First-call resolution, average handle time, service level standards, call abandonment, sentiment, and customer satisfaction—These are all common metrics used in contact centers to help healthcare call center quality leaders assess and monitor the performance of their teams and allocate necessary resources. Call center quality monitoring offers important insights across the enterprise from marketing to operations to compliance and patient experience.
However, despite ongoing monitoring, it’s not uncommon for leaders to feel like they lack visibility into how well their teams are performing and lack a strong grasp on what frontline employees encounter day to day.
Anecdotally, field and call center agents may be reporting that callers seem more hostile and metrics are showing longer hold times and higher call volumes. But even knowing this, it’s hard for leaders to proactively drill down to understand the root cause of these data insights. Most of the time, the focus remains on identified complaints and problems in a reactive approach.
Why it’s Important to Scale QA Programs
To build healthcare call center quality and patient-centric experience, leaders need insights into customer needs. Currently, there’s a missed opportunity in utilizing data sources that already exist inside the contact center: analyzing recorded conversations that are being stored for quality assurance and compliance purposes. Leveraging conversational data insights offers context and clarity and renews focus on why certain leading indicators are recurring.
Tapping into this data source offers a way to assess richer conversations from customers, give greater visibility into reported quality metrics, and help drive strategic decision-making.
This means shifting strategic focus away from a reactive (only responding to problems as they arise) toward a proactive (seeking to identify root causes of agent and customer disruption) response that ultimately helps reduce call center agent burdens and build a patient-centric experience.
5 Ways to Build a Proactive, Quality-focused Approach with Authenticx
1. Establish Scorecard Benchmarks
A main driver in establishing high call center quality is consistency. Benchmark data establishes a scoring threshold that gives visibility into the current state of the program that helps improve the ‘bad,’ expand on the ‘good,’ and maintain consistent performance with both real-time and historical insights. Quality score benchmarks both quantify and qualify feedback that is configurable to specific business needs. Authenticx provides a weighted score system that allows teams to focus on KPIs that matter when assessing business goals in place.
2. Draw Insights from Customer Conversations
Recorded call center conversations offer a wealth of insights that can be filled with compliance issues, agent coaching ideas, and opportunities for improvement. To be truly patient-centric, leaders can learn to anticipate customer needs by listening to them directly. Authenticx leverages machine learning to organize unstructured data with search capabilities, tagging, categorization, and compiling audio libraries for sharing.
3. Pinpoint Ways to Train Agents & Teams
Front line employees are often a customer’s first experience with the organization. Having a mechanism that offers visibility into individual agent quality scores provides coaching opportunities and pinpoints training needs. Authenticx helps platform users sample individual agent calls for an enhanced coaching process that promotes opportunities for managers to provide both constructive and complimentary feedback and notes.
4. Gain Visibility into Vendor Performance
Many healthcare organizations partner with vendors to help manage their call centers. Listening to recorded conversations can provide feedback to vendors to improve consistency and share insights on nuances specific to individual program needs. Authenticx offers a third set of eyes that stands as a neutral party to assess and monitor quality scores to reaffirm quality assurance.
5. Leverage AI and Automation Tools
There is a lot of innovation happening regarding automation and AI implementation. Automating quality monitoring is a critical component in managing volume, as well as improving sampling. Many call center quality leaders typically sample less than 1% of the total volume. There are very real resource constraints that limit teams, agents, and processes. Investing in AI and automation offers opportunities to evaluate more calls and aggregate data insights for a fuller picture of what’s happening.
Tell Me More About How Authenticx Works with Quality Leaders
Healthcare call center quality leaders need to feel confident in their quality scores. Particularly across healthcare, there’s a critical need to identify barriers so processes can be improved. Authenticx was founded to surface meaningful insights from unstructured data. We help leaders strategically invest to optimize their quality assurance metrics to improve customer experience and operational effectiveness.
Our platform provides automated evaluations that review audio and metadata obtained from IVR systems. With out-of-the-box or fully configurable options, our solution offers a healthcare-specific quality solution.
About Authenticx
Authenticx is the new standard for listening at scale with artificial intelligence. The platform brings conversational intelligence to healthcare by analyzing millions of customer interactions (like voice, chat, or emails) to surface immersive and intelligent insights. Authenticx was founded to aggregate, analyze and activate customer interaction data to surface transformational opportunities in healthcare. Using existing data that’s being stored and ignored in your organization, Authenticx reveals hidden barriers, motivators, and strategies so healthcare organizations can make confident, data-backed decisions.
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