With retail assortments growing, turnover increasing and shop floor space shrinking, retailers need new ways to generate profits. Retailer pricing has been driven from the corporate level by established pricing guidelines and competition. Reductions for many retailers are based on tried and tested techniques with x% at 6 weeks, y% at 8 weeks, etc. These traditional methods are insufficient to compete with new online or omnichannel competitors who are better positioned to increase profits through careful price management.
AI is ideal for situations where a retailer needs to optimise a large catalogue of items based on a variety of factors. AI models can be used to determine the best price for each item, using data on seasonality and price elasticity, along with real-time Inputs on stock levels, products and competitive pricing. The result is more careful reductions in grades (colour and size) at a very specific price to increase demand and maximise profits. Profit margin increases are also possible on some items, according to trending demand. AI can also be used for price recommendations indicating key factors. This is useful for retailers who want to know why specific items are being suggested for reductions.
Semantix's mission is the democratization of data, so more people across industries can use the power of AI to solve business and social challenges. The Semantix Data Platform is an all-in-one platform for Big Data that empowers data science teams to scale Machine Learning efforts, increasing speed to develop highly accurate predictive models. SDP has innovative features for retail brands, including machine learning interpretability (MLI), reason codes for individual predictions and automated time series modelling.