Reject the urge to rely on the same contact center metrics you always have. Instead, access clear views of agent performance and industry trends, while unlocking the power of AI to transform your contact center into a business intelligence engine.Try it now
Spinning your wheels analyzing call center data that doesn’t improve performance? Our dashboards give you prompt analysis of customer interactions. In moments, analyze data and see the metrics that matter now.
Analyze every conversation
Respond swiftly to emerging trends
View in-depth agent performance
Benchmark against industry leaders
Zero in on issues right when they happen with Tethr’s laser-focused scoring, and provide call center agents with recent examples and real solutions.
Difficult customer interactions can lead to customer churn. Reduce churn and build loyalty at the same time by identifying and eliminating areas of friction in your contact center.
In a world where 84% of your customers want their problems solved the first time they contact you, ensure your team is up to the task. Tethr’s analytics tools empower your team, getting you closer to first call resolution with every customer.
Use speech analytics to automate call center QA, so you can base findings on comprehensive call data and not sporadic evaluations. Build your digital transformation on a solid foundation of real VoC data.
"Once we deployed Tethr, we could really map out our ideal agent, and how they deploy positive behaviors."
“When we started analyzing calls with Tethr, it was as if shackles had been removed from our entire team. Armed with quantitative data, we could take sustainable steps to improving the experience along the entire customer journey”
Call center analytics software automatically analyzes your call center operations and agent performance and provides actionable insights for your organization.
While some call center software analyzes metrics that focus solely on call volume, agent productivity, and others, Tethr gives you a full picture of both your customer experience and agent performance.
Some of these metrics include customer satisfaction, customer engagement, and a customer effort score. We also use various customer data sources to understand customer trends, such as churn risk.
Advanced analytics tools combine artificial intelligence, existing data, and call center predictive analytics to help improve your call center’s performance.
Using a combination of the data we extract from your customer engagement channels and machine learning, we allow you to easily spot problems in your contact centers, accurately measure customer satisfaction and agent behaviors, and identify customer trends.
You can use these actionable insights to drive business outcomes, such as improving customer loyalty.
A good customer service agent can provide an excellent customer experience while reducing the cost of services. Tethr taps into the power of machine learning and artificial intelligence to measure how effective call center agents handle customer feedback and customer relationships.
We score each agent and team based on the agent’s impact and on the call difficulty, and provide succinct, actionable information that tells you what your call center team is doing right – and what they need to fix.
Our call center data analytics software analyzes data from contact centers such as average handle time and other key performance indicators, but also works on improving customer satisfaction by measuring and identifying other agent behaviors such as uncertainty, confusion, and negative language.
We know your customers don’t always speak directly to call center agents. We have many customers who use Tethr to analyze the call center operations, but we don’t stop there.
Our suite of contact center analytics solutions can also analyze conversations you have via web conference, chatbots, live chat, and case management. We also offer integrations with customer relationship management platforms and several cloud service providers.
The voice of customer (VOC) refers to the customer feedback about a particular product, service, or experience. It is important for companies to listen to the voice of the customer to understand their overall customer experience and customer journey and identify what's needed to improve their offerings. Companies often collect voice of customer data from customer surveys, but increasingly, companies rely on artificial intelligence tools to capture actionable insights about customer sentiment from customer support team conversations and sales calls.
Voice analysis software is a technology that analyzes conversations using AI and machine learning to determine customer and agent engagement, customer sentiment, and effort level. It is often used in call centers and customer service settings to improve communication between customer service agents and customers.
Customer service metrics are performance indicators that measure how well a company is serving its customers. Examples of these metrics include average handle time, response time, resolution time, customer effort score, customer retention rate, and customer satisfaction scores.
Conversation intelligence software, also called call intelligence software or conversation analysis software, is a platform that analyzes customer interactions, such as phone calls or chat messages, to extract valuable insights and improve communication strategies. This software can help companies improve customer service, cut costs, reduce churn, and increase revenue. Companies use conversation intelligence software to gain insight into customer expectations, customer behaviors, sentiment analysis. They can also gain contextual information about key metrics for customer service department performance and individual agents' performance.
A call center agent performance scorecard is a tool that measures the performance of call center agents based on various metrics such as call volume, call duration, customer satisfaction, contact resolution rates, and more. Scorecards help managers identify areas for improvement and track progress over time.