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Webinar: July 14th at 12pm ET

Reinventing Reputation Measurement for an "Always-On" World

 

In an era of vast societal polarization and the growing demands of value-driven stakeholders, brand's need to take visible, proactive (and sometimes controversial) positions on hot issues of the day has made managing reputation more challenging than ever.  

 

The old adage, "you can't manage what you can't measure, and can't measure what you can't define" is certainly apropos for today's brand and communication leaders who have struggled with largely static, traditional survey-based approaches when the world around us is changing day by day and reputations are impacted by "almost everything."

 

The good news, help is on the way in the form of new reputation measurement solutions that combine "real-time" unstructured social and Voice of Consumer today together with AI-assisted "natural language understanding technologies and advanced analytics that are game-changers for reputation and brand management execs.  

Register today! In this webinar you’ll learn:

  • The limitations and challenges of survey-based reputation measurement solutions

  • How new "always-on" reputation measurement approaches address new needs in terms of actionability, "in the moment" measurement, and adjusting for rapid changing stakeholder demands and expectations

  • Why a new Social Reputation Index solution can help predict in advance how specific future actions might be perceived by different stakeholders and their potential impact on reputation.

  • How new reputation scoring is moving beyond vanity metrics and being tied to business outcomes such as sales and shareholder value at leading organizations

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Conversus.AI is the leader in MLaaS for this type of natural language processing. Provided by Converseon, the platform is already intelligent, having been rigorously trained over the last decade across more than 20 industries and more than a dozen languages. It was named “Top NLP” Platform by the 2019 AI Breakthrough Awards and Quirks Marketing Research and Excellence Award Winner. With effective use, its models generally outperform individual humans and transform this messy unstructured data into insight-rich research-grade data.