Leveraging AI to revolutionize toll road customer service

Over the past three decades, America’s tolling industry has revolutionized the collection process to become faster, friendlier and more efficient by shifting from manual toll collecting to digital methods like electronic toll collection (ETC) and video tolling. Technological advancements such as optical character recognition (OCR) and digital vehicle signature have accelerated this transition, allowing for accuracy and speed.

Additionally, the industry has progressed from processing transactions for an agency’s transponder to adopting regional interoperable devices, enabling seamless travel across multiple tolling systems. Payment options have expanded from cash payments in toll lanes to accepting cash, credit and debit cards, automated clearing house (ACH) and e-wallets in back offices. Recognizing the importance of customer interactions, agencies have established customer service centers to facilitate effective communications.

Looking ahead, we’re poised to leverage artificial intelligence (AI) to make these centers faster, friendlier and more efficient for a sustainable future. In recent years, AI has improved significantly, surpassing rules-based scripted approaches. Through natural language processing (NLP) and machine learning, AI can understand, interpret and generate human language enabling the development of virtual assistants that provide written and verbal responses.

By leveraging AI in back-office solutions, we can enhance customer experience, optimize operations performance and sustain quality management systems while improving customer and employee satisfaction.

Enhancing Customer Experience

An advantage of using AI in customer service centers is its ability to deliver faster, accessible, consistent and efficient services in every interaction. Sixty-eight percent of consumers cited “long wait times” as a frequent pain point in CCW Digital’s 2021 Consumer Preferences Survey. By providing real-time prompts to customer service representatives (CSR) during customer interactions, AI-powered chatbots and virtual assistants can augment the workforce and improve scalability by allowing CSRs to provide faster service and focus on complex issues.

In addition, leveraging design-thinking and real-time tuning enables a digital workforce to be more accessible and instantly provide self-service options 24/7/365 in multiple languages, connecting with customers in preferred channels to resolve issues or answer frequently asked questions. Integrating AI across customer service channels also allows customers to switch channels without losing context, ensuring a seamless, consistent customer experience. AI can even authenticate incoming communications and route customer inquiries based on sentiment analysis. High-priority or negative cases can be automatically escalated to senior CSRs or specialized teams for an immediate, empathetic response.

Optimizing Operational Performance

AI has transformed operational performance in contact centers by streamlining processes, automating tasks and enabling personalized experiences. Contact centers leverage AI to optimize service levels, efficiently allocate resources and improve performance.

Properly managing your workforce is critical for optimizing operations and having the right number of qualified customer service representatives available to respond to customer demands is a must. AI algorithms utilize predictive analytics to predict call volumes and forecast future staffing needs during normal, peak and seasonal times. Service-level optimization tools analyze historical data, current trends, staffing profiles and CSR performance to allocate resources effectively.

To help your workforce work more efficiently, AI can facilitate knowledge management by quickly organizing and indexing vast amounts of data and updating data sources like FAQs, standard operating procedures and training databases. Intelligent search algorithms, content and sentiment analysis and AI assistants can automatically retrieve relevant information, provide guidance, identify areas where customers need assistance and update knowledge databases based on customer inquiries and feedback. This also enables tailored training based on individual performance.

Robotic Process Automation (RPA) technology can improve the customer journey by automating repetitive, time-consuming tasks, like transponder fulfillment, payment processing, refunds and reconciliation. By pulling data and validating it against predefined rules, RPA can mimic these high-volume tasks, reducing manual errors and optimizing CSR workloads. It also operates on the presentation layer of existing applications, eliminating the need for application programming interfaces or developing integrated solutions.

Sustainable Quality Management

AI technologies improve quality systems by enabling organizations to measure and standardize replicable quality assurance processes for day-to-day operational compliance. Quality management platforms incorporating AI can effectively monitor and assess customer interactions to identify trends and improvement opportunities.

AI algorithms can assess customer engagement performances in real time and send results to the CSR and management dashboard. Speech analytics can transcribe conversations, extract valuable insights, detect customer sentiments and identify keywords or phrases. They also detect emotional cues to determine customer sentiment by analyzing speech patterns, tone and voice modulation, allowing CSRs to promptly address concerns and respond accordingly. Based on sentiment analysis, customer inquiries can be routed to the appropriate individual or team. High-priority or negative sentiment cases can be automatically escalated to senior CSRs or specialized teams, ensuring an immediate, empathetic response.

In addition, AI algorithms can analyze customer interactions across multiple channels, including emails, chat logs and social media posts. By examining text patterns, keywords and contextual clues, these algorithms can identify whether customer sentiment is positive, negative or neutral. They can also monitor social media platforms and online review sites to capture real-time customer feedback and sentiment. Sentiment analysis tools can aggregate data, identify trends and generate actionable insights to proactively address customer concerns or manage your agency's reputation.

Implementing AI in customer service centers holds immense potential. It can support the entire customer lifecycle, improve the digital experience and provide consistency and context in customer interactions across all channels while minimizing costs and staffing workloads. By embracing AI, we can better meet customers’ expectations in the ever-evolving landscape of toll collection and provide quality, sustainable services.