Call center agents are the front line of customer interaction. They don't just interact with customers; they also collect a wealth of information that can improve the customer experience and drive the business forward. But how can brands harness this information to improve their customer experience (CX)? The answer lies in effectively integrating technology and experience to address the customer’s exact need: responsiveness and convenience paired with quality service.
According to McKinsey, companies applying advanced analytics reduce their average handle time by 40% and increase self-service containment rates by as much as 20%.
Call center analytics is the process of gathering and analyzing customer data to discover insightful information. Call center analytics can help organizations identify and prioritize the most valuable interactions with customers, enabling them to spend less time on repetitive activities and more time on strategic initiatives. Analytics can identify customer pain points, identifying process improvements, gaps in information shared through other channels or highlighting areas for product development. By providing information that streamlines processes, it can also drive employee engagement, further increasing productivity, lowering turnover rates and improving service quality.
With the right tools and techniques, data derived through call center analytics enables contact centers to deliver world-class CX, increase brand loyalty and promote work efficiency.
More than half of customers interact with at least three brand channels before making a purchase or having their question answered. Each touchpoint is an opportunity to collect data and insights. However, more data isn't always a good thing unless you can distill that information into insights that drive meaningful actions.
In a busy customer service environment, agents confronted by a lot of data to interpret can feel overwhelmed and find that their attention is directed away from understanding the customers’ needs towards simply understating the information in front of them. Therefore, it’s important to start with a clear use case for the information you’re capturing and how it will be used to develop your systems and processes around your goals. In this way, you will have a greater impact on both the performance of your call center and the CX your teams deliver.
1. Omnichannel or cross-channel analytics: Today’s multichannel customers expect a seamless, omnichannel experience able to pick up where they left off on one channel and carry on the experience on another with the help of an omnichannel CX. Brands can deliver this experience only when they support a 360-degree view of the customer. Analytics across the customer journey will enable you to understand and improve the end-to-end experience.
2. Call center desktop analytics: Activity taking place on each call center agent’s desktop is valuable data and a window into the agent’s performance, application utilization and usage patterns. Effectively harnessed, this data optimizes processes, enhances employee productivity and provides customized feedback and training to agents based on their performance.
3. Operational insights: Operational insights identify where automation could benefit the call center and where process improvements could drive efficiencies. Operational analytics integrates data to enable agile and intuitive processes that transform business execution and decision-making by identifying patterns and trends in data that may not otherwise be obvious.
4. Predictive analytics: Predictive analytics takes historical customer interaction data and layers it with machine learning to predict customers' behavior and needs. This data brings your customers’ preferences to the fore and, as such, drives customer retention and satisfaction and identifies high-value customers for targeted campaigns. Predictive analytics uncovers the effectiveness of customer service teams and helps to understand competitor trends, detect risk, control churn and powers intuitive decision-making for top-line growth.
5. Business intelligence insights: These are insights about your business that support planning and forecasting including data about customer behavior, trends in sales or product adoption and historical data such as product transaction counts or customers' purchase histories.
6. Speech and text analytics: Speech analytics is the analysis of the human voice and its characteristics, including pitch, volume and cadence. Speech analytics has a wide range of uses and can be combined with other tools to reduce manual effort. For example, speech analytics can identify the sentiment of the caller and determine the reason for their call, combined with other tools, speech analytics can automate the update of internal system reducing the manual entry of data and highlight next best actions to the agent. Text analytics has similar benefits across written communications such as messaging, email or social media. Text analytics can identify trends in conversations about topics related to customer service. These analytics help improve customer service and increase efficiency in the call center.
Aggregated, customer interactions are a gold mine of data. Combining the insights derived in each interaction identifies patterns in customer behavior and understands the CX delivered at each touchpoint. But to benefit from the insights call center analytics delivers, the data must be delivered in a simple, easy to action format that focuses on the most important metrics.
Call center analytics has broad benefits, from tracking the performance of individual agents to monitoring the overall performance of the entire call center operation and its impact on the wider business. Analytics can be real-time or retrospective, depending on the need. By aggregating data, call center analytics uncovers trends that may not be identified in individual contacts.