By Ray Naeini
Establishing positive customer experiences leading to customer loyalty is today’s major objective for all enterprises. Customer loyalty differs from customer satisfaction in that it establishes a long-lasting relationship for retaining customers. Achievement in customer satisfaction is an ongoing journey, not a single set of actions.
Enterprises first focused on customer interactions with agents by capturing and analyzing customer calls, emails, and chat. They followed this by training agents to better serve customers during calls. To a great extent, this approach delivers certain objectives toward customer loyalty, but it ignores several other steps of the customer journey critical to customer experience management. For example, no matter how well-trained agents are in interacting with customers, customer satisfaction is already impacted negatively if a customer struggles with a confusing interactive voice response (IVR), has to wait on hold for a long time, gets routed to the wrong agent, or has to repeat information.
Customer experience management demands a holistic view and improvement of the entire customer journey. This consists of four major segments:
- Routing customer service requests to the right center, organization, and agent rapidly, accurately, and without the customer repeating information
- Managing the customer interaction for the best outcome for the customer
- Processing customer service requests accurately and on a timely basis
- Capturing and analyzing customer feedback and sentiment from all customer touchpoints, both during and after the completion of service, and implementing calibrations and corrective actions.
This is, however, hard to do. Enterprises face major challenges in effectively integrating and implementing these four critical elements of customer experience management. This is where intelligent automation (IA) technologies can greatly power the customer experience management initiative. As the name implies, automation is achieved by intelligently analyzing data and making decisions to launch an automated action. The nucleus of IA, commonly used the same way in all four segments, is comprised of:
- Data and media capture, aggregation, and unification, with big data management performed on an enterprise-wide basis from all entities critical to the customer journey. This includes telecom platforms (network routers, IVR, PBX, and ACD) and key performance indicators (KPIs) from workforce optimization and management, CRM, and ERP.
- Multi-channel analysis (speech, desktop, and text) of unified data and creation of actionable knowledge
- Artificial intelligence (AI) drives learning decision-making engines (LDME) to further analyze actionable knowledge to make best decisions and continuously learn from historical data and analysis.
- Automated activities driven by LDME to launch actions and automate functions
Recent advancements in AI and learning machines that have transformed these concepts from theory to real products are the key to making IA a feasible solution in powering the four steps of customer experience management.
In the customer service routing segment, IA continuously and automatically captures, monitors, and analyzes the status and performance of all entities engaged in the customer journey, makes the best decision, and in real-time, launches the action to intelligently route the service request. It also captures customer information from each touchpoint and deposits it in a single place accessible to all agents and systems to prevent customers from having to repeat information.
During agent interactions with customers (calls, emails, chat, and desktop transactions), IA captures and analyzes interactions to automatically conduct QA, compliance management, and customer sentiment analysis, to then automate agent interactions through real-time coaching, workflow automation, reminders, and notifications. The recent developments in AI, AI-based chatbots, and intelligent virtual agent (IVA) technologies intelligently automate customer interactions while reducing enterprise expenses.
When it comes to processing customer service transactions, IA utilizes robotic process automation (RPA) to automatically, intelligently, and rapidly process repetitive tasks in various processes without human errors. Business process automation (BPA) then performs data collection, unification, and analysis of customer transactions to automate business processes.
Finally, IA continuously and automatically captures customer sentiment and feedback from every customer touchpoint during and after service (including social media content and customer surveys), analyzes the data, and provides actionable knowledge to LDME that can offer conclusions, trends, and actions. This is all designed to improve systems, processes, and the interactions engaged in the customer journey.
Ray Naeini is the CEO and chairman of OnviSource, Inc.