Brands nowadays collect a tremendous amount of data on their customers. From purchase history to social media commentary, customer insights may be collected across multiple touchpoints. In addition, contact center metrics such as average handling time and first contact resolution provide data on how the customer experience is affected by service practices. Through close examination across channels, brands may use such valuable information to create richer customer experiences. Here are five ways big data can be used to improve the customer experience.
Metrics can say a lot about the experiences your customers are having. For example, longer average handling time (AHT) or low rates of first contact resolution (FCR) might indicate communication or organization issues that need to be resolved. Are agents able to contact supervisors efficiently when extra help is needed? Are agents well trained in using the CRM database? Understanding such metrics can help improve contact center practices and the overall customer experience.
Customer emotions play an essential role in their relationships with brands. Using big data to better understand how customers feel is therefore critical to connecting with them on an emotional level and winning their loyalty. Data sources may include formal surveys, call transcripts, social media comments, and virtually any other exchange between a brand and a customer. Brands should analyze both quantitative and qualitative feedback to make improvements to their service, such as using softer language, more emotionally charged marketing campaigns, and more personalized service.
Whenever possible, brands should do their best to streamline processes and save customers time. For example, if customers are re-routed frequently, it may be necessary to match agents to more appropriate roles or improve the efficiency of IVR menus. If abandonment rates are high, offering customers callback options may ensure that they don’t waste time being placed on hold.
Customer feedback and satisfaction scores may be used to improve communications among employees as well as with customers. For example, if customers complain about an agent’s tone or pacing in conversation, employees may be trained to enhance their soft skills and check with customers for comprehension before moving on to the next step. Similarly, if agents are not performing optimally because they spend too much time looking for peer support, better communication systems may be put in place to make service interactions more efficient.
Big data is also critical to implementing targeted marketing practices. For example, paying attention to click-through rates of links communicated through marketing emails, text messages and other channels can reveal whether or not a marketing strategy is leading to actual sales. In addition, geolocation data may also give brands opportunities to better target customers near brick and mortar stores or during the in-store shopping experience. Brands may use such information to share information regarding sales events and extra discounts that may be applied in-store. As brands collect various forms of data on their customers, a thoughtful and customer-centric approach to interpreting this data may lead to improved service practices and stronger customer experiences.
Interested in our solutions?