VOIDS provides an operating system that utilizes advanced forecasting algorithms to optimize supply and demand for e-commerce brands, significantly reducing stock inefficiencies. By enabling precise multi-channel product demand predictions, VOIDS helps businesses minimize lost sales and excess inventory, resulting in improved capital efficiency and product availability.
Funding
$20K 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.
Founders
Product
Problem
E-commerce brands often struggle with inaccurate demand forecasting, leading to stock inefficiencies such as lost sales due to stockouts and increased costs from excess inventory. Traditional forecasting methods relying on historical sales data and gut feelings fail to account for volatile demand and external factors like promotions and marketing campaigns. This results in suboptimal capital efficiency and reduced product availability.
Solution
VOIDS provides an operating system that utilizes advanced forecasting algorithms to optimize supply and demand for e-commerce brands, significantly reducing stock inefficiencies. The system forecasts multi-channel product demand and provides actionable insights to prevent lost sales and excess stock. By integrating data across various sales channels and considering factors like seasonality, marketing events, and promotions, VOIDS delivers a comprehensive demand view. This enables brands to make informed decisions about purchasing, replenishment, and inventory management, leading to improved capital efficiency and product availability.
Target Audience
The primary target audience includes e-commerce brands in various segments such as nutrition, fashion, and beauty, particularly those struggling with stock inefficiencies and seeking to optimize their supply chain operations.
Features
- Multi-channel demand forecasting engine that integrates data from various sales channels and countries
- Prediction of sales spikes from recurring events and revenue drops from historic out-of-stocks
- Cross-product learning for improved forecasting accuracy, even with limited data
- Tailored buying recommendations on variant, product, or category levels
- Quantification of financial impact and timing of stockouts or surpluses based on product-specific lead times
- Automated purchase orders by syncing supplier data and tracking deliveries
- Supplier condition application for better financing or delivery allocation
- Delivery date, order quantity, and unit price updates