The future of customer support is becoming GenAI powered Agents + Humans in the Loop: The real-time deployment use case of Movate Interaction Analytics (MIA) solution takes the market by storm with its first mover advantage. A new frontier in agent empowerment is here.
Contact center heads are on their toes to balance the need for speed and agility against cost pressures. With AI transforming customer service, contact center leaders must blend human skills with AI-driven enhancements to augment customer-agent interactions. The goal is to empower agents, enhance efficiency, and boost CSAT levels.
From the heart of Movate AI comes the Movate Interaction Analytics (MIA) Solution—A GenAI-powered Agentic AI solution that leverages LLMs for augmenting agent performance and enhancing CX. Sampling of records and Quality Assurance (QA) reviews of contact center agent interactions take a turn for the better. Let’s assume an agent handles 45 calls a day. There would be a rare case where the agent performed exceptionally well or unusually badly. MIA provides a complete and accurate quality assessment of agent’s overall interactions by accurately performing the contact analysis (voice or chat or email), exception handling, and quality assessments against the rubrics. Imagine the avalanche of customer support interactions across LOBs, product lines and multiply this figure by a global team of agents dispersed across locations to get the big picture of the impact that MIA can have on agent performance. The goal is to provide niche insights that augment full-time agent support, improve adherence to rubrics, boost quality scores, and enhance overall CX.
As part of the Movate AI platform, MIA integrates seamlessly into client IT ecosystems; it gauges and provides niche insights targeting agents’ adherence to well-defined client rubrics by measuring a host of soft-skill and linguistic parameters.
Auditing Agent Performance
Covering omni-channel support, predominantly voice, email and chat, the SSDET (Soft-skill Development Team) typically assesses, audits and score human agents against various well-defined quantitative and qualitative metrics, often structured around rubrics that are customer-specific and LOB-focused for auditing agent performance. For example, standard parameters include greetings, empathy, active listening, escalation handling, retention, upselling to name a few.
The conventional process would be to perform live monitoring, review recorded interactions, QA scorecards, speech analytics, and customer feedback surveys. But wait a minute. In a contact center witnessing gargantuan transactions in a day, manually auditing and periodically giving feedback on training requirements for hordes of agents is a costly, tedious and time-consuming rigmarole.
The exception to the rule
Consider a scenario where the SSDETs inadvertently sample out a false positive by considering a rare, isolated call where the agent unusually did well during the interaction with the customer. What if that agent was given a high score by chance because of a random sample that didn’t accurately represent the agent’s performance overall?
In the hum drum of the operations floor, it would be a herculean process to manually sort through the records to review those specific records again. This is like finding a needle in a haystack.
This is where MIA comes into the picture. Unlike a rule-based solution, Movate AI’s solution has that uncanny human-like reasoning power to autonomously self-learn (over a period) exceptions, rubrics, and isolated incidents of skewed agent performance (contrary to the norm) across scenarios and recommend performance improvement programs to the floor managers.
Real-time deployment use case
Commenting on the solution’s real-time implementation use case for a client and its successful first-mover entry in the contact center landscape, Krishnan Gopalrao, Vice President of Movate Propel Labs stated, ‘‘MIA can automate records across formats such as audio, chat, email transcripts, benchmark performance against different set of rubrics (as in the case of different customers) and provide precision quality analysis in a jiffy.’’
The (AI)gentification of interactions is here. Real-time experience of successfully deploying an GenAI-powered interaction analytics solution with an agentic AI flavor positions Movate as a pioneer in the market.
Swift go-to-market
With no other solution in the industry coming close to what MIA can specifically deliver, Movate has been quick in AI-first adoption and prototyping which gained swift traction and visibility in terms of GTM and positive outcomes for clients.
By integrating Agentic AI solutions like MIA , contact centers can enhance customer experiences, streamline operations, and boost efficiency. The solution integrates with Movate’s proprietary platforms like Movate Edison to drive significant business outcomes like improved agent productivity and efficiency, elevated CX, CSAT levels and satisfaction, and reduced costs.
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Movate AI: Your solution to unclutter and demystify business operations
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Leap into the AI-first future boldly and purposefully with Movate AI.
Related information
- Blog: Deliver tangible ROI with Movate AI’s Universal Chatbot
- Web: Movate Edison – Movate AI – Suite for Enterprise Transformation
About the author
Thirumaran Dhanpal, Senior Architect at Movate Propel labs.
With over 16 years of extensive experience in diverse technologies and domains, including Microsoft technologies, Azure and AWS cloud services, and a specialized focus on Enterprise-Grade Generative AI applications, Thirumaran Dhanpal currently serves as the Senior Architect at Movate’s Propel Labs. In this role, Thiru leads various AI projects encompassing Generative AI and Agentic AI, overseeing successful use cases, solution development, model prototyping, and deployment for top global clients. LinkedIn