Countering Weather Uncertainties in Beverage Demand Prediction with Machine Learning
AlletecEmerge specializes in helping diverse businesses with demand prediction using Artificial Intelligence and Machine Learning techniques. The solution can be used by Food and Beverage companies to build far more accurate demand prediction models, which help them better manage the weather challenge impacting their demand.
Predicting Footwear Demand Three Seasons in Advance using Machine Learning
Footwear demand forecasting is a very complex problem because demand must be predicted at Store-SKU-Size level . Our solution helps Footwear and Apparel companies by building far more accurate demand prediction models, which help them counter the influence of multitude of external factors such as fashion, events and weather conditions.
Converting Free to Paid Subscribers for an Online Marketplace using Unsupervised Learning
Ecommerce companies depend heavily on paid supplier listings. Listed suppliers on the portal pay a fee to show up on the top of search results. The percentage of paying suppliers is usually only a fraction of the non-paying suppliers, and the eCommerce companies want to increase this percentage. Our solution helps these companies profile their suppliers using Machine Learning techniques, and enable them to focus the ‘most likely to convert’ suppliers, thus hugely conserving the sales and marketing investments.
Predicting Agro-Commodity Purchase Prices with Machine Learning
Efficiency in procurement is a critical success factor for a spices company to be profitable. Level of price fluctuation can vary from 10% within a day to even as high as 100% across the year. Artificial Intelligence and Machine Learning driven models can help these companies make good price predictions, thus helping optimize the procurement stages, geographies and quantities.
Identifying Consumer Financing Fraud using Machine Learning techniques
Consumer Electronics companies attract customers with No-Cost EMI Promotional offers. Dealers and buyers often exploit such schemes to get undue advantage by selling them in open market in cash. Our solution helps these enterprises by detecting fraudulent behaviors in their sales patterns using Machine Learning.
Predicting Patient no-show at Hospital OPD
A US-based hospital experienced nearly 9000 patient no-shows over a 4 year period. This was in addition to appointment cancellations. Machine Learning techniques were used to predict a patient no-show, right at the time of appointment booking, with about 80% accuracy.
