In today’s digital age, companies can get a comprehensive or 360⁰ view of customers by accumulating data from the various touchpoints that a customer may use to contact a company. This data can then be tapped to determine customer patterns or trends in order to better target their marketing offers, and enhance their relationship with customers. According to Accenture, 75% of consumers are more likely to purchase from a company that knows their name and purchase history. Imagine the possibilities if that same company also analyzed relevant data from the customer’s social media posts and other online reviews. Using AI-driven predictive analytics tools, companies can draw insights from end-to-end customer data to track, predict, and personalize the customer’s journey, with the ultimate goal of boosting brand loyalty.
Strengthen Customer Relationships with Emotion AnalyticsCustomers want to feel acknowledged and understood, especially when faced with a challenge. This is why emotional analytics features so prominently in many technological innovations designed to enhance customer retention. Based on research, more and more companies will be taking customer emotions into account in 2021 and beyond. Machine learning can be trained to recognize the embedded emotions in language and determine the customer’s mood. Analyzing these emotions can be used to understand a customer’s experience with a company product, new packaging, or interaction with a representative of the company, and to uncover any weak links that cause negative customer reactions, with the ultimate goal of improving relationships with customers.
Deliver Convenience with Computer Vision-Powered Self-ServiceAI-based chatbots contend with the massive number of support requests that often overwhelm customer service centers by empowering customers to resolve minor issues on their own. Computer vision technologies – such as object recognition, facial recognition, image to text, and image similarities – can add significant value to a company’s self-service platform, allowing customers to visually interact with bots that can guide them to self-resolution.
Computer vision has become a key customer service technology trend due to its many capabilities. For instance, it can add essential data to a customer’s profile based on visual data, help predict issues before they even happen, and effectively route the customer’s case to the relevant agent if self-service is unsuccessful.
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