What Does Generative AI Mean for Your Contact Centre?

Tim Kimber at Vonage explores the key use cases of Generative AI in contact centres, from virtual assistants and call routing to sentiment analysis and agent training, and how businesses can successfully implement it.

Chances are, you’ve probably experienced some form of early AI in a contact centre.

Whether you received suboptimal automated responses in a bot conversation about financial services, had to repeat yourself in every interaction, or got directed to the wrong article, it can feel like your frustrations are not being properly acknowledged.

All this is about to change, as Generative AI finds its way into contact centres to resolve these issues and enhance experiences. Read on to learn what this means for contact centres and how your business can benefit.

Use Cases of Generative AI in Contact Centres

Let’s dive into the use cases of Generative AI and how it can impact your business.

Virtual Assistants

Many contact centres use virtual assistants in the form of voicebots and/or chatbots. They help businesses handle high-volume, straightforward interactions, which frees up human agents to focus on the more complex issues that require specialist knowledge, empathy, and a personal touch.

Generative AI will take virtual assistants to the next level using advanced natural language processing and generation to dramatically improve understanding, communication, and content generation.

This will all be instantly available in any language with the appropriate tone and style. Generative AI also continuously learns from the data and feedback received, optimizing performance and behaviour to match customers’ individual likes and dislikes.

So we can expect Generative AI to enhance customer service and support, resulting in improved loyalty and satisfaction.

Language Support

In the past, providing support for multiple languages in contact centres involved coding it in at source or providing fairly complex language lookup tables – all subject to human error.

That is changing as Generative AI automates and optimizes multi-language support, assisting in the creation and maintenance of quality, consistent, and personalised experiences in many different languages with minimal human effort and resources.

Call Summarisation

With call transcription increasingly used in contact centres, Generative AI can be used to reliably create a succinct written summary of the call.

This not only takes a time-consuming burden away from agents, but also ensures both consistency and accuracy. Using natural language understanding to extract information is critical to the effective running of the contact centre.

Call Routing

This used to mean relying on a set of predefined, static, and inflexible rules and algorithms, resulting in suboptimal routing decisions in the contact centre.

Generative AI dynamically optimizes call routing based on real-time data and feedback, learning from every interaction to continuously improve and match callers to the best available agent.

Quality Assurance and Compliance

Many contact centres operate in regulated industries or have to follow some form of compliance, often needing to adhere to processes.

Generative AI can help automate and even optimize these processes, while at the same time reducing risk, improving overall efficiency, and delivering better outcomes. This ensures better quality and compliance standards and typically saves both time and money.

Knowledge Bases for Agent Assistance

Building and maintaining a knowledge base has been an arduous task in the past, with lots of room for human error and misinterpretation.

Generative AI enhances knowledge bases by automating both the creation and maintenance process, using natural language processing and machine learning to extract, validate, and update relevant information from a wide range of sources.

This also tends to make the knowledge base far more dynamic and flexible, ensuring personalized and contextualized responses, with a predilection toward learning and continuous improvement.

Sentiment Analysis

While speech analytics has been around for a while, a relatively new development is the widespread use of sentiment analysis to uncover customer emotions in interactions.

This has relied on predefined rules that can struggle to capture the precise nuances and contexts of human emotions, along with limitations for languages, dialects, accents, or even slang.

Generative AI can help automate and improve sentiment analysis, resulting in significantly improved customer satisfaction, retention, and overall loyalty (plus process improvement).

Appointment Scheduling

Scheduling a doctor’s appointment or a technician’s visit is something we all do from time to time. While many organizations have moved away from human-to-human appointment scheduling, some automated systems still leave a bit to be desired.

Generative AI can provide a better way to schedule appointments using natural language processing and machine learning, with customers able to interact via voice, text, or web.

Confirmations, appointment reminders, rescheduling, cancellation, and feedback are all easily handled. It even learns from customer preferences and behaviour, improving experiences, saving costs, and reducing missed appointment rates.

Script Generation

Contact centres that use scripts for agents can be somewhat restrictive with a “one size fits all” approach, limiting the personalization customers expect.

Generative AI improves this through dynamic and personalized scripts that leverage natural language generation and understanding to create engaging conversations. It also continuously optimizes scripts based on customers feedback and data, improving performance and quality.

Predictive Analytics

Generative AI can provide additional capabilities to analytics by enriching data architecture, analysing very large data sets, and using data to create software code that can build deep analytic models. This improves prediction accuracy and can identify new solutions to complex problems.

Voice Cloning

An emerging contact centre technology is the ability to create a synthetic voice that sounds like a native speaker. An example is making the voice of an offshore contact centre agent sound like a local in the market being served.

This has multiple applications, including personalized customer interactions, better brand image, and less agent fatigue. Generative AI can enable realistic and consistent synthetic voices with minimal data and effort.

Customized Sales and Marketing Messages

Generative AI can automatically and continuously analyse customer data, past call transcriptions, and other information to create highly relevant and personalized messages that can increase engagement, satisfaction, and loyalty.

Agent Training

This is a critical part of contact centre operations, helping to reduce the ramp time for new agents and keeping existing agents refreshed with the latest knowledge and skills.

Generative AI can be used to ensure realistic and diverse training scenarios and dialogues based on current data and customer profiles, adapting the difficulty and complexity of the simulations based on agent levels and progress.

It can provide instant and actionable feedback with suggestions on handling different situations, plus gamification and rewards that boost agent engagement and motivation.

Benefits of Generative AI in Contact Centres

Generative AI can predict the needs of your customers, so that you can provide a highly proactive and fully tailored support service.

It also facilitates the auto-generation of customer replies, can assist agents in real time during customer engagements, automates the process of note taking by summarizing transcripts, and produces customized agent training programs.

How To Implement Generative AI in Your Contact Centre

Tools like IVR (interactive voice response), agent assistance, robotic process automation, and chatbots have already come some way in improving agent productivity.

Generative AI will increase what can be automated, performing tasks that are far beyond the capabilities of these early technologies.

Once you’ve decided that you need Generative AI in your contact centre, you’ll want to find a partner who can give you good advice before, during, and after the sale.

To get started, choose a contact centre vendor that owns their AI technology and has already integrated it so everything works easily, straight out of the box.

Make sure you prioritize vendors who own both their contact centre and AI technologies, have a long heritage of successful deployments, and can provide a 24×7 global support capability.

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

For more information about Vonage - visit the Vonage Website

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.

Author: Vonage
Reviewed by: Jo Robinson