What is Agent Assist?
Agent Assist is an AI-driven tool in contact center technologies that supports human agents in customer interactions with real-time tips and post-interaction agent coaching.
Agent Assist uses Natural Language Processing to understand human language and sentiment analytics to track how customers feel about solutions during an interaction. It draws from company databases and real-time analytics to provide suggestions for improving customer satisfaction and compliance adherence.
Quick facts
- Function: AI-powered tools draw from knowledge bases, customer history, and real-time analytics to automate repetitive support tasks and provide real-time and post-interaction tips for improving performance speed, quality, and accuracy.
- Domain: Agent Assist tools deliver consistent experiences across phone, voice, text, chat, and social media channels in a unified platform for streamlined workflows.
Who uses it: Contact center support agents and teams across industries use Agent Assist to enhance productivity, reduce costs, improve customer experiences, and expertly handle complex inquiries.
Why it matters
- Customer experience (CX): Agent Assist optimizes CX by elevating service quality and personalizing support with compliant solutions tailored to customer needs and preferences.
- Agent experience (AX): Agent Assist automates routine tasks and offers process guidance, reducing workloads while boosting productivity. It streamlines interaction handle time and enables agents to focus on complex requests, improving agent confidence, proficiency, and satisfaction.
- Cost: Depending on the technology platform, Agent Assist features can come with additional implementation or monthly fees. Still, it can be highly cost-effective by increasing agent productivity, service capacity, and agent and customer satisfaction and retention.
- Quality: Agent Assist improves service quality by providing policy-compliant tips based on keywords in an interaction.
- Speed: Live assistance reduces the amount of time agents spend searching for answers, reducing handle time, wait time, holds, and transfers. Faster service allows teams to handle more interactions.
- Compliance: Agent Assist flags potential violations, enabling agents to de-escalate situations and proactively resolve issues.
How it’s used in BPO
Agent Assist is used in support and sales interactions to optimize customer experiences and contact center workforces. Agent Assist automates interaction handling across all communication channels. Automated QA scores each request and solution based on predefined criteria.
Monitoring and improvement
Continuous performance monitoring ensures agents and AI models perform up to standards.
Key Performance Indicators (KPIs)
Specific metrics track performance quality and highlight areas for further coaching and improvement. The following KPIs are vital to the success of any contact center team.
- Service Level Agreement (SLA): An SLA is a contractual agreement between a company and a service provider spelling out which services the BPO will provide, the expected level of performance, and the metrics used to measure performance quality.
- Average Handle Time (AHT): AHT is the amount of time it takes, on average and including after-call work, for an agent or a team to close a support ticket. Agent Assist can reduce AHT through real-time assistance and automated after-call notes and summaries.
- First-Call Resolution (FCR): FCR measures the success of solutions by tracking the rate at which complaints are resolved the first time a customer contacts the support team. Agent Assist can improve FCR by unifying the customer experience with consistent and compliant guidance.
- Customer Satisfaction (CSAT): Measured on a scale of 1 to 5 or by percentage out of 100, CSAT describes how satisfied customers are with a product, service, or company. Agent Assist can improve CSAT by personalizing support using comprehensive analytics. Automated surveys capture how customers feel about support when it’s fresh on the mind after an interaction is complete.
- Quality Assurance (QA): QA measures support quality by scoring interactions and solution accuracy against a company’s guidelines and performance standards. Agent Assist improves QA scores with accurate, compliant suggestions and tips triggered by key phrases and live sentiment tracking.
Agent Assist risks, limitations, and compliance
- Misuse and misinterpretation: Over-reliance on AI tools can lead to a failure to correct misinterpretations of contextual or industry-specific language or knowledge, increasing inaccurate responses.
- To mitigate this, teams should regularly update industry-specific terms and QA the Agent Assist model performance.
- Data privacy considerations: Agent Assist analyzes sensitive personal information, putting companies and customers at risk in the case of data breaches or security attacks.
- Reduce risks by strictly following all industry-specific compliance regulations and global laws for handling customer information. Implement strict security guidelines, frameworks, and access controls to protect customer data.