customer or sales prospect. This helps objectively evaluate call quality.
• Agent Tracking and Training: Voice conversational AI tools provide performance insights to agents, assisting CX and sales leaders in enhancing their QA processes and helping agents improve their performance with personalized lessons.
• Real-time instructions: Smart conversational AI applications offer real-time assistance to your agents, providing instructions on their tone, customer intent, and prompt information search, among other aspects.
• Cost and Time Savings: CCAI solutions can independently handle a large volume of customer queries, reducing agent and infrastructure costs. Faster resolutions also significantly decrease the cost per call and save time for both agents and customers.
• Data Analytics: Data is now invaluable. Before generative AI and conversational AI models, most of the valuable information from agent-customer interactions was wasted. That is not the case anymore. Novel AI call center solutions can transcribe the calls, extract keywords, and conduct CSAT and sentiment analysis to turn each call into an asset.

With these latest transformations, contact centers and customer service leaders can now be on top of delivering quality CX at a great ROI for the first time. But this is not the end. Customer interactions can be leveraged as a great source of insights for further improvements, upselling, and revenue growth. The true potential of an AI-powered contact center can only be uncovered if the implementation is robust from start to finish.

• Analyze your present contact center operations: The first key decision will be a thorough analysis of your current contact center operations and pinpointing the major pain points. An AI-based contact center solution such as Vsynergize offers a lot of benefits. A detailed rundown of your current contact center operations, infrastructure, technology, expenditure, and performance metrics will be critical before the eventual transformation.
• Determine your long-term goals and objectives: Each organization faces a set of common and unique challenges in its contact center operations. These pain points will help determine which long and short-term goals you are aiming to achieve. Define the key outcomes such as sales ROI, agent performance, data analytics, CX, and other strategic pointers. You can access our case study, which can help with framing the above.
• Create a strategic roadmap: Once you attain a detailed understanding of your current positioning and major challenges, it’s time to map a strategic and practical trajectory. This plan will outline the steps, timeline, resources required and other such details of the entire transformation. This roadmap will become your AI contact center implementation bible to keep the execution on track. You will also have to keep things agile for whatever challenges emerge along the way.
• List the AI technologies and tools required: Selecting the AI contact center technology, including conversational AI applications, conversational AI chatbots, and generative AI applications, is important. Consider factors such as functionality, scalability, customization, ease of integration, migration capabilities, and vendor reputation. Vsynergize has an outstanding track record in leading such projects to success. Check out more here.
• Assess your data infrastructure: In a cutting-edge contact center AI model, your data is a key asset. Partnering with a contact center tech provider that assures data integrity, security, and quality is extremely important. Work on implementing good data governance practices to align the new model with your desired data privacy, security, and compliance norms. Besides, it also needs to ensure data quality, accessibility, and compatibility across your systems.
• Trial period to test waters: When preparing to deploy your AI contact center and conversational AI for customer service tools, it’s advisable to initiate a pilot implementation. In the initial phase, observe and analyze various indicators, from customer interactions to extraction of valuable insights. Evaluate the accuracy of the results obtained during this soft launch to determine if additional training for the AI is necessary. Following any required adjustments, proceed with entrusting the AI tools with whatever scope of operations you have determined.
• Promote collaboration and training: Ensuring that human agents and other resources undergo comprehensive training is crucial during such technological mass shifts. It’s essential to equip them with a deep understanding of how AI can enhance their daily tasks and responsibilities. Additionally, emphasize the potential of an AI call center to pivot them beyond sales targets through objective feedback and enhanced team collaboration.
• Evaluation of results and collaboration: Beyond the soft launch, the organization-wide implementation requires constant monitoring and adjustments. This will be a never-ending process of analyzing performance metrics and CSAT to keep the cycle of refinement. Moreover, collaborating with our conversational AI tech partner for further finetuning is critical for long-term success. Vsynergize specializes in such migrations and working as per your unique business needs.