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The Power of Intelligent CX Discovering Trends in the Age of AI

The last few years have been marked by an overwhelming amount of change for customers and the way services are delivered. From the adoption of leading technologies to tectonic shifts in customer channel preferences, companies have struggled to keep pace with customersu2019 evolving needs and expectations.<br><br>However, companies have tapped into newer technologies, such as the internet of things, AI and ML algorithms, Martech platforms, and a growing number of digital media tools that can formidably advantage them when combined with agile methods.

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The Power of Intelligent CX Discovering Trends in the Age of AI

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  1. The Power of Intelligent CX: Discovering Trends in the Age of AI successive.tech/blog/power-of-intelligent-cx-discovering-trends/ The last few years have been marked by an overwhelming amount of change for customers and the way services are delivered. From the adoption of leading technologies to tectonic shifts in customer channel preferences, companies have struggled to keep pace with customers’ evolving needs and expectations. However, companies have tapped into newer technologies, such as the internet of things, AI and ML algorithms, Martech platforms, and a growing number of digital media tools that can formidably advantage them when combined with agile methods. Hence, businesses that want to surpass—or simply catch up with—early movers need to consider their data and technology foundation and how leading technologies can add value and personalization to their CX. In this article, we explore how to assemble high-quality customer experiences using technology and customer data and emerging trends in the Age of AI. What is Intelligent CX, and how does it create an impact? 1/8

  2. Customer experience, driven by the adoption and thoughtful implementation of advanced technologies, such as AI, automation, and data analytics, is what we call intelligent CX. When all these advances work together, not as discrete, standalone elements but as parts of a greater whole, business experiences create a lasting impression on all touchpoints of a customer’s journey. These disruptions require all types of organizations to engage their target customers in new ways with technology—from online car shopping to leveraging self-service; digital has become ingrained in delivering all kinds of customer experiences. Businesses can potentially derive 75% of the value for their use cases in customer experiences from Generative AI. The adoption of advanced technology is only part of the whole story. The temptation to sit back and wait to see how these technologies evolve and change the customer experience is worth the wait, but it must be resisted. A compelling CX strategy must start with understanding what the customer wants and then delivering it with the help of these tech advances, such as who the customer is, what they want, what job they do, and even how they feel about themselves and most importantly, about the brand they choose. – Gaurav Malik, Chief Strategy Officer, Successive Digital For example- Brands like JPMorgan Chase, Starbucks, and Nike have announced that efforts made toward personalized and seamless omnichannel experiences are at the core of their corporate strategy. They have attained the ability to capture, analyze, and utilize personalized customer data at scale, as well as learn how to use AI to understand, shape, customize, and optimize the customer journey. Trends for Intelligent Customer Experience in 2024 and Beyond AI AND INTELLIGENT EXPERIENCES Generative AI for a personalized and interactive journey Generative AI poses an opportunity to personalize customer interactions better. Personalization has taken center stage in recent years for creating unique customer experiences, and generative AI can help achieve this. Generative AI models like ChatGPT and Dall-E work by taking inputs such as text, image, audio, video, and code and generating new content into any of the modalities mentioned. 2/8

  3. These models such as ChatGPT are based on statistical models and utilizes deep learning to analyze patterns in large datasets and then replicate these patterns to create new content such as text, images, music, or videos. These AI systems are trained to generate new data rather than predict outcomes based on existing data. They operate by predicting the next piece of data in a sequence, whether it’s the next word in a sentence or the next pixel in an image. The technology behind generative AI involves neural network models that use artificial neurons and their interconnections to create innovative content across various media types. Gartner reveals that by 2025, 80% of organizations will be applying generative AI technology in some form to improve agent productivity and customer experience. For example- Coca-Cola curates personalized marketing campaigns using Generative AI models. These models analyze individual consumers’ demographics, interests, and preferences, including social media interactions and purchase history. Here’s how Generative AI can help Content generation- Generative AI can create tailored personalized content assets that target individuals based on their preferences and behavior. Whether it’s a personalized SMS, an email, a social media post, or a chatbot response, generative content can capture audience’s attention. Data Analytics—By analyzing the customer’s data and preferences from different channels, generative AI consolidates this information to provide a more comprehensive understanding of customer preferences and behaviors for a more refined strategy. In short, any organization that needs to produce clear written materials potentially benefits from generative AI models. Organizations can also use generative AI to create more advanced-level materials, such as higher-resolution versions of medical images. And with the time and resources saved here, organizations can pursue new business opportunities and the chance to create more value. Chatbots as digital agents Chatbots have been around for over a decade and now have undergone a supercharged transformation as AI is giving chatbots a voice with the most advanced models and the ability to interact with the customers. Incorporating natural language processes and machine learning is giving virtual customer assistants the ability to determine not just what rules-based action to take based on a word but to understand the meaning of words in different combinations, have real conversations with the users, ask questions, and do actually something for the customer. 3/8

