What is an agent assist?
An agent assist is an AI-powered software that aids contact center agents in providing exceptional customer support by analyzing case context in real time, offering relevant suggestions and predictions through machine learning, and identifying potential red flags in responses like profanity or bias.
Just as 4.2 billion people have found virtual agent assists to be a useful part of their everyday lives, contact center agents benefit from having AI assistants there to help them deliver excellent customer support.
How does an agent assist work?
An agent assist uses artificial intelligence to analyze customer-agent interactions in real time and recommends relevant responses that are brand compliant and supported by knowledge base articles. Using natural language processing (NLP) and speech recognition, agent assists can understand query context, identify customer sentiment, and highlight similar cases with relevant workflows for agents to reference.
NLP and speech recognition further help the agent assist to evolve with each agent-customer interaction over time and provide accurate information to customers.
Key features of an agent assist
An agent assist helps automate agent workflows, like call transcription, call summary, and scheduling call-back — improving agent productivity.
Learn more: Turn high-performing service agents into a guide for others with smart AI and automation
Agent assists scan and evolve with each agent-customer interaction and recommend suggestions accordingly to help agents resolve customer queries in the best way possible.
Improves agent productivity
After implementing agent assists, you’ll notice a visible improvement in your agent’s productivity, CSAT, FCR, customer experience, and other important customer service metrics.
Why does your customer support team need an agent assist?
1. Reduce agent ramp-up time
By utilizing an agent assist to recommend intelligent responses and highlight non-compliant terms, you can reduce a new hire’s training period significantly and help them reach an acceptable performance level fairly quickly after onboarding.
2. Improve first contact resolution (FCR) rates
Agent assists continuously scan agent-customer interactions and surface self-service options such as knowledge base articles and FAQ pages — enabling them to recommend real-time intelligent responses that agents can use to augment their responses to customers.
Agents can choose the most appropriate response and send it to the customer, improving both customer response time and FCR rate.
3. Keep costs under control
Agent assists empower agents to handle multiple conversations simultaneously and help customers get the right support at the righttime, reducing operational costs and time-per-interaction.
4. Keep customers happy
Customer satisfaction (CSAT) is a customer service metric used to gauge the extent to which a customer is happy when they interact with your company. A higher CSAT represents happier customers.
You can increase your CSAT scores by empowering agents with AI-driven resources to anticipate customers’ needs, solve issues faster, and drive better resolutions with a human touch.
5. Keep agents happy
Happy agents lead to happy customers. If your agents receive an overwhelming amount of queries with little to no help from contact center managers to handle them efficiently, it can lead to agent burnout and churn.
A good AI-powered agent assist helps boost agent productivity by simplifying their tasks with brand-compliant suggestions and automates repetitive, manual tasks that keep support agents from meeting their SLA targets.
Best practices for making the most of your agent assist
Providing agents with an agent assist doesn’t ensure a positive customer experience unless you make continual updates to the information that the AI-powered software draws from.
Here are a few things you can do to ensure that your agent assist performs at its best:
Feed your brand guidelines to the agent assist
Brand guidelines reflect an organization’s values and help ensure a consistent customer experience across touchpoints.
Agents follow these guidelines to have brand-compliant interactions with customers, but agents can sometimes forget to stick closely to the guidelines, leading to negative customer experiences.
An AI-driven agent assist scans agent responses in real time and flags them if they are non-compliant with brand guidelines. This only works, however, if you feed your brand guidelines to your agent assist software every time they’re updated.
Identify common queries and create suitable workflows
Contact center managers and supervisors should regularly review agent-customer interactions, or at least have frequent discussions with agents about their conversations, so that you can identify the most common problems that your customers face.
Once you are aware of their pain points, create suitable workflows and feed them to the agent assist so it can highlight those workflows to agents whenever similar cases appear. Remember to update these workflows regularly to keep up with customer requirements and expectations.
Monitor, measure, and improve
Don’t set up your agent assist once and then trust it to perform optimally forever. You should continually monitor its performance, KPIs, and other customer service metrics, including:
Customer satisfaction score (CSAT)
Customer retention rate (CRR)
Number of upsells and cross-sells
Customer lifetime value (CLV)
Consistent monitoring and analysis of these metrics will help you determine whether — and how — implementing an agent assist benefits your business. This analysis will also help you discover opportunities to improve your customer service experience.
Transform your agent experience with Sprinklr’s AI Agent Assist software
Sprinklr’s AI Agent Assist is a powerful solution that makes your agents happy — and your customers happier. As the world’s first unified customer experience management (Unified-CXM) platform, Sprinklr empowers agents to interact with customers across 30+ touchpoints and delight them using an AI-powered agent assist that can:
Highlight similar cases supported by AI-generated replies
Sprinklr AI matches current customer conversations to resolved cases in your data set — and surfaces valuable insights to help agents deliver the best customer resolutions.
Accelerate agent response times by identifying standard procedures for common use cases
Sprinklr AI uses your organization’s best practices to match customer intent to the correct step-by-step procedure and automatically presents that information to agents during customer interactions. AI then scans in-progress agent responses and flags them for violations of policy (discriminatory language, profanity, tonality, and relevance) before they hit “Send.”
Optimize agent supervision by predicting CSAT scores before cases close
Sprinklr AI reads sentiment, intent, emotion, intensity, and time between responses to learn which factors result in high or low CSAT scores — giving agents a live early warning signal and alerting supervisors to intervene if a predicted score drops below thresholds.
Try Sprinklr Service today and make fast, personalized customer service a reality for your business.
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