Call center conversations are packed with valuable information. But, it can seem like a near-impossible task to sift through all call records for valuable, actionable information.
Here, we will consider how to better use call center conversations to your company’s advantage, particularly in terms of improved sales and NPS as well as decreased compliance risk. Then, we will explore how NeoSound’s speech analytics solution software can make applying these improvements infinitely easier.
To analyze all these data, companies can choose either traditional or automated quality management processes.
In this article, we'll be comparing the automated and traditional approaches. The intention of the article is to help in making the decision to opt for a digital transformation of your call centre’s quality management process.
AI has been useful to many industries, call centres being one of them. AI has been deployed to handle mundane tasks and has also been quite helpful in optimising human interaction. However, altering your call centre’s structure to incorporate AI technology might be quite a complicated process.
Traditional call centers have always been dogged by several problems. Customer care reps have to rely on their natural senses to detect changes in customers’ moods. Also, they typically spend most of the call time searching for answers to customers’ questions. And then, there are language and cultural barriers, which are even more apparent in diverse societies like the US and Europe.
This means that contact centres are becoming increasingly important in reducing customer churn and attracting new consumers. CallMiner also found that 84.1% of consumers were likely to stay loyal after a positive experience with the call centre while 78.4% were likely to switch providers after a bad experience.
If customers have issues about payment, but you've updated your FAQs and prepared your chatbots to respond to questions about shipment and delivery, no wonder they're calling - they can't find the answer!
Call analytics software can help you do topic classification to find out what type of calls you have and the top complaints or questions customers are calling in about.
Nearly 100 people were infected with coronavirus in a Seoul call center, forming the biggest COVID-19 cluster to date in Seoul, South Korea.
Call centers are literally a hotspot for infectious outbreaks because they typically have large numbers of people on a single floor.
Many businesses have already asked their staff to work from home to reduce the potential spread of the coronavirus amongst their employees. Last Friday, March 13, Cloudflare's co-founder and CEO Matthew Prince sent out an email to all its customers noting a 10% increase in Internet usage patterns in regions impacted by COVID-19. Peak Internet traffic has surged 30% in Italy which has had a national lockdown.
If your system does not allow your employees to work from home, you have to figure out a contingency plan so you can continue to monitor your employees and route calls even when they're at home.
The worst part is that you found out about the incidents because the customers complained, not because your own managers picked up the issues.
Is it possible to find out more promptly whether your employees are complying with your customer communication standards?
With technology, you certainly can.