  4. The best part about the adoption of these digital agents is that they surpass the concept of on-hold music, which indeed created friction points in customer service. With chatbots, you no longer have to wait for the next agent to serve you; they are always available at your fingertips. Transparency in AI-driven CX With the increased frequency of data breach cases, both customers and companies have now made transparency in intelligent customer service a key priority, as they believe that lack of transparency could lead to increased customer churn in the future. The industry demands transparency to establish trust between the customer and the provider. This trust becomes especially important when dealing with sensitive information that reveals a person’s identity, health history, and financial status. No customer wants to feel like AI is snooping on them or making their data available to cons. Hence, by incorporating human oversight and intervention in AI-driven processes, companies ensure accountability and mitigate the risk of algorithmic bias, errors, or data breaches. Artificial intelligence is a relatively newer technology and hence, complete adoption of AI will take some time. Transparency in AI provides a clear explanation for why things happen with AI and helps customers understand the reasons behind AI’s data-driven decisions and actions so they can ensure they’re fair and reliable. DATA-DRIVEN EXPERIENCES Leveraging data in real-time for modified experiences Another report by Gartner reveals that 71% of B2C and 86% of B2B customers expect companies to be well-informed about their personal information throughout an interaction. Now, Imagine a scenario where you visit an online store, and it suggests a specific jacket, considering your preferred style, past purchases, and even the local weather forecast! This jacket fits you perfectly, and the customization approach enhances your satisfaction and loyalty and makes customers feel valued. For example- Messaging apps like WhatsApp and Facebook Messenger use real-time data on user location, activity, and preferences to deliver contextual messages and notifications. Have you ever received a promotional offer from the restaurants you were just googling? It’s because they use your data in real-time and send targeted offers and promotions to nearby users based on their current location and dining preferences. 4/8

  5. Putting data to work in real-time modifies customer experiences as the expectations of speed, foresight, and hyper-personalised delivery of relevant information is closely related to how well the data shows results. Driven by these granular real-time customer insights, companies are fundamentally reshaping the industry by enabling customized experiences based on individual data and their preferences. Incorporating security throughout the CX Data, both in transit or at rest, must be secured. Organizations in customer services are understanding this need and bringing ways to win customers’ trust with their personal and confidential data through intelligent customer service. Every year, consumers lose billions due to fraud, whether breached accounts, stolen identities, deepfakes, or scams. Now, with the growing adoption of AI, customers have become suspicious of the businesses that are charged with protecting their data. With the increased digitization of customer interactions and the scrutiny of customer communications, safeguarding sensitive data is more important than ever. The easiest and the most worthy way is to implement encryption technologies for data transmission and storage and establish stringent access controls to protect sensitive customer information. Additionally, many companies are already building upon customer trust and loyalty by prioritizing data security measures, safeguarding their reputation, and fostering long-term relationships. Data-driven personalization and predictive analytics The trifecta of data, personalization, and predictive analytics are closely linked to one another. When we put data to work on the patterns, they reveal predictive insights, which are used to build personalized user experiences. By analyzing vast datasets encompassing customer preferences, behaviors, and interactions, businesses are segmenting their audience and delivering recommendations that resonate personally. For example- Netflix collects vast amounts of data on user interactions, including viewing history, ratings, search queries, and time spent on the platform. The collected data is then cleansed and processed to remove irrelevant information and handle missing values. To gain insights from this data, Netflix employs machine learning algorithms such as logistic regression and gradient boosting machines to predict user churn based on historical user behavior. The churn prediction models are integrated into Netflix’s recommendation engine, allowing the platform to personalize content recommendations and retention strategies for individual users. 5/8

