Cloud-Based Collaboration Is the Key to Driving Efficiency, Alignment, Analytical Abilities & Insight-Based Results

The digitization of agent support allows us to build rich datasets that help us understand why and how often agents need to reach out to get support to service our customers. Our analytics then enables us to dive into that information, driving feedback to process, knowledge and training for continuous improvement. Plus, it also provides us a platform to work on automating that support.

Gaining alignment

When you have 50,000 or more agents answering consumer questions daily, you want to make sure you are all marching to the same beat, answering questions consistently and with the most accurate information. The same is true for all business sizes. By connecting a team digitally, you create an organizational network that has similarities to a social network. It facilitates information sharing, fosters connectedness within the team, and provides one-to-one and one-to-many messaging. And like a social network, it can be analyzed for sentiment, topics, trends, participation and influence. This network effect allows you to observe how aligned the team is in delivering consistent, high-quality service interactions. Within the platform, you access the same tools and information that your co-workers use, preventing inaccurate information shares and completely differing responses per person. In our business, we see consumers researching and self-servicing against their own unique challenges before they call into our centers, which means their questions are more complex and technical. OneSYKES allows us to give our agents the right tools and support to answer the questions quickly and accurately to keep our customers happy.

Advanced analytical abilities

There are two types of datasets: structured and unstructured. Most businesses are familiar with analyzing structured data (think Excel numbers turned into charts and graphs), but unstructured data can be harder to dissect simply because it can be hard to measure things like conversations and behaviors. Each call provides a continuous stream of data including agent actions, behaviors and conversations combined with traditional call-center metrics that result in a precedent setting pool of data. But when you apply natural language processing and machine learning to those elements, you can start to analyze what makes up each part of that phone call or customer experience. It’s like turning a 2D picture into a 3D picture, because you can see so much more depth and you gain so much more knowledge. Because our cloud-based collaboration platform logs all the data, it gives us the structure to learn from every customer interaction like never before.

Producing insight-based results

Now that we have all this data, it’s time to turn those into actionable insights to fuel back into your processes, business knowledge, team-member training and personalized coaching. Within the cloud-based collaboration system, you’ll be able to see where team members are struggling, and you can address that in upfront training and within coaching sessions. Maybe you uncovered a need for new resources, tools or process changes so your team members can deliver the very best customer service. Next, you can develop a plan to create those materials and distribute them within the system for easy adoption. In addition to making changes to upstream processes to train and prepare the team, real-time predictive analytics with self-learning capability provides recommendations to the operational leaders to improve performance throughout the day. The whole point is to help ensure your team can work smarter vs. harder—and using insights to develop new efficiencies, is the way to do it.