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High-quality customer care is a core tenet of your contact center’s success. According to a new study by McKinsey, customer engagement focused on emotional, complex, and loyalty-driven interactions are the future of the customer experiencea new study by McKinsey. But the question is, what does that look like in action? For that, you need in-depth and accurate data.

Data is how you determine if you’re meeting goals and providing exceptional customer experiences call after call and day after day. With data, you can choose how to meet needs successfully and improve your processes when and where you need them. There’s only one problem: many contact centers struggle with insufficient data, particularly in eCommerce.

How is Bad Data Defined in the Contact Center, and Why Does it Matter?

Insufficient data in the contact center is defined as any data that doesn’t tell you the whole story or allow for simple and accurate analysis. It costs companies an average of $9.7 million per year due to poor decision-making, business inefficiencies, mistrust, missed opportunities, and lost revenue.

Examples of insufficient data in the contact center include:

  • Too Much Data: Data overload is a problem for many contact centers. Being paralyzed by too much information without understanding the communication means you can’t leverage the data to improve your performance.
  • Too Little Data: At the same time, call centres gather too little data. You need tools such as text analytics or QA scorecards in place to collect, analyze, and interpret data daily.

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  • Inaccurate Data: If you rely solely on your agents to tag customer issues based on their opinion, there’s a high likelihood that problems will be classified incorrectly or missed entirely. Data can also be inaccurate if not enough is collected to paint the entire picture.
  • Poor Data Quality: Lastly, only 16% of companies characterize their data as “very good.” This poor-quality data can be due to a lack of tools for monitoring and analysis, not measuring the correct KPIs, or misinterpreting what information means.

Whatever the case, this bad data results in customers feeling unsatisfied and money being left on the table. After all, 58% of American consumers will switch companies because of poor customer service.

So, how do you overcome the problem of insufficient data to make better decisions? Recognize where bad data comes from in the contact center and learn to focus on good data instead.

Discover how text analytics gives you rich insight into your customers.

5 KPIs that Avoid Bad Data in Your eCommerce Call Center

While metrics on account information, order quantities, shipping addresses, payments, and marketing performance are essential, they don’t give you the whole picture. There is a mountain of hidden data in your contact center to provide high-quality customer service. Understanding this data, where you can find it, and what it means will help you recognize performance issues immediately and make changes for the better.

The following five KPIs should be monitored and analyzed consistently and constantly, so you can start making the right decisions and avoid insufficient data.

Customer Call Volume

Customer call volume might sound like a simple metric for your contact center, but it is crucial. Increases and decreases in call volume can indicate many different issues. And understanding the reason behind the change is essential for your performance. It will help you make both short- and long-term adjustments to your day-to-day procedures, training, and workflow to decrease why your customers call you.

For example, for an eCommerce business, an increase in customer service call volume could stem from product issues, website payment gateways, or account issues—the list is endless. A solution like text analytics can uncover the underlying issue through keyword analysis and topic trends to discover what's driving your call volume text analytics can find the underlying problem through keyword analysis and topic trends. You can then track your call volume against specific issues to determine what problems are costing you and how to fix them.

Product Defects

Issues with products (or services) have an obvious and direct impact on your company. These issues can negatively affect your brand and ultimately impact revenue. After all, every product returned as defective or unsatisfactory costs your company in fulfilment and negative reviews.

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That’s why it’s essential to track product defects as a critical data point. You should cross-reference the number of defects reported with the volume of your product/item calls to make more informed business decisions regarding customer satisfaction with a particular product. From there, your contact center can disseminate this information to your product team or adjust agent training to tackle the problem head-on during every call.

Undelivered Shipments

Customers dislike waiting for their product to arrive, and undelivered shipments are a significant negative mark against your brand. But shipping issues can have many different causes, from mistyped addresses to changes in account details or issues with a shipping partner. Knowing where the problem stems from can help you better handle shipping complaints when they come up.

In a global marketplace, it’s essential to track customer shipping complaints by a specific carrier/shipping partner. Even if this is a shortlist, it will give you a better idea of where the shipping issue stems from and whether changes need to be made to your processes or procedures to fix the problem.

Average Call Length

Like call volume, average call length is another metric in the contact center that helps you uncover complex issues. You can keep an eye on matters as they grow more complicated by tracking this KPI. This understanding will help you quickly train your agents to handle these more extended support calls. It will also alert you to more significant business issues that may need fixing to avoid these complex issues in the first place.

Issues with Your Website

While websites are beneficial for communicating product information, they can also cause many problems. For example, if you get a lot of calls or tickets about item pricing, color availability, or payment gateways, your website could be the source of these problems. By tracking issues with your website as a data point and looking at trends, you can determine where website improvements are needed—including your customer knowledge base page—and make adjustments to cut back on these types of calls.

How to Use AI Text Analytics to Gather Good Data and Improve the Customer Experience

Developing a comprehensive view of the issues in your contact center is essential to success. The last thing you want is to miss issues floating just below the surface. To be increasingly competitive in such a difficult market, you have to get a handle on your contact center data.

Text analytics can help you analyze 100% of your text interactions automatically. In this way, you can gain the necessary insight into every customer query and conversation for better and faster decisions. It will help you uncover agent knowledge gaps, identify learning needs, improve agent training, and enhance the customer experience.

After all, the actual value of customer support comes when all of your data works together to give you a complete view of your customers’ wants and needs.

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