Employ sentiment analysis and text mining to improve customer experience
Sentiment analysis and text analytics are fueled by smart and advanced language algorithms and machine learning algorithms. Other methods rely more on linguistics, others rely more on machine learning and deep learning. Hybrid AI methods though are more effective as they combine the best of linguistic and machine learning/deep learning methods. Also, granularity of analysis and sentiment is very important too.
These algorithms analyze customer feedback and allow you to spot themes and topics discussed, classify them, identify context and opinions, quantify the negative and positive feelings of customers and associate them with features of products and services. Trends, preferences and other projections based on the analysis are part of the actionable insights generated. Using metadata in the analysis offers deeper insights. Through the analysis, the elements of customer experience are unfolded.
- Customer care
Customer service and support teams can monitor your overall customer satisfaction. The teams can see the moods and impressions of your customers before offering support. It is an effective service-based approach that increases satisfaction and helps you understand the big picture.
With text mining and sentiment analysis, the team can handle large volumes of feedback at once, especially when chat volumes are at a peak. It takes a moment to realize which chats require more attention and which offer a smooth experience. With text analytics and sentiment analysis, you can make your customer service more adaptable. Feedback is gathered in one place from different channels, categorized, timely prioritized with relevant alerts and the team has all the necessary elements (i.e. opinions, sentiment and complaints about product features, purchase conditions, distributors, logistics, customer service etc.) to decide fast how to react in each case. The reaction should involve empathetic statements and getting prepared to solve issues in one interaction with the client. The level of customer satisfaction is boosted having a positive impact on the overall customer experience and minimizing customer churn.
Marketing teams can not only monitor customer sentiment but also detect more direct opinionated changes to your brand and identify the reasons for such changes. Insights can contribute to maintaining your brand appreciation and image.
Marketing and advertising teams can improve the message your brand sends to customers. Creating personalized and highly relevant campaigns based on the insights generated by text mining and sentiment analysis of your customer feedback can increase customer engagement and create positive customer experience. This is important as customer experience begins from the very first contact of the customer with your brand. As Philip Duffield, the managing director of Advertising Cloud, Adobe EMEA, mentions that “[t]hose that can root campaigns in deep audience intelligence and marry them with engaging real-time content delivered across the right channels, will achieve relevance and personalization at scale.”