Our objective is to optimize the omnichannel performance of your E-commerce sales
Dispodyne algorithms analyze channels and buying behavior to drive profitability.
In volatile times managing omnichannel sales we perceive as challenging to avoid stock-outs or overstock as well as optimizing channel performance. Machines can support human expert insights into market and channel behavior. That defines the starting point of Dispodyne predictive analytics.
Dispodyne e-commerce predictive analytics applies advanced augmented intelligence, machine learning and stochastic algorithms to help merchants and DTC producers to run their sales and demand planning processes when operating in the dynamic field of e-commerce in multiple channels and storefronts.
Dispodyne has a toolset that analyzes the demand signal of previous customer buying behavior separated by segment, category, storefront, channel and other criteria. Based on these analytics clients are enabled to run a guided scenario planning to generate sales and demand forecasts that fits the merchants market expectations including campaigns and other measures. We also provide algorithmic to convert unconstrained into constrained demand.
Draw analogies and based on relevant historic data algorithms generate sales forecasts.
Run multiple supply scenario with different purchasing budgets to optimize economic outcomes.
Drive ROI using intelligent algorithmic like optimizing order quantities.
Co-Founder and Head of Product. Enthusiastic to get AI technology and services into enterprises.
Co-Founder and CTO. Has focussed most of his business life on extracting insight from data.