6 AI tools to improve customer service.

In today’s fast-paced, digital-first consumer market, omnichannel contact centres have become the frontline for customer service.

By Greg Jarvis, Head of Customer Success at Connect SA

In the quest to deliver exceptional customer service and customer experiences (CX) that meet evolving expectations around digital engagement, operators must leverage digital transformation strategies to maintain a competitive edge.

In this regard, artificial intelligence (AI) has emerged as a game-changing technology given its ability to optimise contact centre operations, enable greater efficiency and personalisation at scale, and support frictionless interactions. These AI-driven digital tools can revolutionise contact centres and enhance customer service.

1. AI-powered chatbots and virtual assistants

Contact centres can access AI-powered digital channels in the cloud to unlock additional omnichannel capabilities that optimise operations and transform customer engagement.

Rolling out AI-powered chatbots, virtual assistants and other self-help channels, such as intelligent IVR, offload call volumes from live agents as these engagement platforms can handle routine (high-volume low-complexity) customer queries and in so doing empower customers to find solutions independently.

These AI-driven tools provide instant responses, reducing wait times and improving customer satisfaction. They also operate 24/7, ensuring always-on support that enhances the overall service experience.

2. Predictive analytics

Predictive analytics tools use AI to analyse historical data and amongst other “things” anticipate and pre-empt customer needs and call volumes.

Once contact centre operators migrate to the cloud environment, they can start integrating AI, machine learning and Natural Language Processing (NLP) into core systems such as customer databases and CRM applications, which paves the way for predictive modelling.

By analysing historical customer and interaction data, predictive analytics solutions can understand patterns and preferences, empowering contact centres to proactively offer tailored solutions, personalised recommendations, and faster resolutions. This data-driven approach to customer service improves engagement and fosters brand loyalty.

In addition, predictive models analyse past call patterns to forecast future call volumes, including peak times. These forecasts allow contact centre managers to schedule the appropriate number of agents to support the expected peaks, which minimises wait times and improves customer service and satisfaction levels.

3. Intelligent call routing

With AI-enabled intelligent call routing, calls are routed to the most appropriate agent or employee who has the expertise to address the caller's request based on the customer’s outstanding queries, , history, and sentiment.

These efficiencies result in reduced average handling times (AHT) and increased first-call resolution (FCR) rates, which improves customer satisfaction.

Skill-based call routing can also reduce call charges by giving customers the option to choose a call path based on a series of client-defined questions.

4. Sentiment analysis

Sentiment analysis tools use NLP to gauge customer emotions during interactions. By analysing tone, language, and keywords, AI-powered sentiment analysis tools can determine exactly how customers feel, detecting frustration or satisfaction in real time.

These insights allows contact centres to respond proactively by assisting the agent in real-time to manage the customer frustrations, improving customer service and boosting customer retention.

5. Automated quality assurance and performance monitoring

AI-powered analytics tools can automatically monitor and assess agent performance by analysing customer interactions in real time, creating opportunities to offer real-time assistance to agents, thus coaching them in-call and pre-emptively improving CX without manual intervention.

By identifying trends, highlighting areas for improvement, and ensuring compliance with legislative requirements, service standards, automated quality assurance solutions support staff training to ensure contact centres can maintain high service levels.

The ability to provide staff with granular information also creates transparency in terms of performance, which can support better engagement between agents and management.

6. AI-powered self-service channels

When call volumes spike, customers typically experience long hold times. These capacity limitations mean customers turn to other channels like email and social media, which require scarce human resources to process and add additional pressure on contact centre agents.

AI-based decision engines can triage and thus prioritise inbound calls, allocating basic engagements and repetitive tasks to automated AI solutions like chatbots or virtual assistants.

These AI-powered knowledge bases and self-service portals empower customers to find answers without contacting an agent, which offloads customer service interactions from agents to boost contact centre capacity and support lower AHT and higher FCR rates.

These self-service capabilities are also available 24/7, ensuring customers can access relevant information whenever they need it.