5 Powerful Ways Data Analytics and AI Are Enhancing Customer
To keep up with empowered customers and nimble competitors, you must change how your firm provisions and manages data.”
—Forrester’s The Data Management Playbook For 2021
Data plays an increasingly important role in today’s technology-powered business landscape. Organizations rely on data to understand customers, design innovative new offerings, enhance operations, and guide business decisions. Data also powers technologies like Artificial Intelligence (AI) and Machine Learning to allow them to deliver world-class service and memorable experiences that garner customer loyalty and stickiness.
Here’s how AI and data analytics are helping to reinvent customer service.
AI-driven Predictive Analytics to Personalize Customer Journeys
World-class customer service starts even before a sale is made. This makes it necessary for organizations to understand customers better. Organizations can leverage customer data to create relevant customer micro-segments and mini-clusters based on a deep understanding of their true intent. Knowing what matters to the customers in these segments enables organizations to customize the journey for them and deliver experiences that are contextually relevant for each customer.
Customer interactions have now become complex and fragmented as they seamlessly span multiple channels. Even in the face of that complexity, with a clear picture of the needs and motivations of their customers, organizations can apply comprehensive predictive analytics, and take steps in real-time to proactively provide information, handle objections, and ease any friction across all preferred customer channels or touchpoints.
With Machine Learning, organizations can learn from the data gathered from previous customers and make predictions about what is likely to drive conversions for new customers. The organization can take very specific action to move them ahead in the buyer journey. They can provide personalized recommendations, pricing options, and bundled offerings at the right time to increase the probability of a favorable outcome for both the user and the firm.
Anticipate and Meet User Needs
With the power of data and AI, service organizations can predict user behavior, and anticipate their needs, even after the sale is made. This enables them to engage with customers as they transition into becoming users at the right time and on the best channel with targeted support messages, personalized conversations, and the best service for an audience of one. Proactive support can help customers know more about the product they have purchased, the best way to get the most from it, the various options for seeking support, and possible upgrade and maintenance plans. It will also make them feel that the brand they have chosen values them and their business.
Anticipate and Meet User Needs
With the power of data and AI, service organizations can predict user behaviour, and anticipate their needs, even after the sale is made. This enables them to engage with customers as they transition into becoming users at the right time and on the best channel with targeted support messages, personalized conversations, and the best service for an audience of one. Proactive support can help customers know more about the product they have purchased, the best way to get the most from it, the various options for seeking support, and possible upgrade and maintenance plans. It will also make them feel that the brand they have chosen values them and their business.
Seamlessly Adapt to Customer Communication Preferences
The current service landscape, particularly in a post-COVID world, is very different from what it used to be. Now, customers use multiple channels – usually between 3 and 5 – to contact customer service. A majority (86%) also expect call centres to provide a self-service option so they can take charge of their own issue without going through the rigmarole of having to call a contact center. Machine Learning automatically adjusts preferred channels based on who the customer is so agents can interact with customers one-on-one. With data analytics, they can be there for them on their preferred channel to ensure a smooth, seamless service workflow, all the way from the first contact to issue resolution. With CRM integration, they can also view customers’ contact details, interaction history, purchase history, and other relevant information, so they can make informed decisions to ensure that every customer feels valued and appreciated. This not only ensures great customer experiences, but also has a positive impact on the company’s CSAT, loyalty, and ultimately, profitability. With predictive analytics, they can improve call completion times, measure customer satisfaction, and even reduce churn by accurately predicting and proactively offering what customers need.
Deliver Quick Solutions with Automated Chatbots
58% of consumers are willing to sever a relationship with a business following a poor customer service experience. Virtual agents and chatbots can minimize such eventualities. Powered by AI, Machine Learning, Natural Language Processing, and other related technologies, automated bots effortlessly answer common or repeated customer questions with relevant, timely information in a user-friendly, non-intrusive format. Customers can connect instantly to an automated agent to initiate an interaction in real-time. Moreover, since live chat allows them to multitask without having to wait for a response like they would normally do in a voice-only service interaction, they can do this without disturbing their busy schedules.
If the issue is too complex and the chatbot cannot provide the relevant answer, they can automatically reroute the conversation to a real human agent. The handover is seamless with minimal impact on the customer’s experience. By taking care of repetitive queries, bots allow live agents to focus on interactions where human inputs are more critical. This enables the contact centre to deliver better and more relevant solutions, along with personalized experiences that boost brand loyalty.
Improve and Maintain Service Delivery Quality
Improve and Maintain Service Delivery Quality Modern AI and data analytics tools can monitor interactions in real-time. This is useful for training and developing agents, and for improving their performance. Earlier, supervisors had to reactively check call logs to review performance, identify gaps, and decide on corrective actions. But now, they can proactively identify potential issues, and implement corrections appropriately and quickly. This kind of proactive information-gathering, analysis, and action helps the service organization improve its service delivery quality, which directly impacts customer satisfaction. Real-time AI-led monitoring also provides agents with relevant, action-oriented insights about their performance, which encourages them to take accountability over their own improvement goals. Service organizations now have access to vast stores of customer data. By using AI, Machine earning, and data analytics organizations can understand their customers, shape their journeys, drive intelligent engagements, and deliver meaningful experiences that customers will cherish. Of course, these technologies will never replace human communication, decision-making, and empathy. However, if harnessed and optimized well, they can create powerful synergies that enhance customer service, and enable organizations to develop stronger, trust-based, mutually beneficial relationships with their customers.
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