Brand Risk Analysis

Brand Risk Dashboard

Updated on: Friday May 10, 2024

Welcome to Infegy’s Brand Risk Dashboard. This dashboard identifies companies with crisis management opportunities.

Note: this version is locked, if you would like an unlocked version, please click here.

Power Ranking Overview

This gives you all of the brands currently undergoing brand stressors detrimental and harmful to their brand health.

Daily Power Ranking of Brands Most At Risk

See how brand position has changed over the last month.

Trend Data

Conversation volume and negative sentiment over the last 30 days

Individual Indicators

High ranking reasons these brands are currently at risk.

Methodology

We created this by analyzing and ranking brands based on collected posts within a rolling 30-day period, weighing various risk factors including market performance, regulatory changes, and public sentiment, all aggregated from multi-platform social media posts, blogs, news articles, and other publically available posts.

Each brand’s risk score is calculated using our proprietary weighted algorithm that factors in AI-derived financial, criminal, health, emotional, sentiment, and topic-based risk inputs. Our ranking methodology balances the distribution of negative emotions and sentiment with the overall post volume of conversation. We generate each input using Infegy IQ, our custom-built machine learning model trained on hundreds of billions of posts we’ve collected since 2007.

For a deeper look into thousands of customizable factors relating to the brands you care about, check out our flagship product, Infegy Starscape.

Data and Acknowledgements

Dataset period:
The data aggregated and analyzed with a rolling 30 day period. We update it daily using Infegy Starscape's API and the Infegy Social Dataset. Descriptions of brands and companies sourced from various online sources.

Descriptions of brands and companies are sourced from public websites. The original list of 2000 companies originates from Forbes. Text summaries were generated by large language models summarizing Wikipedia articles and might contain errors.