Interaction Analytics: Listening in on the Omnichannel Customer Journey
Interaction analytics (IA) literally listens to (or reads) the voice of the customer and interprets what they are saying (or writing) and how they feel about a company, product, or service. It converts customer conversations into transcripts and structures the insights so they can be shared throughout the enterprise. Interaction analytics is necessary to understand many aspects of the omnichannel customer journey, as it provides the intelligence to discover emerging and previously unknown issues and trends and discern the nuances in customer interactions, including sentiment and even emotions. Interaction analytics applications capture and report on what is happening, enabling companies to measure the impact of their actions on their customers and prospects.
Feature-rich IA solutions deliver significant benefits to contact centers. They generally come with an analytics-enabled quality management (AQM) application to automate the quality management process, and real-time guidance (RTG) to provide agents with alerts, best practices, and knowledge articles to handle customer interactions correctly. However, for IA to deliver strategic benefits, its use must be expanded beyond contact centers and applied more broadly throughout the enterprise. Companies should use interaction analytics to identify and fix avoidable mistakes, improve operations, increase revenue, measure and assess the effectiveness of marketing programs, identify new product ideas, and evaluate the performance of the back office, just for starters.
Most departments in an enterprise will benefit from a firsthand view of what customers think about the job they are doing; this includes auditing and compliance, risk management, legal, and collections departments. The benefits of IA solutions will increase as they are applied to the growing number of departments that impact the customer journey.
Operationalizing IA Throughout an Enterprise
Thanks to artificial intelligence-based technologies, including predictive and real-time analytics, IA solutions are becoming vastly more useful, and companies have begun to integrate and embed IA into a variety of enterprise and contact center applications to improve their insights and to operationalize IA findings organization-wide. For example, to increase the value of surveying/voice-of-the-customer applications, vendors have started to embed interaction analytics capabilities into them to help structure free-form customer feedback. And as an essential feed into customer journey analytics solutions, IA helps companies understand and stitch together the comprehensive customer experience story.
Today’s feature-rich IA solutions deliver benefits that go far beyond identifying the reasons customers reach out to an organization. Sentiment analysis, for example, provides insights into the experience of both the customer and the employee. Interaction analytics output, when used in conjunction with predictive analytics, sentiment analysis, and other relevant data, can improve many aspects of an organization’s operations. It can make routing more intelligent; predict quality, customer satisfaction, and Net Promoter Score ratings across all interactions; assess the likelihood of a prospect or customer buying, paying, or churning; and help enterprises better understand employee engagement.
IA can listen to/read both sides of a conversation and trigger real-time guidance or next-best-action recommendations to help an agent handle an issue properly. This includes delivering context-based resource materials from the knowledge management system or knowledge base. Transcription capabilities, another feature of IA, can create an after-call work summary, which is made available to the agent and posted to a customer relationship management or other system. And, when IA is integrated with robotic process automation, it can trigger relevant follow-up tasks based on topic and intent.
Contact center management and supervisor dashboards increasingly include IA results, blending the data with other contact center KPIs to help companies operationalize IA findings. Those findings are also incorporated into senior executive dashboards to provide a snapshot of what is happening. IA vendors are enhancing their visualization and exploration capabilities and making it easier to combine system results with third-party solutions and databases.
Enterprises should apply IA broadly, beyond their contact centers, so that executives and managers throughout the company have timely and actionable access to what is happening and how customers feel about their brand. To realize the greatest return from an IA solution, companies should use these solutions as a primary data source in a change management program dedicated to improving the customer journey and CX and reducing operating costs. Interaction analytics should be supported by enterprise business analysts who share findings with a cross-functional team of department managers responsible for applying findings and fixing the underlying issues.