5 effective ways to improve customer support with big data analytics
With consumers’ awareness level at an all-time high, the age-old saying ‘Customer is the King’ is even more critical in a modern business ecosystem. In addition to achieving the right product-market fit with a high-quality product or service and the correct positioning, customer support can become an integral component for long-term success.
According to Salesforce research, 89% customers are likely to make a repeat purchase after a positive service experience. For businesses focusing on providing an impeccable customer experience, big data analytics can play an essential role in achieving this target.
Businesses need not rely on speculation and guesswork to provide a better customer experience. Big data analytics equips businesses with actionable insights to improve customer support efficiently. However, most companies struggle to figure out how big data analytics can impact customer experience positively.
Here are the five effective ways that can help you improve customer support with big data analytics:
Integration of big data analytics in your customer service operations can help provide automated predictions regularly. It does not only help offer personalized nudges to the customer but can also act as a guiding force for the customer service team. A BI platform that brings predictive power to analytics can provide insights that can help build a positive customer experience by analyzing customer behaviour. With insights into customers and their expected behaviour in advance, the customer service team is better equipped to handle possible objections and improve customer satisfaction scores.
With no-code analytics, businesses can extract customer intelligence and track agent productivity without the help of a data scientist. The customer service team can use advanced capabilities of big data analytics to track, measure and improve performance of various processes. Advanced analytics can help a business with systemized insight building and end-to-end data solutions. Depending on the metrics you are tracking, you can take steps towards improving specific areas of customer service with the right measurement tools in place.
According to McKinsey Research, 70% of the customer’s journey is driven by how they feel they are being treated. Therefore, it is crucial to understand how customers feel on an emotional level and build an ecosystem to win their loyalty. Big data analytics enable a business to undertake sentimental analysis in a customer journey. With qualitative and quantitative feedback, big data analytics can analyze sentiments to improve customer support.
Streamlining customer support processes
Big data analytics can be essential in streamlining customer support processes and saving time for customers. For instance, if the customer is getting re-routed from the IVR frequently, it may be worthwhile to improve agent quality or increase the efficiency of the IVR menu. Similarly, if the abandonment rate is higher than the average, a business should look at including a callback option rather than keeping customers on hold for an extended period. Similar shortcomings in the processes can be uncovered using big data analytics in customer support which helps streamline the level of service to the end customer.
Improves problem-solving ability
Interacting with customers and resolving their problems is a critical customer service component. It is not just the regular run-of-the-mill problems that need timely resolution but even the complex ones that are unusual and rare. The introduction of big data analytics in customer service operations can help in improving the problem-solving ability of the customer support team. Big data analytics can help detect and analyze variants of various queries and determine the correct answer. You can also use big data analytics capabilities to create self-service solutions for customers to improve customer experience. It helps in understanding what your customer needs and making decisions to solve the challenges faced by the customers.
Modern brands need a consistent focus and a strategic approach to improving customer support operations. The introduction of big data analytics can help analyze structured and unstructured data sets for a better understanding of consumer behaviour. Companies can monitor their performance and are better placed to respond to future events and outcomes. With real-time analytics, a business can be expected to improve the level of service and customer experience drastically.
(The author is Mr. Naren Vijay, EVP – Growth, Lumenore and the views expressed in this article are his own)