Tailor Customer Experiences With Artificial Intelligence Related Articles 12 Top Uses of Artificial Intelligence in the Contact Centre Our Top Use Cases for AI in Customer Service Artificial Intelligence in the Call Centre: Survey Results Artificial Intelligence in the Contact Centre: What You Should REALLY Know © Black Salmon - Adobe Stock - 1064461262 Filed under - Industry Insights, CallMiner Delivering positive customer experiences (CX) is critical – it’s how organizations drive loyalty, competitive differentiation, and revenue growth. Now more than ever, it is essential for businesses to benchmark their present CX performance and prepare to better meet customers’ evolving expectations. Artificial intelligence (AI) provides a golden opportunity for tailoring positive customer experiences. AI-powered tools enable contact centres to handle more complex situations that used to require human intervention, provide customer self-service options, and extend enhanced support across contact channels. Today, AI is being layered with current conversation intelligence solutions and emerging techniques encompassing machine learning (ML) and robotic process automation (RPA). Automating aspects of contact centre operations makes it possible to serve customers in new ways, raise customer satisfaction and give businesses more insight into their customer interactions. Read on for our list of use cases and proof-points to guide your AI-powered customer experience strategy. Use Cases & Proof Points AI by itself does not improve customer experience or agent productivity. Rather, this technology streamlines processes – often mundane or repetitive processes – and can uncover trends or patterns within data. It’s through AI that humans can make more informed business decisions and drive improvement. Here is a sampling of how combining AI-powered conversation intelligence solutions can benefit contact centre operations. Improve First Call Resolution (FCR) As a live call or online chat progresses, AI can predict the direction the interaction will take, accurately forecast whether the customer will make a future contact, and guide agents accordingly. Create Better Customer Experiences Across Departments Engagement and analytics data can be used to assist throughout the customer journey, from sales to onboarding, technical assistance, billing and payments. Increase Customer Satisfaction AI can predict whether a customer will be satisfied or dissatisfied with a specific action an agent could take, thereby helping agents take approaches to deliver better outcomes and experiences. Predict Customer Churn AI is used to predict churn by analyzing historical data to identify at-risk customers. These insights can help companies proactively take action to engage customers and get the chance to improve customer satisfaction. Identify Upsell Opportunities AI can rate how likely a customer is to respond to an upsell request and prompt agents to upsell likely prospects and avoid spending time on low-likelihood customers. Improve Agent Training The predictive powers of AI can be used to forecast how well agents will perform in different situations and tailor individual training and coaching strategies. Using Data to Train Chatbots Call transcripts from your call centre are a data goldmine to train chatbot interactions. Customer service agents see the value of such capabilities – 64% believe AI-powered chatbots will enable them to provide a more personalized experience to customers. Reduce Agent Turnover and Improve Job Satisfaction Approximately three quarters of organizations that use AI and ML said their employees are doing more interesting work as a result of ML-enabled processes, and 78% said ML-enabled processes will result in improvements in job satisfaction and retention. Prevent Fraud AI can detect fraudulent activity based on when, how often, and by which channels an individual contacts a company, the questions they ask, the requests they make, and the specific words, phrases and persuasive techniques used. AI represents the next step in the evolution of CX. It gives new value to old, previously untapped data and helps organizations continuously make experiences better by learning what works and applying the results. This blog post has been re-published by kind permission of CallMiner – View the Original Article For more information about CallMiner - visit the CallMiner Website About CallMiner CallMiner is the leading cloud-based customer interaction analytics solution for extracting business intelligence and improving agent performance across all contact channels. Read other posts by CallMiner 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: CallMiner Published On: 7th Oct 2022 Read more about - Industry Insights, CallMiner Recommended Articles 12 Top Uses of Artificial Intelligence in the Contact Centre Our Top Use Cases for AI in Customer Service Artificial Intelligence in the Call Centre: Survey Results Artificial Intelligence in the Contact Centre: What You Should REALLY Know Related Reports White Paper: How to Operationalise AI Workflows in the Contact Centre White Paper: How to Drive Business Improvements with Customer Insights eBook: How Customers Can Lead Your Business Transformation in 2024 White Paper: Five Secrets of Top Performing Contact Centres Contact Centre Reports, Surveys and White Papers Get the latest exciting call centre reports, specialist whitepapers and interesting case-studies. Choose the content that you want to receive. Contact Centre Reports, Surveys and White Papers Invites to exclusive Webinars & Events Weekly Newsletter