Real-Time and Predictive Analytics Impact Agent Experience

Rebekah Carter

A proactive approach to agent experience

Strategy
Real-Time and Predictive Analytics Impact Agent Experience

To run a successful company, businesses need a lot more than just a focus on strong customer experience. If your agents aren’t engaged, productive, and efficient, then they can’t deliver the kind of meaningful moments your customers are looking for. That’s why “Agent Experience” is increasingly making its way to the top of the considerations list for growing brands.

For years, enhancing the agent experience has been a highly reactive process. Companies examine their employees’ performance with historical reporting and surveys. Over time, it’s possible to make changes that could stop turnover spikes from happening again or reduce agent problems.

But what if it was possible to predict problems and see issues in real-time?

Real-time and predictive analytics offers an opportunity to proactively improve agent operations.

Real-Time for Employees

Real-time analytics are reporting tools that allow companies to watch important metrics and KPIs in real-time. In the contact centre, these solutions often include insights into important information like the number of calls answered, or time to resolution for customers.

Though these real-time analytics are excellent for tracking where you could be losing out on customer opportunities, they also present an excellent opportunity for your employees. For instance, with real-time analytics, companies can create cloud-based wallboards that show employees their current status in regard to things like calls answered, or customer rating.

Being able to see this information is an excellent tool for gamification and engagement in the agent environment. Particularly now, in a hybrid world where employees might be working from home, real-time reporting makes it easier for staff to see whether they’re performing on par with their peers.

Employers and business leaders can even implement competition elements that encourage team members to work towards the best numbers in different metrics for a chance to win a prize. This kind of technology keeps staff engaged even when they don’t have managers around to motivate and supervise them.

Further Benefits of Real-Time Analytics

Real-time analytics allow employees to track their performance and make adjustments in real-time. This improves engagement across the enterprise, by essentially providing staff with constant real-time feedback. Team members can see, without micro-management from supervisors, where they need to accelerate their performance or make changes to their strategy.

If you’re using the right tools for real-time analytics, then you can also collect meaningful and contextual insights that show employees how to improve their scores. For instance, an analytics system could track the sentiment of customers who interact with an agent and show them that low sentiment might be why their review score isn’t as high as it could be.

All the while, real-time feedback also gives employers and supervisors the information they need to see where team members might need additional support or training. When you can see exactly where your agent’s strengths and weaknesses are at any given moment, it’s much easier to drop in and offer help at just the right time.

Many contact centre solutions with “barge-in” and whisper functionality could even allow a manager to take over when they notice the sentiment of a customer and an agent falling at a rapid rate, so that the agent is saved from the stress of the interaction, and the company has another chance to alleviate the issues of the customer.

Alternatively, a real-time analytics solution combined with an AI service could assist an agent in trouble by offering them guidance on how to move the conversation onto the right track. AI solutions can pull information from previous playbooks and conversations with the clients or use information from a CRM to guide employees.

Real-time analytics don’t just motivate your team members, they can act as a lifeline in difficult interactions – the kind of conversations more likely to send your staff running for the hills.

What About Predictive Analytics?

Real-time analytics in the contact centre or customer experience environment is like keeping your finger constantly on the pulse of what’s happening in a CX environment. This makes it much easier to see where agents need help at the moment, and how supervisors can help. Alternatively, predictive analysis is about looking into the future, based on the information you’ve gathered in the past.

With predictive analytics, you can improve the agent experience by ensuring that there are enough employees on hand to deal with complex problems and peaks in customer demand. Companies can see when their most chaotic time periods are, and take on extra staff when necessary, to handle the burden.

Predictive analytics can also demonstrate where employees might need extra help going forward, by showcasing some of the moments where your agents have had the most problems with customer interaction. This shows business leaders where to invest in additional training or help for their employees.

For instance, if your staff members are wasting too much time looking for customer information, maybe it would help to have a virtual assistant on hand? An AI bot could look for data instantly when connecting a customer to an agent, so the employee can focus on the conversation. When you identify what’s slowing your agents down, you can also determine what kind of measures you need to take to reduce that slow-down in the future.

Could Analytics Reduce Agent Churn?

Regular turnover is one of the most significant issues that any CX environment can face. Being understaffed has a ripple effect, leaving your remaining agents feeling overworked and overwhelmed, and causing problems with customer service.

You can even build a picture of what the perfect agent looks like, so you know how to improve your hiring strategy too. With real-time and predictive analytics, you can potentially determine some of the reasons why your agents are leaving and take steps to fix the problem.

Just as you can examine the sentiment and perception that customers have towards your business, you can also recognise the moments when your employees’ sentiment drops too. AI solutions can help you pinpoint the most problematic experiences that your agents face, so you can eliminate the hurdles that might be causing your staff to leave.

 

 


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