In the past Companies controlled the buying process and the customer journey, with the IoT that shift has moved to the consumer. If you really want to lead in the marketplace you must focus on customer experience. As customer service evolved, the consumers now do business based on customer experience. In this blog we will discuss how the greatest advantages technology can give us is access to this information. One example is purchase tracking, which companies can use to supply suggestions based on past buys. You can apply this same concept to your customers’ experience with service representatives if you have the right tools.
Problems With Traditional QA Processes
Quality assurance (QA) exists to ensure that consumers are receiving the best experience when they communicate with your company. However, many businesses make a mistake right out the gate by establishing QA standards based on what they think their customers want, rather than what customers are actually asking for.
This isn’t necessarily a business’s fault. The crux of the issue is a lack of concrete data, which may be caused by limited resources to collect said data. When employees are responsible for all call monitoring, only a tiny portion of calls—sometimes as low as 1 percent—can actually be listened to. Unfortunately, that’s not enough to be a representative sample for analysis purposes.
A lack of real data can lead companies to guess at what creates a great customer experience, which may do more harm than good. To better offer what your clients want, you need a reliable, efficient way to monitor calls and collect data—which brings us to AI.
AI and Data Collection
Artificial intelligence (AI) is a vital component of automation and can be a powerful tool when used correctly. Since according to an article by eMarketer, about three-fourths of customers feel that the best service is provided by a real person, the key isn’t necessarily more automation but strategic automation.
In the case of call centers, AI can be utilized to evaluate calls, thereby increasing both efficiency (since software can listen to more calls) and data collection. When it comes to this second point, it’s essential that the AI used is dynamic, meaning that it can learn. An AI programmed to listen to agent and customer interactions, for example, can learn to identify a number of factors that may influence a QA score, such as:
- Tone
- Business policy
- Contextual conversations
- Keywords that indicate an escalation
In fact, you may be able to customize your AI to recognize different factors based on your market. For example, if your company is a virtual bank, you may want the AI to track how many calls are related to website navigation, so you can determine if your site is easy to use.
The Customer Experience
Of course, AI alone can’t create the prime experience your customers expect. You need knowledgeable people to analyze the accumulated data and identify any trends that result in churn. You then need people to take this information and translate it into practices. Finally, you need people to implement those practices in the day-to-day and deliver that human touch. Think of AI not as a replacement for human employees but a valuable tool your business can use to elevate your call center to its greatest potential.
Here at Etech, we pride ourselves on supplying innovative solutions to help our clients offer the best customer experiences to their own consumers. To learn more about our call-center technology, call us at 936-371-2640 or visit us online.
This blog was first published on LinkedIn.
