The wealth of customer data these days presents a challenging task for brands. Metrics such as abandonment rates, first contact resolution, and average handing time certainly provide insights into the quality of customer experiences being delivered. However, most brands also recognize the critical importance of big data in getting a truly global view of what their customers want. From email content to social media posts and text messages, unstructured data can be found across all channels and hold precious answers to how your brand can improve customer service. Here are six tips for using big data to transform customer experiences for the best.
Big data may be obtained from all your contact center channels, and beyond. Be sure to pay close attention to all social media sites, where customers have a high tendency to leave comments. Using advanced social listening tools to detect customer concerns can empower your brand to take proactive measures. SMS, email, and app communications are also full of valuable feedback, especially due to the growing trend of conversational commerce. More than ever, customers are showing a preference for communicating with brands through messaging, making direct demands that shed light on what they are looking for in a brand. Lastly, big data can be found in other places outside of mainstream channels: blogs and feedback surveys should also be analyzed.
Getting a comprehensive view of customer preferences will eventually enable your company to offer overall stronger customer experiences, including saving customers time. Specifically, big data may be used to save time at various points along the customer journey. For example, brands can track a customer’s preferred channel to ensure that all outbound communications are delivered on that channel. When customers are browsing a brand website, analytics may also be used to determine when live chat pop-ups should be offered to provide prompt customer service.
A variety of analytical tools may be used to offer enhanced customer experiences. For example, Vocalcom text and speech analytics offer critical insights into what exactly customers are saying about a brand, making sure that no comments are ever lost. The text analytics engine works across multiple languages to reveal customer insights for delivering stronger service. In addition, voice emotion recognition software can detect numerous emotions on both sides of a customer service call, enabling better customer relationship management. Lastly, the all-important net promoter score (NPS) is essential to measuring customer loyalty. Vocalcom software, for example, computes a brand’s NPS but also uses native text analytics to automatically analyze verbatim feedback and determine what companies need to improve and what is working well.
How about using big data to making marketing offers your customers actually want? Geolocation tools have changed marketing practices thanks to big data. Customers are increasingly mobile these days, and those who opt in for mobile marketing offers can benefit from perfectly timed messages that assist them in making a purchase or entice them to buy. For example, if a customer is geographically close to the location of a retail store, brands may offer a special discount or notification that there is a sale currently on at this location. Once customers are in-store, brands may also offer customer service options to assist them with purchase through channels like live chat or SMS. And don’t forget messaging apps: Customer conversations reveal direct information about their product and service interests, empowering brands using conversational commerce to offer bot-assisted personalized recommendations.
Big data can also be gleaned from internal contact center communications. Customer service agents frequently take notes on customers, which may be contained in a CRM database. Paying close attention to agent comments on customers can provide further insight into how to improve service practices and offer stronger marketing offers that cater to customer preferences.
Big data is also paving the way for cutting-edge self-service. For many brands, big data can help predict problems before they even arise, essentially eliminating a need for any customer-initiated contact. For example, if a utilities company detects a technical issue, it may be resolved before the customer is even affected. Using big data to inform customers proactively therefore saves them time. In addition, tracking deliveries to provide customers with real-time information prevents them from having to reach out for assistance.
By analyzing multiple sources of big data available on customers, brands may develop optimized customer service practices as well as stronger marketing campaigns for greater overall customer experiences.
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