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Customer Experience Management Powered by Intelligent Automation

Customer Experience Management Powered by Intelligent Automation

Customer Loyalty vs. Customer Satisfaction

All enterprises should strive to create positive customer experiences that lead to customer loyalty. Customer loyalty is different from customer satisfaction.  It establishes a long-lasting relationship with customers. It is an ongoing process, not a single set of actions. Therefore, enterprises should develop a strategy for customer experience management.

Companies first focused on customer interactions by capturing and analyzing customer calls, emails and chat. Agent training soon followed to better serve customers during interactions. This approach helped to achieve customer loyalty, but it ignored other steps of the customer journey critical to Customer Experience Management (CXM).

4 Segments of Customer Experience Management

Customer experience management demands a view of the entire customer journey, consisting of the following four segments:

  1. Routing customer service requests to the right organization and agent rapidly with no need for the customer to repeat information
  2. Managing interactions for the best outcome for the customer
  3. Processing customer service requests quickly and accurately
  4. Capturing and analyzing customer feedback from all customer touch points during and after the completion of service, making changes and taking action toward improvement.

intelligent automation

Intelligent Automation Technologies Greatly Power Customer Experience Management

Enterprises can face major challenges in establishing these four critical segments effectively. This is where advanced Intelligent Automation (IA) technologies greatly enhance CXM programs.

The core components of IA is commonly used the same way in all four segments.

  1. Data and media capturing, unification, and big data management performed on all areas critical to the customer journey. This includes telecom platforms (network routers, IVR, PBX, ACD, etc.) and key performance indicators from workforce optimization, workforce management, customer relationship management and enterprise resource planning.
  2. Multichannel analysis (speech, desktop and text) of unified data and the creation of actionable knowledge
  3. Learning Decision Making Engines (LDME) driven by Artificial Intelligence (AI) further analyze actionable knowledge, make best decisions, and learn from historical data and analysis
  4. Automated actions driven by LDME launch actions and automate functions

 

Artificial Intelligence and Learning Machines are Key to Making IA a Practical Solution

customer journey

In customer service routing, IA automatically captures, monitors and analyzes the status and performance of all entities engaged in the customer journey. Routing makes the best decision and launches the action to intelligently route the service request in real time. It also captures customer information from each touch point and deposits it in a single place accessible to all agents and systems. This prevents customers from having to repeat information.

IA captures and analyzes customer interactions (calls, emails, chat, desktop transactions) to automatically conduct quality assurance, compliance management and customer sentiment analysis. Real-time coaching, workflow automation, reminders and notifications help automate agent interactions. Recent developments in AI-based chatbots and Intelligent Virtual Agent (IVA) technologies automate customer interactions while reducing enterprise expenses.

When it comes to processing customer service transactions, IA utilizes Robotic Process Automation to process repetitive tasks in various processes without errors. IA utilizes Business Process Automation to perform data collection, unification and analysis of transactions to automate business processes.

Finally, IA captures customer sentiment from every customer touch point during and after service. This can include social media content and customer surveys. IA analyzes the data and provides actionable knowledge to LDME that can offer conclusions, trends and actions.

Each of these four steps is designed to improve systems, processes and the interactions engaged in the customer journey.

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