  6. IMMERSIVE EXPERIENCES Immersive experiences are the future of online shopping The growth the e-commerce industry has seen in the past few years is incredible. Almost anything can be ordered online and delivered to your doorstep in a matter of days (if not minutes). As a result, customers take convenience as a given and want more of the status quo. This rise of customer needs and the immediacy of delivering products and services is partly fueled by the lockdown imposed during the pandemic and partly by the technology advances happened during that time. While companies see the potential here, they are willing to invest in what delights customers the most when making the purchase by offering immersive experiences. According to Shopify, businesses with 3D and AR content have seen a 94% increase in conversion rates. One of the real-life implementations of immersive technology is seen in Ikea; their Place app allows users to visualize how furniture will look and fit in their homes using augmented reality. North Face’s digital shopping assistant helps customers find the perfect outdoor gear through conversational AI. The idea is when completing a purchase; customers need to feel that they really understand the product or service, which should also inspire the same level of confidence. For this, immersive technology has taken the front seat. Customers today are so engrossed in their purchasing decisions that they’ll even watch live-streamed sessions to gain shopping advice. Virtual voice assistants for handling complex issues One of the unsung trends, or, say, the hero of intelligent customer experience, is virtual voice assistants, who carve out a more advanced role focused on handling complex and escalated issues. Almost 80% of customers expect chat agents and support representatives to assist them with everything they need. The brimming line between support and sales has begun to blur through virtual assistants. A decade back, customer support teams that worked through call centers have now transitioned through virtual call agents and chatbots. However, customers harbor no complaints about this massive shift; they still want the option to talk to a real human being. 6/8

  7. Hence, instead of relying completely on the digital-first virtual bots, organizations are introducing virtual voice assistants as an option. When companies create a seamless transition from chatbots to voice channels for handling complex issues, consumer confidence in the former rises. That, in turn, becomes a virtuous cycle in which customers feel increasingly satisfied with reaching out via digital channels, thus lessening demand for phone options. VR to captivate audiences and drive brand affinity Virtual reality can be used widely to increase brand awareness and customer’s trust in the brand and its point of view. The New York Times “The Displaced” VR documentary provided a firsthand look at the lives of refugee children, resulting in a 15% increase in subscriptions. This way, VR can be used well to transport users to virtual environments related to their products or services or reflect on a message. These experiences allow audiences to engage with the brand memorably and interactively. How to Implement Intelligent Customer Experiences? Companies across industries have realized the importance of putting personalization at the center of their business strategies. Still, focusing on “what customers think of us” vs. “what customers think of themselves” is an overlooked opportunity to mend. To support a positive shift in customers’ self-perception, organizations can apply the following approaches: Focus on the customer-first approach. A Gartner study found that if customers “realized something new about their needs or their own goals,” they were 1.73 times more likely to buy. Hence, the first step to implementing the intelligent customer experience is putting customers at the center of organizational decision-making rather than simply focusing on profits or products. Businesses can tune in to their customers’ needs and deliver experiences they appreciate when they take this approach. With the help of advanced technology, companies can mend their strategies in favor of the customers. Start with a core data set and build to improve accuracy. Most organizations face challenges with data quality and availability, and without data, this transition towards intelligent customer experience-driven organizations is a non-starter. However, companies can start by utilizing the granular level of customer data to create a hypothesis of the different data sets and identify the measurable attributes for inclusion in the predictive model, like binary properties of purchasing decisions or annual spending. Over 7/8

  8. time, understanding which features are significant in the machine-learning model—and comparing those with the hypotheses—can help organizations recognize where data may be inaccurate or incomplete and adapt their data-acquisition strategy accordingly. Invest in the right partner. Most companies do not have a good grasp on what an technology-driven digital experience can do for their customers. When we discuss about intelligent customer experience, AI, data and immersive experiences lays the foundation to delivering what customers crave for. Still, you can’t harness the full power of ICX without the right partner that co-innovates with you. At Successive Digital, we co-share a vision and believe in the transformative power of personalized, consistent, memorable customer experiences that create a lasting impact on your customers. As an innovation-intensive customer experience company, we help you strengthen your organization’s way of delivering CX with a strategic thinking approach, driving immediate, lasting, and measurable organizational impact. Get in touch with our experts. 8/8

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