DAASH provides an AI-powered platform delivering predictive commerce intelligence for the beauty industry. The system uses proprietary data and machine learning to generate weekly updates on competitor channel-specific rank, sales estimates, and product attributes. This enables brands and financial services to make data-driven decisions regarding innovation, market share analysis, and competitive benchmarking.
Funding
$5.5M raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
BCFounders
Product
Problem
Consumer brand owners in the beauty industry often lack timely, granular data on competitor performance, making it difficult to understand market share dynamics and identify revenue-driving products. Traditional market research methods are often slow, expensive, and provide limited visibility into rapidly changing trends.
Solution
Daash Intelligence provides weekly insights on competitor sales performance, market share, and emerging trends in the beauty industry, leveraging proprietary data and AI algorithms. The platform delivers channel-specific data on product rank, sales estimates, and key attributes, enabling brands to quickly identify top-performing products and understand competitive advantages. By combining data from research panels, search traffic analysis, and public data enrichment, Daash models sales performance and market share with a high degree of accuracy. This allows brands to make informed decisions about product development, marketing strategies, and competitive positioning.
Target Audience
The primary target audience includes marketing and sales teams at consumer beauty brands who need timely, granular data on competitor performance to inform strategic decisions.
Features
- Weekly updates on competitor sales performance and market share
- Channel-specific data on product rank, sales estimates, and key attributes (e.g., category, ingredient, benefit)
- AI-powered analysis of emerging trends and product demand
- Identification of revenue-driving products for each competitor
- Sales estimates and units sold estimates for specific products
- Data-driven insights into competitor strengths and weaknesses
- Competitive ranking at retail and direct-to-consumer (DTC) channels