• April 25, 2017

Frrole Launches Scout Analytics App

Frrole, a provider of consumer and social intelligence products, today announced its latest product offering in Scout, built specifically for marketers, analysts, and researchers. Scout was built using artificial intelligence that offers deep consumer insights based on social analytics.

Scout is a complete social intelligence tool that offers audience intelligence, social listening, and on-demand research all in a single platform. Scout leverages Frrole's AI platform, which offers meaningful and intelligent insights into consumer personas, moods, demographics, interests, on-demand research, marketing activities and their impact, and real-time competitive intelligence.

"Enabled largely by machine learning and AI, a new generation of software is emerging on the scene which is changing what it's been possible to do for the customers. At Frrole, we are fundamentally reimagining what is possible with social data and are taking it much beyond its usual confines of social listening and measurement," said Amarpreet Kalkat, co-founder and chief technologist at Frrole, in a statement. "Our goal is to build a true next-generation consumer Intelligence platform that makes a brand-new future possible. We are also working on another revolutionary product called DeepSense, soon to be launched, which is built for product innovators and strategists and it offers deep consumer insights and personas that can make any product smarter for an ultimate product experience for users."

The Frrole platform can nderstannd billions of social conversations and relationships as they occur in real time. It leverages algorithms around machine learning, natural language processing, and named entity recognition to build this understanding and can then build thousands of data models based on traditional web data sources like Wikipedia, Freebase, Geo Maps etc.

Frrole's topic intelligence engine analyzes hundreds of millions of social conversations in real time by performing extensive analysis across varied statistical, linguistic, semantic and contextual layers. The derived insights can be used for use cases across marketing and analytics like brand, campaign, and competitor intelligence.

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