Conversation intelligence platform Converseon has announced the launch of a suite of AI-powered solutions to drive predictive analytics from conversational data. The aim is to predict business outcomes such as sales and evaluate the likely impact of future courses of action based on content in conversational and social streams.

The solutions include:

  • Social Brand Reputation Intelligence System: This measures, and predicts the impact of actions on, brand reputation, including environmental, social and governance (ESG) components.
  • Social Brand Relevance System: This looks at how well products and services match the needs of consumers in target markets. It monitors not just current needs but predicts future needs and how products can align with them.
  • Both solutions incorporate Assess (benchmark against past performance and key competitors), Diagnose and Predict modules.

Why we care. Monitoring website engagement, call center activity and transactional data is not enough in a world where stakeholders can address brands directly — or each other, with reference to brands — in streams of conversational and social engagement that exhibit enormous and increasing volume and velocity.

Using AI to capture positive and negative sentiment at scale, identify developing problems and create opportunities to engage, is in itself nothing new. The intriguing proposition from Converseon is that its tools can build predictive analytics on this analysis.

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Exponentially growing channels. “Exponentially growing social and related conversational data is a powerful source for predictive insight at a time it’s most needed, but such data all too often drowns brands with too much noise and hindsight insights,” said Rob Key, CEO of Converseon in a release. He considers the ability to connect real time conversation data to business outcomes an important step forward for reputation and brand measurement, social listening and customer intelligence.

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