How AI Is Changing Contact Centres and How to Benefit

According to Gartner, contact centres are on the brink of a significant transformation, with conversational artificial intelligence (AI) deployments projected to slash agent labor costs by $80 billion by 2026.

AI is reshaping the foundations of contact centre operations, equipping businesses with formidable tools to elevate customer service, boost operational efficiency, and bolster overall performance.

Five9’s Ruthie Carey delves into the different technologies used in AI-powered contact centres, provides a step-by-step guide to implementing AI in contact centres, and shows how artificial intelligence is transforming contact centres.

3 AI Technologies Used in Contact Centres

1. Voice Biometrics

Voice biometrics is a revolutionary technology that revolutionizes call centre operations. Its ability to use an individual’s unique voiceprint for authentication ensures airtight security, mitigating the risk of password fraud and identity theft.

This safeguards customer data and builds trust and confidence in the call centre environment. In addition to its robust security features, voice biometrics significantly enhances operational efficiency.

Automating the identity verification process reduces the workload on agents, enabling them to focus on resolving customer issues and providing a higher level of service.

This leads to shorter call durations, quicker issue resolution, and, in turn, increased customer satisfaction.

Moreover, voice biometrics can potentially drive up the adoption of Interactive Voice Response (IVR) self-service, a cost-effective channel often underutilized due to security concerns.

With voice biometrics in place, customers can access IVR systems with peace of mind, knowing their identity is secure.

This reduces the strain on live agents and shrinks call queues, leading to a more efficient call centre operation.

In this era of heightened security concerns, voice biometrics emerges as a game-changing technology that ensures customer protection and operational excellence in the call centre, ultimately benefiting businesses and their clients.

2. Natural Language Processing (NLP)

Natural language processing (NLP) is a critical component of AI that revolutionizes communication between computers and human language.

Within AI-driven contact centres, NLP plays a pivotal role in comprehending and interpreting customer inquiries, sentiments, and intentions, whether expressed in written or spoken language.

It excels in identifying and addressing customer concerns during voice calls, with the flexibility to route complex issues to live agents when necessary.

NLP-powered systems efficiently manage inquiry routing, glean valuable insights from customer interactions, and promote more effective communication with customers.

The integration of chatbots and virtual assistants in contact centres is reshaping the industry, with Juniper Research projecting substantial annual savings of $11 billion by the end of the year.

These AI-driven chatbots and virtual agents, armed with NLP capabilities, provide real-time, customized assistance, as customers increasingly embrace self-service options via voicebots and chatbots. This trend leads to a reduction in call volumes and substantial operational cost savings.

Furthermore, McKinsey’s forecast that automation could replace up to 29% of agent tasks underscores the remarkable productivity enhancements and elevated customer experience facilitated by chatbots and virtual agents, cementing their position as fundamental elements of AI-powered contact centres.

3. Speech and Text Analytics

Speech analytics, driven by AI, reviews audio recordings of customer interactions, including phone calls. It automatically transcribes conversations, identifies keywords, gauges customer sentiment, and highlights critical issues or trends.

In contact centres, speech analytics aids agent performance monitoring, identifies training needs, and offers valuable insights into customer feedback and preferences.

AI-powered speech analytics tools expedite the evaluation of call recordings and transcripts, suggesting whether agents meet QA scorecard criteria.

This analysis is automated for all an agent’s calls, eliminating random call selection by supervisors and minimizing the chance of unfair QA assessments.

Unleashing the Full Potential of AI: A Step-by-Step Guide

While integrating AI in contact centres can seem challenging at first, it doesn’t have to be. Here is a step-by-step guide to help you unleash the full potential of AI and turn your contact centre into a powerhouse of customer service excellence.

1. Understand AI’s Abilities in Customer Service

Start by clearly understanding AI’s capabilities in the context of customer service. Recognize how implementing AI in contact centres can enhance customer interactions, streamline processes, and improve efficiency.

2. Identify Key Areas for AI Implementation

Start by assessing your contact centre processes and determining where to implement AI effectively.

It could be in improving customer experience, agent experience, or operational optimization. The big idea is to align AI with your business objectives and needs, ensuring it creates the maximum impact.

3. Select and Customize AI Contact Centre Solutions

After identifying the areas where AI can enhance operations within your contact centre, the next step is to choose a suitable AI contact centre solution.

Depending on your specific business requirements, choose a vendor that offers flexibility and vendor-agnostic platform that will allow you to pick from a wide range of AI offerings.

Collaborate with your selected vendor to customize a tailored AI contact centre solution to ensure a seamless alignment with your unique operational needs.

4. Set Up a Timeline

Establish a comprehensive timeline for introducing AI in contact centre operations. Consider aligning AI implementation with strategic goals and budget constraints.

Break down the implementation process into manageable phases, allowing for a smooth transition and minimizing disruption to ongoing operations.

Do not forget to involve the stakeholders in planning to ensure a successful and coordinated rollout of AI technology.

5. Train and Tune AI

Effective AI implementation necessitates thorough training and testing of AI algorithms. Train AI systems using historical data to help them recognize patterns and make accurate predictions or decisions.

Regularly tune AI contact centre solutions to ensure they perform optimally and achieve desired levels of accuracy. This step is crucial for refining AI algorithms, enhancing accuracy, and ensuring adaptability to changing conditions.

6. Combine AI With Human Agents

AI should assist, rather than replace, human agents. Integrate AI into existing workflows to enhance human capabilities.

AI contact centre solutions can handle routine and repetitive tasks, freeing human agents to focus on more complex issues and value-added activities.

Combining AI with human agents improves efficiency, reduces response times, and ensures a seamless customer experience. Don’t forget to train your staff in using the new AI technology.

7. Watch and Get Feedback

Continuous monitoring is essential to assess AI’s performance and impact. Implement key performance indicators (KPIs) to measure AI’s effectiveness in achieving business objectives.

Gather feedback from both customers and agents to identify areas for improvement. Regularly update and refine AI algorithms based on these insights.

AI can significantly enhance efficiency, customer satisfaction, and overall business outcomes when executed effectively.

Follow the above steps to gain a competitive advantage and position your contact centre for future success in a rapidly evolving technological landscape.

This blog post has been re-published by kind permission of Five9 – View the Original Article

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Call Centre Helper is not responsible for the content of these guest blog posts. The opinions expressed in this article are those of the author, and do not necessarily reflect those of Call Centre Helper.