Automate AI-driven insight for Brand Building with Dash

From corporate finance to service operations, the usage of Artificial Intelligence (AI) has grown exponentially across all industries, with AI expected to contribute to a 21% increase in United States GDP by 2023. Natural language processing (NLP) and image processing are branches of AI that have helped data scientists align with business KPIs and deliver insight faster.

One company that is harnessing the power of NLP and image processing is Crant, a creative machine learning company that bridges the gap between marketing data and business value. Crant recently launched an AI platform that provides daily metrics and engagement analysis in a multi-page Dash app. They focus on a metric called “brand love”, which processes large volumes of data from multiple social media platforms to measure how attractive brands are for their respective audiences. In order to scale data processing capabilities and incorporate Python-based AI packages while maintaining front-end customizability, Crant data scientists transitioned from Google Data Studio to Dash Enterprise.

Join this upcoming customer spotlight with Crant to learn how they saved 28 hours per week on analysis time and brought innovation to marketing intelligence and reporting by:

• Developing a Dash app that measures and displays a company’s brand attractiveness in real-time, by drawing insights from historic, competitor, and benchmark data
• Conducting image processing from social media posts to identify key drivers for user behavior and offer smart recommendations to drive higher post performance
• Implementing NLP and semantic analysis with relation to DE&I metrics
• Offering outlier detection and contextualization of social media platform share depending on post engagement