How to use big data to improve customer service

Providing customer service is a lot trickier these days than it was 20 to 30 years ago. Back then, the majority of the work was done via face-to-face or phone interactions. Today, we live a world that runs on the web. In fact, two in five people across the globe have access to the internet, and customer service can be approached from a wide range of channels. There is practically an unlimited amount of data that can be extracted from each interaction.

These days, brands are able to pull big data insights to gain a better understanding of their customers’ needs. This knowledge makes them better equipped to respond to requests with little to no disconnect.

Big data is growing at an exponential rate. The truth of the matter is that many companies aren’t using big data to its full potential. Opening up the data stream to your entire organization and properly combining insights across departments can do wonders in providing top-notch, consistent customer service.

Organizations of all sizes and backgrounds should be harvesting information at customer touch points to develop stronger relationships. Here is how you can use big data in your support operations to make customer service your strongest asset.

Collect data encompassing the entire customer journey

First and foremost, if you want a better understanding of what your customers need, you must understand how they interact with your brand at each touchpoint.

This means interpreting big data on customer profiles, behavior, workflows, etc. Believe it or not, a single piece of information is often the key to converting a customer. This is a very important concept to keep in mind when providing customer service. Some important criteria in examining data and identifying patterns are:

• What is the reason that the customer contacted support?
• What events in the customer journey resulted in this interaction?
• How were these issues solved in previous occurrences?

Further, customer data is extremely valuable in real-time. It provides a deeper look into what the customer is doing at the exact point when they reached out for assistance and provides historical context. From here, you will have more in-depth information on each customer to make informed decisions about how to handle their query. For this reason, it is wise to collect data from as many different sources as you can.

For instance, let’s say you have a customer who has inquired about a refund on multiple occasions. They have called, sent emails, live chatted, and connected with you on social media. Using the data from their previous interactions and journey through your system, each time you interact with them, you should provide different answers to avoid going around in circles. To simplify this task, you might use a customer insight platform like Signal to provide a unified view of all the interaction data you collect.

Learn what exactly customers want before the interaction

One of the biggest advantages of incorporating big data into business operations is the ability to look at historical information and make educated decisions for the future. This is called predictive analytics.

Using these insights in customer service requires techniques a bit more advanced. You will need to dive deeper into your data stream and look for factors that signal shifts in consumer interests and trends so you can act on them preemptively.

Optimove is a great tool for collecting data-driven results and providing predictive customer modeling to gain a deeper understanding of how to create your plan of attack.

Predictive analytics can also be used to pinpoint the most effective approaches to take when interacting with customers. Using the information mined across marketing, sales, and product departments, customer service can determine how to deal with the issue appropriately backed with context.

This will, however, require a good deal of collaboration and effective project management across your organization. Use a task scheduling and workflow management tool like WorkZone to keep all of your departments on the same page so that nothing slips through the cracks. Handling valuable customer data to provide the most effective responses requires impeccable internal communication.

To go even further, predictive analytics can be used to keep tabs on external factors like social media and brand mentions across the web. Through digital media monitoring integrated with sentiment analysis, you can learn what people are saying about your brand or industry as a whole. With these insights, you can anticipate spikes in inbound traffic and aid customer support in responding to inquiries.

Keep improving internal processes

Everyone knows that it’s near impossible to satisfy each and every customer. Before the internet took off, call center managers relied heavily on roll ups and daily reports to get an idea for how their teams were doing.

Now, with the help of big data, you can learn how your customer support agents rate among users and how well they conveyed actionable solutions to problems. From here, you can get in-depth answers in regards to the location and nature of bottlenecks in your processes and how to properly set up training programs in the future.

Harvesting data on customer feedback extends past your support team. These metrics can be applied to all departments that have interactions with users. Look for certain patterns in areas such as:

• Response time
• Hold time
• Abandonment rate
• First contact resolution

Tools like Zoho Desk help you gain a deeper understanding of how you can use this information to optimize your customer service operations across all channels.

Parting words

Customer service is a vital part of business and always will be. Luckily, the amount of data that is available provides all sorts of clues on how to make the entire process seamless and result in more satisfied customers. Keep in mind, there is more competition among brands than ever before. Customer service is a huge priority for a lot of consumers. The strategies you put in place now will have a huge impact on the future of your business.