Pricing Analytics: 8 Wk Implementation

Revenue Management (RGM) is the application of disciplined analytics that predict consumer behavior at the micro market levels and optimize product availability and price to maximize revenue growth.

Obtaining the right product pricing for adequate revenue on every product, is an important pillar of RGM. Challenges faced by organizations due to poor pricing analytics:

1. Inability to optimize pricing and facing market positioning challenges
2. Reduced profit margins due to missed opportunities for price adjustments
3. Suboptimal promotion strategy formulations
4. Inability to tailor pricing by channel or region

Sigmoid has developed a suite of solutions for driving sales through price elasticity backed recommendations. How does Sigmoid's solution help:

1. Identifies the optimal pricing model for the product portfolio
2. Distinguishes brand from its competitors
3. Evaluates brand positioning in market
4. Minimizes product cannibalization by using a data-driven approach to rationalize product offerings

Key solutions offered in the suite of Pricing Analytics by Sigmoid:

1. Price Pack Architecture
2. Intelligent Price Recommendation a. Price Optimization b. Recommendation using Price Elasticity c. Price Simulations

The following Azure workloads have been used in developing the above mentioned solution:

1. Azure Data Factory (ADF) for orchestrating data integration pipelines to integrate data from diverse sources
2. Azure Data Lake Storage, serving as the underlying storage layer
3. Microsoft Purview for a Unified Data Governance
4. Azure Machine Learning
5. Integrating and analysing large data sets
6. Power BI for Business Intelligence