We are midway through 2022. Contact center trends that were forecasted at the beginning of the year have had sticking power and we have seen a common theme emerge as the months have passed. The theme: Strategic organizations are centralizing their operations around consistency.
Customers care about their interactions with your business more than ever before. By unearthing the customer data insights your business call center is already collecting, businesses can better meet customers’ expectations, and improve their overall customer experience. Call center analytics makes it easy to understand your customers.
In a call center, few things are as mission-critical as having adequate information. Being able to understand how each individual, team, product, and channel is performing together at any given point in time helps with agile decision-making and building positive customer experiences. The best way to get the information you need? Call center analytics.
If you work as a contact center manager, you probably have experienced the following scenario: You have several agents out on their scheduled lunches when your website experiences an issue and there is a sudden influx of calls. Your agents that are still logged on are managing the influx to the best of their abilities but you are watching calls getting abandoned and wait times climb. It is stressful for everybody involved and you know this situation could quickly escalate and have serious down-the-line consequences.
Call centers and contact centers are fast-paced environments with a variety of tasks, processes, and team members. However, due to these fast-paced environments, things can also easily fall apart quickly. High call volumes, long queue times, over or understaffing issues, and customer escalations are just a few examples of how a perfectly regular day in a contact center can turn ugly. Call center management is a complex skill to master, but fortunately, with the right tools, strategies, and mindset, the skill becomes more achievable.
In recent years, the customer service industry has been upended with pandemic-related challenges. In particular, call centers and their teams have had to quickly adapt to new work environments, technological barriers, high call volumes, and increased customer escalations, just to name a few. And as organizations continue to navigate and adjust to the expectations of their customers and employees, certain call center customer experience trends have come to light.
When you are communicating in person, we have much more than words on our side to help us get our point across. Body language, facial expressions, hand movement and gestures, and of course, our tone of voice help us deliver our message the way we intend it to be understood. So much of human communication is non-verbal and helps our brains figure out the context and meaning of messages. When we communicate over the phone and no longer have those nonverbal cues on our side, suddenly our word choice and our tone of voice become increasingly significant.
Whether your team has gone permanently remote, returned to the office, or you are working in a hybrid model, everyone seems to be struggling with how to engage their employees in a meaningful way that doesn’t come across as “forced fun” or “mandating culture”. So we’ve compiled a list of some popular ways to cultivate participation, engagement, and connectedness within your organization regardless of your industry, or if your team members are in office or remote.
Call center managers supporting their team members is more important than ever before. With the great return to the office lagging for many businesses across the country, it’s safe to say that remote work is here to stay, at least for the time being.
In the world of business intelligence, “data” and “analytics” are often terms used when discussing tools your business should or could be using more efficiently. But it gets confusing really quickly when you start looking into how to actually use and analyze data. Things quickly become about programming languages, machine learning, and artificial intelligence. Or you click one too many times and you get into the weeds of advanced statistical analysis and regression models or predictive modeling.