customer service

‘Customer is the King’. This is always true, whatever business you are in or whatever product/service you are dealing with. Customer service plays a key role in brand differentiator in most of the businesses today. Gone are the days when you had to rely on historical data to analyze your customer’s experience. Advancement in Big data analytics has made life easy for professionals dealing with customer service. Furthermore, big data-enabled customer relationship management a holistic approach for today’s business. It has turned customer service more responsive and agile.

Customers’ preferences and the kinds of products that drive them to a set of products business is handling is worthy of analysis. Big Data analytics deals with such large data sets that are too complex for traditional data-processing application software. Not only that, Big data is capable of handling them adequately. Big data analytics collects, organizes, and analyses massive volumes of data to discover patterns and other useful information for a business to use. Let see how big data customer service is improving the overall business process of any organization.

Related post – 6 Factors which will change the Big data landscape 2020

What Does Big Data Mean for Enterprises?

Big data has many characteristics like volume, velocity, variety, veracity, variability, value, visualization, and validity. However, for any business, the three V’s have the main significance: velocity, volume, and variety.

For example, big data volume which is the quantity of data a business deals with. But if that data is not analyzed properly, there is no meaning in dumping the data. Similarly, to enhance the user experience, the data velocity and variety must be considered.

For marketing purpose, these 3 V’S must be capitalized off.

The Role of Big data in improving customer service

Big data analysis can help a business in the below parameters –

– To make them capable of making better decisions

– Generating high productivity

– Cost-effective operations

– Personalized customers’ needs

– Monitoring sales growth

– Upgrading customer service

Here are the 5 ways that helps business to improve customer service

1. Using Big data for personalized customer service

You may have thousands of customers for a particular product, but the reasons to choose that product may not be the same for each of them. Let say; a business is selling health drink. Now some segments of customers may have to pick it for health benefits. Some are for flavors, and some as a routine choice. Thus an analysis of these data can provide better insights on customer preferences, and the business can expand the options of the product based on that. They can make it more personalized for the users. This basically enables a company to know the customer’s needs before they ask for it.

It was a pretty daunting task in the past, but with the help of big data, it is now easier to analyze. Also, this not only acts as a boost for customer retention but also expands the customer base. As per one study, 5% retention of the customer can generate a 25% increase in profit.

2. Big data can reduce churn rate through multi-channel support

Customer support is an integral part of any business. And today, most of the customers prefer multi-channel support. It could be through phone calls, emails, social media platforms, chats, and so on. Furthermore, if a business cannot provide proper support to its customers, there is a high chance of an increased churn rate. How will a company know a customer’s preference on this and its capability to provide the necessary support? Big data acts as instrumental in this case.

Big data analytics helps you to understand how your customer service functions across different channels. The potential customer may indeed like a particular mode of communication. Still, the business doesn’t want to build only one state-of-the-art customer service channel while losing points on others. Through data analysis on agents’ knowledge, efficiency, response rates, etc., big data can show how to do and point out the details they should improve.

3. Enhances problem-solving efficiency

Big data customer journey is not limited to customer support. Interacting with clients and solving their issues is an essential part of customer service. Some problems are common, which a business may deal with every time and have ready answers. But some may be unusual and, if not responded immediately, may affect the business negatively. 

Big data analysis can detect and analyze all variants of users’ queries and problems and determine the same answers. This helps to enrich customer service agents with knowledge and efficiency.

4. Improved response time

Waiting time is a crucial factor when dealing with customer service. It is not expected that your potential customers, who are the business’s primary source of profit, will be waiting for long. The market study shows that customer recommendations on social media can increase the business profit by 25%. Using big data, it is not hard to calculate customer response time across multiple channels. This also helps determine the strong and weak points of the customer service process and improve the ones that slow down the process.

A business can recommend outsourcing the service if the request volume is high or don’t have enough capability to handle this analytics data’s requests. No doubt, decreased response time enhances the customer experience.

5. Customer service executive analysis

Whether a customer will stick to your business or look for others solely depends on his buying experience. As mentioned above, customer service plays a crucial role here, and it is part of the customer buying experience. Thus customer service executive needs to be competent and inclined towards customer interests on a 24/7 basis. So, as a business, you must be aware of how they are performing, their competency level, etc.

Big data analysis can give a business a better idea of a customer service executive’s average response time, hold time, abandonment rate, and other factors that might influence customer service productivity. This also minimalizes escalation issues. Based on the data analysis, employees may be provided with necessary training on customer handling.

Conclusion

Since brands need a more strategic approach to driving sales and excellent customer service, there is no better substitute for Big data analysis. Using big data, companies may analyze a vast set of complex data sets to gain essential aspects of customer behavior.

Additionally, with real-time big data analytics, a business can step ahead of the competition and improve the service dramatically. This could lead to a higher conversion rate and more revenue. Additionally, with big data, companies can monitor the products used by their customers; at the same time, it can proactively respond to future outcomes — no matter whether it is successes or failures.

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