Price Optimization


Perform what-if analysis and create data visualizations essential to forecast prices

Price of a commodity or service is one of the most crucial factors that budget-constrained customers consider for making buying decisions. With online options aplenty, consumers weigh all options for optimum profitability and maximum returns before reaching a decision. Hence, price optimization is imperative for retail giants to remain relevant and maintain growth in a fiercely competitive market. They combine demand modeling and ‘what-if’ analysis to strike the right balance between safeguarding the customer wallet and ensuring a fool proof pricing strategy. They also observe and study the impact of pricing strategy on sales and the retailer performance.
The Problem Canvas
  • Can profitability be increased by price rise?
  • Is there an impact of inventory dynamics and competitive pricing on pricing of commodities?
  • Set and manage price strategy to maximize profitability
The Data Question
  • Have the right price, both for the customer and the resellers, to gain a competitive advantage with the help of several optimization mechanisms considering factors like production costs, customer spend and offers by competitors

Solution Canvas


Rubiscape uses a proprietary approach for applying various methodologies and datasets, estimating parameters and building the best-fit models for attaining a price-value coherence. The models emerge with a robust strategy to forecast prices that are perceived by customers as value-for-money.

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RubiStudio – Data Joiner, Data Exploration
RubiSight – Data Visualizations

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Data wrangling
Data visualisations
Machine Learning
Domain Knowledge

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Total sales and average weekly spending estimates for each retail sector in Great Britain (in thousand GBP).

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Business Impact
  • Efficiently Generate Scientific Pricing Forecasts with Automation
  • Reduce manual errors and improved operational efficiency
  • Increased profitability with better accuracy
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