What is Agent Assist?

Agent assist is AI-powered software that detects keywords and phrases during a live customer service interaction to improve the experience. Used in contact centers, agent assist can help guide agents on how to deal with a customer query. It also introduces efficiencies, automating time consuming activities such as searching for customer information.

What is Agent Assist in the Contact Center?

Agent assist is used during live contact center interactions. The software detects keywords and phrases, and, based on them, collects and presents any relevant information an agent needs to support that customer service query. It also offers real-time notifications with suggestions and tips.

The Importance of Agent Assist in Customer Service

Agent assist technology improves customer care interactions on both ends. Not only do customers receive speedier and more efficient exchanges, but it can lighten the workload and pressure on agents’ shoulders.

Who Uses Agent Assist?

Agent assist is used primarily by contact center agents in digital customer service. It also can be used in online sales and digital engagement. Using agent assist tools across departments can ensure consistent communication with customers, regardless of which team they’re interacting with.

How Agent Assist AI Works

Agent assist uses natural language processing (NLP) and natural language understanding (NLU) in order to detect and understand keywords and phrases. Agent assist technologies then use machine learning (ML) to provide suggestions to agents based on the training data provided to the algorithm. ML can then continue to learn and optimize its responses and suggestions.

Pros of Using Agent Assist

Introducing agent assist to contact centers can improve productivity and benefit the bottom-line.

Increased Efficiency and Productivity

Agent assist can perform much of the time-consuming background work needed for smooth customer service interactions, making calls, chats and other customer interactions quicker and higher performing. It can also offer real-time suggestions to improve the quality of calls, providing feedback that helps to train customer service agents, allowing them to become more effective. This means agents can handle a greater number of calls while improving the consistency of customer interactions and helping to reduce and prevent errors.

Increased Customer Satisfaction

Agent assist leaves customers happier, as they are receiving higher quality responses from agents. Their problems can be resolved more quickly, and in the most optimal way. Customers also receive a more personalized experience, as agents are able to tailor their interactions based on the customer’s history, preferences and sometimes even personality.

Reduced Costs

The live guidance that agent assist provides service consultants during calls reduces training time for new employees. Agent assist can also improve the first-call resolution (FCR) rate, meaning less time and money is spent on the same customer. Agents can deal with more conversations, and they can even handle multiple chat interactions at once, lowering labor costs.

Cons of Using Agent Assist

Agent assist also has some drawbacks that you might think about when considering the technology for your contact center.

Perceived Loss of Personal Touch

While agent assist doesn’t remove or replace human agents, it takes away from the natural interactions they would have with customers, as they are being guided by what the software tells them. And whilst being able to handle more customer interactions is a benefit, it often means the personal and human-to-human connection can be lost for the sake of efficiency.

Risks of Inaccuracy

While AI technology has come a long way, it isn’t perfect. With different accents or dialects, keyword and phrase detection can fail to pick up important information in live calls accurately. ML algorithms are only as good as the data available and trained upon, meaning if the training data is not enough for it to learn from, responses may not be accurate.

Risk of Irrelevance

From customer information and context, agent assist systems can adjust to suit each customer. If the software is not trained properly, it can lead to irrelevant and nonspecific responses and recommendations to the customer.

How Do I Set up Agent Assist

It’s important to implement agent assist correctly to get the most effective and successful running of the software.

Define Clear Goals and Metrics

The first step you can take is to establish what you want to gain from agent assist software. This can help guide the decisions you make when setting up your system. As part of this, set the metrics and KPIs that can measure the performance of your chosen software.

Discover Ways Agent Assist Can Make an Impact

In researching agent assist, you can learn the full extent of its capabilities. With this, you can evaluate your contact center and understand how agent assist would improve your processes and efficiency.

Adopt Features Based on Needs

Not all agent assist software is equal. It’s important to identify what you need from yours. With this, you can ensure that everything you need is implemented and that you aren’t wasting money on unnecessary features.

Monitor and Evaluate Performance

Like any platform, ensuring it continues to be effective after implementation is worthwhile. By checking your agent assist software against your chosen KPIs, you can monitor its performance and understand where it works well and where there are still inefficiencies.

The Future of Agent Assist

As AI technologies continue to develop and advance, we can look forward to agent assist technology becoming more effective and commonly used in the contact centers of the future. As NLP and NLU improve at understanding and interpreting speech, agent assist can make its recommendations and actions more accurate.

Personalization and relevancy will likely improve as agent assist software develops to better understand customer information and context. Automation is also likely to increase, meaning agent assist can handle more complex situations without human intervention and remove more workload from human agents.

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