How Data and Analytics Improves Customer Service

Before getting into the meat of this blog, you should consider two statistics: 

·         Approximately 70% of people would spend more on a company with excellent customer service.

·         Around 24% of satisfied customers will return to a business two-plus years after a stellar service experience. 

Now, these statistics shouldn’t come as any surprise. Regardless, the numbers highlight how vital customer service is to any business. It even can bridge the gap when you don’t necessarily have number-one products on the market. 

Therefore, improving your customer service should always be a top priority, as it will make you permanently attractive to consumers. As society enters the age of rich data and more in-depth analytics, it becomes more possible to hone this crucial business facet.

Barriers in Front of Obtaining Valuable Data

According to a McKinsey & Company study examining customer service in manufacturing, the public sector, and healthcare, these industries obtained only 30% of their data’s potential value. 

There are several barriers these sectors face when trying to extract worth from their data. 

For instance, there’s limited access to the information and not enough cross-channel integration. Most importantly, there’s an inability to attract highly skilled data scientists. 

So, how can these obstacles be hurdled?

Leveraging AI Technologies 

When using AI technologies, it’s possible to minimize human labor while digesting data at scale. From there, it’s possible to make pattern-based predictions and implement data throughout several data points – but really, this only scratches the surface. 

The above benefits are the first step in discovering the critical questions to ask and figure out the data’s meaning.

AI tools give you actionable insights because they offer interactive charts, visual filters, and dashboards. These features help with prioritizing successful improvements. It then becomes possible to hone your customer service and make your brand stand out above its rivals.

Teaming Up with Traditional Methods

AI tools don’t necessarily stand alone. You don’t need to say goodbye to what’s familiar. Instead, you’re bolstering those old processes with advanced technology.

For instance, KPI reporting and other traditional business intelligence still offer value when used in tandem with artificial intelligence. 

You’ll know which resources are best suited for individual customer service channels because the data shines a light on how they’re used. Applying natural language to grasp group issues will help pinpoint oncoming trends, sentiments toward your brand, and weaknesses.

These technologies allow you to be proactive with your improvements. You don’t have to wait for problems to cause less than favorable customer experiences before rectifying the situation.

A Practical Example

Here’s a potential scenario where data and analytics will make interactions more fulfilling and fruitful for both agents and customers. 

Surveys show 52% of customers claiming that a knowledgeable staff was the most prioritized attribute in their experience with a brand.

Combining AI with other traditional data collection, reporting, and analytics will direct customers to the correct agent. After all, different reps often have their own areas of expertise. Ensuring that the most suitable connections are made vastly streamlines and enhances the process.

Hiring Data and Analytics Experts 

Technologies such as AI undoubtedly make a significant impact on data and analytics. They remove much of the mundane, menial work involved so that the relevant parties have time to focus on the big picture. 

There is a caveat to the above notion: you require the most capable people to fill the data scientist and analyst roles to leverage this information. All the technology and flashy tools in the world mean virtually nothing without skilled experts putting them to use.

By partnering with Synergy Systems, you’ll have access to a vast pool of top-performing data and analytics talent. 

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