AI-powered personalization: The future of customer experience
To stay ahead and meet the rising demand for personalized customer experience (CX), businesses need to implement next-generation customer engagement strategies. AI-based solutions in contact centers improve CX, employee performance, and overall operational efficiency. Recent AI developments – like automation, data analytics, sentiment analysis, and machine learning (ML) – enhance personalization without sacrificing time or resources.
This article explores AI’s functions that enable personalized CX in contact centers, the benefits of adopting this approach, current sector-specific examples, and potential future applications. It also discusses some limitations and potential solutions for business leaders to consider.
Improved call management and CX
AI-enabled automation and personalization can strengthen both the customer and employee experience by reducing the burden of mundane and administrative tasks on human agents.
One effective solution is the implementation of AI-enabled chatbots, which can handle routine inquiries and provide instant responses that decrease waiting times and increase customer satisfaction. With the help of ML algorithms, more complex situations can be escalated and/or routed to the most appropriate agents based on their expertise, ensuring that customers receive the best possible assistance.
According to customer surveys, 77% felt that AI-enabled chatbots were helpful for resolving simple issues, and 76% agreed that they provided faster responses[1].
By minimizing the time agents spend on basic tasks, employees can focus on delivering value-added conversations that improve CX and foster loyalty. Additionally, data analytics can enable identification of pre-existing customers and their requests, providing historical data that enhances engagement and avoids unnecessary repetition.
Implementing sentiment analysis can further enhance CX by providing valuable, real-time insights into customer emotions and attitudes. Tone, language, and sentiment expressed during customer interactions can be recorded and analyzed by AI to swiftly identify dissatisfaction that needs addressing. Agents are also able to better gauge customers’ emotional states, which supports them to engage with more empathy, driving personalized and beneficial interactions.
Business decision-making and operations
AI-powered personalization also brings significant advantages across employee wellbeing, business operations, and cost savings.
Firstly, it prioritizes employee wellbeing by empowering call center agents with intelligent tools that analyze real-time customer data. This enables them to deliver tailored and empathetic CX, which boosts customer satisfaction while reducing stress and fatigue among agents. As a result, job satisfaction and overall wellbeing increase.
The use of AI analytics also helps identify patterns in customer behavior, enabling optimized service offerings. These operational efficiencies lead to reduced call-handling time and improved performance.
Similarly, sentiment analysis provides oversight of recurring issues in customer – agent interactions, empowering leaders to address and resolve common customer pain points.
Lastly, AI-powered personalization generates substantial cost savings. Automation of repetitive tasks and increased agent productivity results in improved handling of higher call volumes, without requiring agents to work overtime or having to recruit additional staff. Additionally, AI chatbots and virtual assistants (VAs) operate 24/7, which reduces the need for round-the-clock human support.
Given the advantages to call management and overall customer experience, 91% of large organizations expect to increase their budgets for AI and data analytics to improve operations and customer care[2].
Challenges, limitations & solutions
AI-powered personalization is undoubtedly beneficial, but it also has its challenges. One significant limitation is the potential for over-reliance on AI algorithms, which can result in a loss of human touch and empathy in customer interactions. AI may struggle to fully understand and address nuanced emotional needs, leading to customer dissatisfaction.
Moreover, ensuring the technology can adapt to rapidly changing customer preferences and behaviors poses challenges. AI relies on historical data to make predictions and recommendations, which may become outdated or irrelevant as time goes on.
To address these limitations, call centers can adopt an AI–human hybrid approach. AI can handle routine queries, while human agents manage complex and emotionally sensitive situations.
Furthermore, call centers can implement processes to obtain customer feedback on their personalized experiences, which can be leveraged to improve the accuracy and adaptability of AI algorithms.
Another limitation is the risk of biased decision-making. AI algorithms learn from historical data that may contain human biases and prejudices and, if not carefully monitored and adjusted, these biases can be perpetuated in the personalization process, resulting in unfair treatment/exclusion of certain customer groups[3]. Ongoing monitoring and comprehensive data quality controls are necessary to identify and mitigate bias in AI models, and striking the right balance between AI automation and human involvement is crucial.
Additionally, effective change management and data-quality maintenance are essential for successful AI implementation. Ongoing training programs can equip human agents with the skills to work alongside AI systems effectively.
Future of AI-powered personalization
AI-powered personalization has already made significant strides across various sectors. In healthcare, chatbots understand patients’ symptoms, offer medical information, and schedule appointments. E-commerce companies use algorithms for personalized recommendations, enhancing CX and boosting sales. In finance, VAs can assist with financial planning and investment recommendations. These examples highlight how AI is already transforming customer experiences and will continue to do so.
In call centers, the adoption rate of AI-enabled chatbots for customer self-service is expected to reach 90% by 2024[4] with a substantial budget increase for AI implementation. Expected spending on AI is estimated to reach US$126 billion by 2025[5].
Generative AI, such as ChatGPT, has undoubtedly had an influence on these budget increases, as it has established itself as a major contributor in the evolution of chatbots. The advancements this technology has introduced allows chatbots to constantly review and integrate real-time data points to craft customized, human-like responses to customer queries and commands.
Business leaders understand the inevitability of integrating AI technology into their CX strategies to ensure business transformation in contact centers[6]. The most prominent channels that contact center executives are looking to transform include agent/voice telephone services (45.24%), robotic process automation (43.65%), and voice bots (42.06%). Other channels that organizations are looking to transform include intelligent assistants/agents (36.51%), email (34.13%), and interactive voice response (32.54%).
Natural language processing (NLP) will play a crucial role in AI development, enabling real-time analysis of customer inquiries Additionally, the continued development of AI algorithms means that 86% of business leaders are expecting to use the technology to minimize customer frustration[7].
The possibilities of high levels of personalization will result in faster and more accurate issue resolution, leading to increased customer satisfaction and loyalty.
Looking to the future
AI-powered personalization is a key component in the future of CX. Integrating AI into CX strategies transforms call management, boosts efficiency, and empowers employees. Automation, data analytics, and sentiment analysis enable tailored interactions, proactive issue resolution, and improved sentiment. While challenges exist, a hybrid approach that combines AI and human agents addresses challenges like biases and preserves the human touch, and ongoing training and monitoring mitigate biases and ensure data quality.
Advancements in NLP and ML will further improve AI’s ability to anticipate customer needs. The future of CX is bright, and business leaders have the opportunity to leverage AI-powered personalization as a powerful ally for success.
Author: Mark Angus, CEO of market research consultancy Genesis Global Business Services and Founding Partner of The World Source Marketplace for Global Business Services (GBS.World)
[1] Zendesk CX Trends 2022 report.
[2] NewVantage Data and AI Leadership Executive Survey 2022.
[3] What Do We Do About the Biases in AI?
[4] Zendesk CX Trends 2022 report.
[5] Artificial intelligence software market revenue worldwide 2018–2025.
[6] GBS.World Marketplace 2022 Buy-Side Demand Survey.
[7] MIT Technology Review Insights: Customer Experience and the Future of Work.
This article comes from magazine:
FOCUS ON Business #11 July-August (4/2023)
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