According to IDC, generative AI spending in the Asia-Pacific region alone is projected to reach US$26 billion by 2027. This includes AI investments in customer engagement as businesses seek to remodel their operations around creating delightful customer experiences at every touchpoint.
However, while AI use cases in customer experience are increasing, traditional contact centres still struggle to meet the evolving expectations for personalised, omnichannel interactions. Amid shifting customer demands, contact centres need to transcend inefficient legacy systems and overcome integration challenges to gain a competitive edge in the age of AI. By embracing advanced technologies and improving system interoperability, they can better cater to modern customers and enhance overall service quality.
The strategic benefits of modernising
Utilising real-time customer data and advanced language models can enable businesses to offer self-service capabilities and improve agent experiences. Modernising contact centres through cloud-native architecture can facilitate the delivery of better customer service at a lower cost and help businesses transition from outdated systems to more advanced ones. Solutions that integrate data with AI advancements can address operational inefficiencies in contact centres, benefiting both customers and teams alike.
For customers, streamlined processes and unified customer data can lead to faster responses and solutions. They do not have to go through the hassle of repeating themselves or waiting on operators to locate their information. Insights drawn from unified data, including customer history, conversational insights, preferences, and AI-derived traits such as sentiment, predicted lifetime value (LTV), and churn propensity, can also create highly contextualised and personalised interactions, which can keep customers happier and translate to greater loyalty and customer LTV for the business.
Businesses and agents also stand to gain. Reduced instances of app switching, better access to recommended responses, and automated wrap-up reports can enhance overall productivity. This approach addresses issues such as long waiting times, repeat calls, and high transfer rates, ultimately leading to service and operational performance improvements. Businesses can streamline operations further using predictive analytics, which reduces workload and search time for agents.
The next race: Embedding CDP data into the contact centre
Harnessing the potential of first-party data and empowering agents is essential for modernising contact centres. Collecting first-party data from various sources and integrating it into real-time service interactions can provide agents with more comprehensive information than traditional customer relationship management (CRM) systems. Using a customer data platform (CDP) alongside CRM can help contact centres better understand customer behaviours.
Leaders in customer experience can rely on CDP data because it offers real-time insights and supports the shift towards omnichannel. The real-time nature of CDP data allows leaders to respond swiftly to customer needs and preferences as they arise. CDPs’ ability to consolidate data from billing systems, data warehouses, and marketing automation platforms also makes it easier to transition across channels without losing context or information.
With the emergence of large language models and the memory capabilities of CDPs, agents now have access to personalised assistance during customer conversations. This development changes the traditional approach to agent training. Lengthy training sessions confined to a classroom setting, which also incur additional costs, are less necessary. Instead, agents can engage with customers more proactively, knowing that their AI assistant can help with complex scenarios that may arise occasionally.
Navigating transformation
As with every new technology, businesses need to be mindful of using AI safely to harness customer data and build transparent and trustworthy systems. According to Twilio’s recent State of Customer Engagement Report, 47% of businesses in Singapore consider balancing security and customer experience their most pressing challenge this year. Protecting customer data and navigating the complexity of regulations were also identified as top challenges.
Incorporating privacy and security features and principles into the development lifecycle of new technologies can support the compliant and responsible use of customer data. The report also found that almost half (48%) would trust a brand more if it disclosed how customer data is used in AI-driven interactions. Additionally, six in 10 Singapore consumers ranked customer data protection, alongside transparent communications such as clear terms and conditions, return policies, and privacy, as the most effective way to maintain trust.
As customer expectations and business needs evolve, traditional contact centres must also keep up with the times. Improving customer experience requires adopting modern technologies that ensure data protection and transparency. This shift involves moving away from outdated models and implementing scalable solutions that can meet business needs. Modern contact centres should be capable of rapidly adapting to changes and providing excellent customer service.
