FINAL WORD
Ravi Saraogi , Co-founder and President , Uniphore APAC scale up their agents , but also eliminate costly humanerrors that occur from overburdened agents to deliver great customer experiences .
Additionally , Natural Language Processing ( NLP ) capabilities can track customer and agent-centric patterns across voice , email , text , or chat , offering vital insights to highlight critical points to be addresses in the customer journey .
Enhancing experiences through automating after-call work
Equipped with insights that help provide a better understanding of customer intent and sentiments , an AI platform can help businesses increase selfservice and automation rates . This effectively resolves transactional interactions such as paying bills , basic service inquiries and tracking usage among others to increase agent efficiency within contact centres and reduce response times when dealing with customers .
Intelligent virtual assistants ( IVA ) can lend a hand to
enhance an organisation ’ s self-service operations . These Machine Learning systems can process customer questions and deliver appropriate next steps to complete a customer ’ s self-service experience . Utilising IVA alongside an AI platform can help cultivate an optimised , seamless CX .
Reducing friction in the customer and agent experience
Enabling agents to be more productive through conversational AI tools is another fundamental approach to improving CX . By utilising AI to guide agents on their next best actions while automating tedious tasks using robotic process automation , contacts centres can make every agent their best agent without weeks and months of classroom training and on-boarding . Not only are they able to quickly
So , what happens next after the conversation ends with the customer ? What takes place post-call is just as important to business outcomes for the telecom industry as what happens during the call itself .
Some of these after-call work ( ACW ) includes summarising the call , updating systems , and fulfilling promises made during the conversation . Having a conversational-AI platform enables automation of repetitive tasks and end-to-end business processes . For example , the platform can listen and transcribe conversations in real-time , automatically creating a call summary for the agent to analyse once the call ends . This improves agent performance and efficiency , increasing their capacity to handle more convoluted customer inquiries .
Managing promises
The final approach addresses promise management – a strategic component in any customer conversation . It directly impacts call handling times , wait times , and customer satisfaction and loyalty as measured by the net promoter score ( NPS ). Missed promises result in a significant negative impact on NPS typically . Using robotic process automation ( RPA ), promises and commitments made by agents are logged in real-time during each conversation whereby follow-up actions and insights that align with customer expectations are automatically provided immediately after the call .
As Egypt takes a step forward into a highly connected era , telecoms need to take bigger , bolder steps than ever before to improve customer and agent experiences . The telecom industry has become fundamental to how societies operate and progress forward . Conversational AI will serve as the cornerstone for augmenting every conversation , from transforming the customer and agent experience to driving customer satisfaction while generating greater loyalty and revenue . Understanding how to keep CX conversation-centric to connect with customers better is imperative for the telecom industry as it will ultimately enable a business to deliver a positive , seamless experience for customers and agents alike . p
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