5 Effective Ways to Improve Customer Support with Big Data Analytics

With consumer awareness at an all-time high, the age-old saying “The customer is king” is even more critical in a modern business ecosystem. Along with getting the right product-market fit with a high-quality product or service and correct positioning, customer support can become a critical part of long-term success.

According to Salesforce research, 89% of customers are likely to repeat their purchase after a positive service experience. For companies that are focused on delivering a flawless customer experience, big data analytics can play a vital role in achieving that goal.

Businesses don’t need to rely on speculation and guesswork to deliver a better customer experience. Big data analytics provide businesses with actionable insights to effectively improve customer support. However, most companies struggle to understand how big data analytics can positively impact customer experience.

Here are five effective ways that can help you improve customer support through big data analytics:

Automated predictions

Integrating big data analytics into your customer service operations can help deliver automated predictions on a regular basis. This not only helps to offer personalized nudges to the customer, but can also act as a driving force for the customer service team. A BI platform that brings predictive power to analytics can provide insights that can help create a positive customer experience by analyzing customer behavior. With information about customers and their expected behavior in advance, the customer service team is better equipped to handle potential objections and improve customer satisfaction scores.

Advanced Analytics

With no-code analytics, companies can extract customer insights and track agent productivity without the help of a data scientist. The customer service team can use the advanced big data analytics features to track, measure and improve the performance of various processes. Advanced analytics can help a business with creating systemized insights and end-to-end data solutions. Based on the metrics you track, you can take action to improve specific areas of customer service with the right metrics in place.

sentimental analysis

According to McKinsey Research, 70% of the customer journey is determined by how they feel treated. Therefore, understanding how customers feel emotionally and building an ecosystem to retain them is crucial. Big data analytics allows a business to undertake sentiment analysis in a customer journey. With qualitative and quantitative feedback, big data analytics can analyze sentiment to improve customer support.

Streamlined customer support processes

Big data analytics can be key to streamlining customer support processes and saving customers time. For example, if the customer is frequently redirected from the IVR, it may be useful to improve the quality of the agent or increase the efficiency of the IVR menu. Likewise, if the abandonment rate is higher than average, a business should consider including a callback option rather than keeping customers on hold for an extended period of time. Similar gaps in processes can be uncovered using big data analytics in customer support, helping to streamline the level of service to the end customer.

Improves problem solving ability

Interacting with customers and resolving their issues is an essential part of customer service. It’s not just the common issues that require quick resolution, but also the complex issues that are unusual and rare. Introducing big data analytics into customer service operations can help improve the problem-solving ability of the customer support team. Big data analysis can help detect and analyze variants of various queries and determine the correct answer. You can also use the big data analytics capabilities to build customer self-service solutions to improve the customer experience. This helps in understanding your customer’s needs and making decisions to solve the challenges customers are facing.

Modern brands need consistent direction and a strategic approach to improving customer support operations. The introduction of big data analytics can help analyze structured and unstructured datasets for better understanding of consumer behavior. Companies can monitor their performance and are better placed to react to future events and results. With real-time analytics, a business can be expected to significantly improve service level and customer experience.

(The author is Mr. Naren Vijay, EVP – Growth, Lumenore and the opinions expressed in this article are his own)

Joseph P. Harris