Customer expectations are soaring to new heights, creating an immense opportunity for companies to differentiate themselves through exceptional service experiences. But operating a contact centre is an expensive undertaking. Between staffing costs, training, technology investments, and high agent turnover rates, companies are constantly seeking ways to optimise their contact centre operations.
This is where artificial intelligence (AI) enters the picture as a compelling solution. By strategically integrating AI capabilities, businesses can significantly reduce costs while simultaneously enhancing the customer experience. Let’s explore how.
The Contact Centre Cost Conundrum
Even the leanest contact centres face staggering operational costs – salaries, benefits, bonuses, training, software licences, equipment maintenance, the works. Premium call centre software alone can run into the millions of pounds. ContactBabel reports that the cost per inbound call has risen 47% in the past 5 years to £6.26, largely driven by increases in new agent starting salaries.
High agent turnover compounds the spending. The average turnover rate in UK contact centres hovers around 26%. For every agent who leaves, onboarding and training a replacement can cost over £10,000. With hundreds or thousands of agents, that adds up rapidly.
Understandably, businesses are seeking AI-powered solutions to curb these soaring costs without compromising service quality.
AI to the Rescue: Slashing Operational Costs
AI-enabled technologies like intelligent chatbots, voice assistants, robotic process automation (RPA), and predictive analytics are rapidly transforming contact centres into cost-efficient powerhouses.
Here are some key use cases:
Automating High-Volume, Low-Complexity Tasks
AI chatbots and voicebots offer huge cost savings by automating repetitive, low-complexity queries at scale. After implementing CAI, Cats Protection handled almost 1,000 additional customer conversations across voice and digital channels, enabling it to respond to a staggering 46% more customers – a feat impossible with human agents alone. Some enterprises report automating over 60% of total inquiries this way, drastically reducing live agent workloads and associated costs.
Optimising Workforce Planning and Scheduling
Precisely forecasting staffing needs is crucial to controlling costs while meeting service levels. Premium Credit experienced significant savings in the time and resources spent creating schedules, performance and adherence. The WFO solution has seen employee engagement rise 13% year on year. A leading UK energy supplier saved millions annually by aligning staffing precisely with projected demand. AI can accurately predict call volumes, topic complexity, skillset requirements, and more to enable this optimal “right-shoring.”
Empowering Agents with Real-Time Guidance
AI augmentation slashes training costs while boosting agent productivity. An insurer reported that their agents using AI coaching reported 22% increased efficiency and higher CSAT scores. They estimate over £3 million in annual savings. AI provides agents with real-time call transcriptions, translations, suggested responses, relevant knowledge articles, and next-best-action guidance.
Quality Monitoring and Agent Performance
Human supervisors can only sample a tiny fraction of agent interactions for quality monitoring. In contrast, AI automatically assesses 100% of interactions to identify training needs, compliance risks, skill gaps and more – enabling targeted coaching that upskills the workforce.
The Customer Experience Upside
While the cost savings are significant, AI’s customer experience benefits may be even more valuable. Faster issue resolution via self-service bots, lower wait times, higher first contact resolution rates, and seamless omnichannel experiences – these capabilities powered by AI result in happier, more loyal customers.
AI also unlocks personalisation at scale. By tapping into historical interaction, product and behavioural data, AI can tailor customer journeys, predict needs, and proactively suggest solutions. This type of hyper-personalised experience is difficult without AI’s heavy lifting and data synthesis capabilities.
Overcoming Barriers to AI Adoption
Undoubtedly, integrating AI into contact centre operations faces hurdles like implementation complexities, data quality concerns, employee scepticism around job security, and more.
However, several tactics can smooth the transition:
- Run AI pilots on lower risk processes to build confidence
- Actively involve employees and address concerns through transparency
- Focus on “Human-Assisted AI” that augments rather than replaces agents
- Invest in data quality, security and governance processes
- Leverage conversational AI capabilities to make human-AI interactions more natural
The Future of AI in Contact Centres
As AI capabilities mature and become more sophisticated, the potential for innovation is staggering. Advances in areas like natural language processing, machine learning, computer vision, emotion AI and more will further automate tasks and drive efficiencies.
Ultimately, AI stands to transform contact centres from costly, reactive cost centres into proactive experience hubs that seamlessly blend human and artificial intelligence. The winners will be companies that embrace this future, and achieve major cost optimisation while delivering superior, personalised customer service at scale.