Authenticx + Listening at Scale

What is listening at scale?

Exponentially listen with confidence and reliability. Aggregate topics, themes, and patterns from millions of conversations to drive relevant and impactful macro insights that enhance business and customer outcomes.

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Key Benefits of Listening at Scale

Amplify

Amplify large samples of data that represent your entire customer population without adding headcount.

Leverage quantitative and qualitative data sources by aggregating millions of conversations.

Guide

Convert conversations into aggregated patterns and themes to guide business strategy and initiatives.

Listen across an array of channels that represent the totality of people you’re serving.

Innovate

Leverage machine learning, AI, and rule-based classifiers to exponentially for macro insights of your customer population.

Pivot quickly and effectively implement identified opportunities and challenges.

What is listening at scale?

By leveraging automation and machine learning technologies, large quantities of unstructured data can be processed and analyzed quickly. This enhanced scale provides support to allow for quicker change (because there is quantitative and qualitative data insights) and better resource allocation to best serve customer needs.

Listening at scale amplifies the voice of the customer so businesses can understand what is working well, pain points, and opportunities for improvement.

What is the impact of listening at scale?

Every day, millions of conversations occur in contact centers – but there’s no way to impactfully listen to all of them without the help of technology to synthesize the data into actionable insights. Oftentimes data sources are siloed, offering only a partial view on what’s actually happening.

Listening at scale matters because it provides an inclusive and representative overview of all customer conversations. This allows decision-makers to devise responses and a course of action at a strategic and tactical level that is informed by an honest, comprehensive view on what’s occurring across the enterprise. By understanding the full scope of the challenge or opportunity, decisions can be made with a high degree of confidence.

How is Authenticx unique in leveraging listening at scale?

Our machine learning models empower organizations to listen to a high volume of conversations.

No one else in the industry is creating a path for leaders to sort through the noise symphony of what’s out there to directly point to what’s important, what to pay attention to, and understand the problems of the customers and people they serve.

At Authenticx, we think of listening at scale like a funnel that empowers companies to scale listening responsibly. At the top of the funnel, there’s an ability to ingest and analyze the totality of customer interactions regardless of telephony, vendor, chat, call, email, text, audio, etc.

This enables leaders to zoom out and see a full picture with usability and actionability, so that in the middle and bottom of the funnel, there can be intentional and direct human-listening, such as:

Individual evaluations
Insight analysts
Data-backed storytelling

This ability to listen to individual conversations (with humans) fuels artificial intelligence tools to be built with high confidence to a macro, inclusive, and immersive view to inform hearts and minds to empower change in healthcare.

We’re changing the game in healthcare by listening at scale.

Authenticx automates millions of customer interactions, bringing context at scale.

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Authenticx Solution | Speech Analytics Software

Conversational Intelligence

Frequently Asked Questions

Artificial intelligence (AI) is the development and deployment of computer systems that can perform human-oriented functions, such as decision-making, predicting outcomes, assessing efficiencies, and automating a specified task.

Machine learning leverages computer algorithms to build models that help assess and analyze data sources. These machine learning tools are becoming increasingly utilized for processing vast amounts of digital data to help identify insights and trends that help pinpoint when, where, and how organizations can be the most effective and impactful.

Conversational intelligence uses artificial intelligence, machine learning, and natural language processing to answer questions, provide quality service, and enhance the customer experience from unstructured conversation data.

While the benefits are countless, we place them into three main categories:

Scaling: Effective AI tools, such as deep learning, help evaluate and represent your entire customer population—leveraging conversational analytics in one, consolidated location.

Monitoring: Take in a meaningful and statistically valid sample of customer conversations to filter and analyze interactions to determine intent, emotions, and meaning.

Automating: Summarize trends across a full data set to drive deeper, more intentional analyses that help predict outcomes with autoscoring.

AI is already starting to be widely adopted across healthcare. When these tools are utilized to build personalized, adaptable, and data-driven solutions, the untapped potential to impact grows.

The healthcare journey today is complicated with many different communication touchpoints between customers, healthcare providers, insurance payers, pharmacies, and manufacturers. Being able to build a macro understanding can drive action at a micro, individual level. Listening at scale leverages innovative tools paired with human understanding to identify where disruption is occurring.

+ Clinical documentation and form submissions

+ Diagnosis, treatment, and therapy plans

+ Claims and benefits verification

+ Customer support and communication

+ Monitoring quality and data trends

+ Fraud monitoring and prevention

+ Customer sentiment and emotions

+ Agent and call center performance, such as coaching and training

+ Marketing messaging and insights, such as brand detractors

+ Common customer questions, complaints, and grievances

See Authenticx Use Cases →

Machine learning is integrated through Authenticx, making it accessible for even non-technical users. Our machine learning models are specialized for healthcare because they were built using healthcare conversations. This allows our models to have greater accuracy and compliance with sensitive information by listening at scale.

As users interact with conversational data within the platform, their actions provide a feedback loop to Authenticx’s machine learning models, allowing ongoing and real-time improvements to the system. The following are some of the machine-listening tools utilized:

+ Speech analytics

+ Transcription

+ Search and find features

+ Trained machine learning models

+ Unsupervised identification models

Authenticx focuses on conversational intelligence for enterprise healthcare.

We use artificial intelligence, machine learning, and natural language processing to leverage unstructured data sources to answer questions, provide quality service, and enhance customer support.

Conversations include audio, text, chat, email – anything that is bi-directional and unsolicited. We specialize in structuring this data and giving healthcare leaders the ability to analyze and activate it at scale with quantitative and qualitative insights.