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Mapping patterns with GenAI

Illuminate the behavior of your customers and agents in the contact center with Accenture Conversation Analytics & Language Modeling (CALM) and Generative AI (GenAI).

GenAI + data for intelligent engagement

Customers expect personalized, proactive, and automated experiences on their preferred channels. However, many companies lack the context around customer call intents to create meaningful insights—leading to ineffective virtual agents and frustrating experiences.

Accenture Conversation Analytics & Language Modeling (CALM) is a data-led analytics and insights tool that leverages GenAI and traditional data science to identify the real, root-cause reasons why your customers are engaging with you and the common steps agents take to address these calls.

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Delivering data-driven customer care

Accenture CALM combines an advanced intent discovery tool with conversational modeling capabilities, enabling users to access rich context and data-driven information.

Effortlessly analyze and generate reports on customer service interactions. Accenture CALM is an innovative solution that combines an advanced "intent discovery" tool with conversational modeling capabilities, providing rich context and data-driven information.

Gain valuable insights that help shape your strategies along with modeled interactions to utilize in virtual agent development.

Accenture CALM on AWS Marketplace

Why Accenture CALM?

50,000

transcripts analyzed at once - analysis at scale!

30%

acceleration in conversation IVR development with generated customer opening utterances.

15%

improvement in operational efficiency.

10%

increase in agent efficiency.

Gain an unbiased understanding of the intents behind consumer touchpoints, their sentiments, sub-intents, hierarchies, and impact on key performance indicators (KPIs) within the business:

  • Customer pain points: Voice of the customer analysis (IVR voice transcripts, emails, live chat, support feedback surveys, etc.).

  • Call prevention: Identify intents that are good candidates for proactive messaging.

  • Self-service and automation: Identify intents that are good candidates for "AI-powered self-service".

  • Self service improvements: Identify interactions where customers' attempts to self-serve have failed.

  • Optimize your IVR journey: Improve containment and identify IVR changes by combining call analytics with IVR flow analytics.

Understand the flow of customer-agent conversations and intent resolution through the automated creation of Conversation Flow Maps:

  • Enhance agent performance: Identify agent training opportunities to address inconsistent or inefficient customer handling.

  • Effective process improvements: Identify process and communication improvements to reduce specific interactions (boomerang calls, repeat touchpoints).

  • Build a foundation for Virtual Agents: Accenture CALM’s key input into conversational design accelerates Virtual Agent creation and identifies exception paths to consider.

Our leaders

Kym Gully

CTO and Customer Engagement Business Lead – Accenture Products and Platforms (APP) Data & AI

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Darleen Svatek

Go to Market Lead, Customer Engagement - Accenture Products and Platforms (APP) Data & AI

LinkedIn