Smartpricing is a pricing management solution for dynamic retail pricing using a machine Learning (ML) data-driven approach, helping to increase gross margins by 5-15% depending on a product category, and up to 6% in average for a retail chain. It covers key pricing tasks with an emphasis on competitive pricing with the ability to optimize revenue and income in general and by product category. Pricing based on three strategies which are maximizing revenue, maximizing gross income and a balanced strategy. Principles of behavioral economics and psychology as flexible rounding and threshold prices, price ladder are built-in. The core ML models are based on ML regression and Bayesian and combining ML techniques and expert knowledge. It has stability of algorithms to statistical errors and inaccuracy of the initial data due to additional preliminary statistical processing and data cleaning. The solution into account the specifics of offline retail business models that calculates, sets parameters and localizes prices at the level of the formats / regions / clusters /stores/ SKUs.
Smartpricing might be used to
- “squeeze” the maximum income from all possible positions and retain sales results;
- differentiate from competitors where buyers expect it
- scale and automatically support multiple pricing formats/regions/clusters and models
- promote as efficiently as possible, and automate the search for the best products, discounts, and promotion time frames
- create different KVI baskets and automatically select the most efficient set of indicator goods
- improve the process consistency, automate all routine and standard tasks in order to focus on strategic objective