Data monitoring is the process of proactively reviewing and evaluating important business data to ensure quality and ascertain adherence to established standards and protocols. While this can be done manually, most contact centers use specialized software that provide all the data needed in the form of dashboards, alerts, and reports.
This technique uses artificial intelligence (AI) to monitor calls in real-time to identify tone and sentiment, gauge customer emotion and satisfaction, and even use algorithms to study the skills of agents.
Text (interaction) analytics
Contact centers using chat, email, or social media to interact with customers have many data quality monitoring tools at their disposal. These can scan the text to identify and analyze data. Note: interaction analytics may include speech analytics as well.
Predictive analytics
This approach analyzes previous data to identify and predict customer behavior, and finds the most effective method of interaction.
Performance analytics
Using custom dashboards, managers can keep track of agent performance and coaching programs for individual agents.
Better agent training
Training newly appointed agents is easier with data-driven coaching programs that explain processes and substantiate different parameters.
Improve service quality
Data monitoring changes how contact centers assess quality across multiple channels and learn from customer interactions. This enables strong decision-making and builds an efficient and skilled workforce generating excellent customer service.
Cost effectiveness
A key benefit of data monitoring is the dollar amount of capital expenses that can be avoided and reduced with streamlined workflows.
Create healthy environment
Scoring agents and providing feedback based on data monitoring in a contact center can create an environment of learning and progress. This motivates agents to improve their performance, increase efficiency and eventually, increase the overall customer service experience.
