TL;DR:
- Invoca introduces new AI-powered features for enhanced customer experience and streamlined processes.
- The update includes LLMs and GenAI functions that offer specific business outcomes.
- Rapid creation of algorithms to identify missed opportunities and overcome objections in customer calls.
- AI Smart Alerting ensures real-time identification of mission-critical exceptions for prompt remediation.
- ChatGPT-based call summarization and structured data extraction enable personalized follow-up calls.
- Combining AI and voice biometrics for quality assurance and agent coaching.
- The update provides an AI-informed Call Review Console for efficient call review and coaching processes.
Main AI News:
In a rapidly evolving technological landscape, businesses are constantly seeking innovative solutions to improve customer experience and optimize their operations. Recognizing this need, Invoca, a leading provider of AI-powered software solutions, has recently introduced a range of cutting-edge features that leverage Large Language Models (LLMs) and Generative AI (GenAI). These offerings are designed to have a positive impact on customer experience while simultaneously streamlining processes and bolstering the bottom line of companies across diverse industries.
Invoca’s flagship offering, Signal AI, has already garnered acclaim since its launch in 2017. Leveraging a portfolio of patents acquired by Invoca in 2015, Signal AI has successfully been integrated into the technology infrastructure of prominent organizations such as DirecTV, Banner Health, Spectrum Retirement, and Rick’s Custom Fencing and Decking. These industry leaders have harnessed the power of AI-assisted insights to reduce customer acquisition costs, identify lucrative market segments, expedite sales cycles, and enhance the efficiency of their customer service agents.
In a departure from the norm, Invoca’s latest update goes beyond the obligatory partnerships with hyperscalers and introduces a combination of LLMs and GenAI functions tailored to address specific business outcomes. One notable benefit is the rapid creation of algorithms and models that identify instances where agents fail to close leads, allowing businesses to pinpoint the precise moments within customer calls where objections can be overcome. By utilizing a “semantic search modeled after ChatGPT,” Invoca’s AI-infused system enables the construction of call classification algorithms with 90% fewer data and as little as 30 minutes of development time. Furthermore, Invoca’s “AI Smart Alerting” feature, powered by LLMs, promptly recognizes mission-critical exceptions in contact center operations and generates real-time alerts for management, enabling timely remediation of potential issues.
Among today’s GenAI offerings, call summarization using ChatGPT is widely hailed as a transformative capability. Invoca astutely incorporates this feature into its latest offering, aligning it with a practical use case that resonates with retailers and service companies operating contact centers. The inclusion of “Structured Data Extraction” further enhances the value proposition. For example, within the automotive vertical, a model trained on the content of phone conversations can effectively identify when callers mention critical details such as the make, model number, and year of a vehicle. This invaluable information empowers businesses to personalize follow-up calls and enhance customer interactions.
In a move that combines the analytical prowess of AI with the personalization capabilities of voice biometrics, Invoca introduces a groundbreaking feature in its latest update. By analyzing every conversation, the system can accurately identify the specific agent who handled a call—a task that was previously labor-intensive and prone to error. This capability proves particularly vital for multi-location and franchise businesses, where multiple staff members may answer calls from a shared phone number. To streamline the call review and agent coaching process, Invoca presents all pertinent call, agent, and outcome information in an AI-informed Call Review Console. This multifaceted resource equips contact center QA managers with the tools to expedite call reviews, provide effective coaching and feedback to agents, and enable teams to collaboratively create and share call playlists for compliance, auditing, and insightful data extraction.
Conclusion:
Invoca’s latest advancements in AI-powered features demonstrate their commitment to driving innovation in customer service and contact center operations. By leveraging LLMs and GenAI, businesses can revolutionize their customer experience, reduce costs, and improve operational efficiency. The ability to rapidly create algorithms, identify missed opportunities, and personalize customer interactions will significantly impact the market by enabling companies to optimize their sales processes and boost customer satisfaction. Furthermore, the integration of AI and voice biometrics ensures quality assurance and enhances agent coaching, ultimately leading to enhanced performance and improved outcomes. Invoca’s comprehensive suite of AI-powered features sets a new industry standard and positions them as a leader in delivering cutting-edge solutions that drive business growth in the competitive market landscape.
