What are real-time call analytics?

Sara Yonker

April 17, 2023

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How many times have you thought of a perfect response minutes or hours after a conversation ended? In your personal life, those would-be perfect responses might torment your psyche. In the business world, it can cost you a customer.

Now, AI can help remove the conversation lags, bad information, or confusion with real-time insights and real-time agent assist. These AI-powered capabilities give contact center agents personalized prompts and notifications while they’re in the midst of customer conversations. Meanwhile, contact center managers can configure customizable dashboards that show them important metrics about customer interactions as they happen, so they can coach to improve agent performance.  

What are real-time analytics?

Real-time call analytics area a type of contact center analytics solution that give contact center agents and managers a real-time view of critical metrics.  They use a few key technologies together: real-time speech analytics, real-time transcription, artificial intelligence and natural language processing. Agents and sales reps are able to get actionable insights into customer behavior, preferences, and pain points during a conversation - not after the call ended.

With real-time monitoring, businesses can monitor key metrics as they happen, identify patterns and trends, and take action to improve the customer experience. For example, if a customer has been on hold for a long time or an agent has been silent for too long, the system can alert the agent to provide an update.

Real-time call analytics can help businesses measure the effectiveness of their customer service efforts, allow call center supervisors to intervene when necessary, and help agents handle complex situations in the moment. By analyzing call data, companies can determine which agents are performing well and which ones may need additional training or coaching. They can also identify areas where the customer experience can be improved, such as reducing wait times, providing more personalized service, or streamlining processes.

What is the difference between real-time analytics and post-call analytics?

Some metrics can be measured in the moment, such as phrases customers say that indicate they're experiencing a certain issue or interaction analytics that evaluate hold times. Other metrics require calculations that measure the complete picture, after a conversation is over.

For example, many contact centers find value in measuring average call handle time, abandonment rate, conversion rates - things that can only be calculated at the end of calls. Post-call analytics also provide historical reports that give valuable insights about your customer experience as a whole, such as the top customer issues and contact center productivity. 

How do real-time call analytics help businesses improve their customer satisfaction?

Contact center analytics software exists for two reasons: to improve the customer journey and contact center operations.

  • Less confusion: One of the biggest benefits to real-time call analytics is the ability to provide agents with accurate, useful information about the specific issue a customer calls about. Specific phrases or questions can trigger automated pop-up links to troubleshooting guides or knowledge base articles, so the agent has the exact information they need to guide a customer through a call.
  • Prompt attention: If a conversation lags with too much silence time or too long of a hold, agents can receive reminders notifying them to give customers updates on the situation.
  • Compliance adherence: Many companies use real-time call analytics to ensure that customer service agents follow all compliance requirements. If an agent forgets to read a disclosure or skips a QA step, the real-time call analytics can alert the agent to do so, preventing compliance risks.
  • Supervisor alerts: Contact center supervisors can receive alerts when certain things happen. For example, perhaps a supervisor wants to know if a customer has threatened to file a complaint.
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How can businesses implement real-time call analytics in their operations?

Implementing real-time call analytics in business operations requires careful planning and execution. If you're interested in implementing a real-time call monitoring solution, you need to consider your business goals and how you'll implement the technology into your team's current workflows. 

1. Invest in the right technology

Before companies can implement real-time call analytics, they need to invest in the right technology, such as a cloud-based call center platform, that supports real-time call analytics.Consider whether you want only audio steams (such as phone calls) or a solution that also provides real-time analytics for chat conversations as well. 

2. Define alert triggers and KPIs

Once the technology is in place, businesses need to determine what types of alerts they want agents and supervisors to receive and find a platform that can provide that. Many agents find that too many alerts can distract them from a conversation, so finding a system that allows custom configuration will help agents instead of distract them.

Companies must also define their key performance indicators (KPIs) and establish a process for collecting and analyzing data.

3. Implementation and Training

Once you select a platform for real-time call analytics, you need to integrate it with your existing call or chat platform, as well as any CRM software. It's also essential to train agents on how to use the real-time call analytics system and how to leverage insights to deliver exceptional customer service.

Additionally, companies need to establish a feedback loop to continuously monitor and improve their operations based on customer feedback. By taking a strategic and proactive approach, businesses can successfully implement real-time call analytics and reap the benefits of improved customer service and increased customer loyalty.

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