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Changing customer perceptions mandate a shift in retail pricing strategies. Monitoring and adjusting pricing models and merchandising decisions in isolation is no longer enough to boost customer loyalty and drive business results. Retailers must factor in customer perception of price from the experience, brand value, key product characteristics customers look for while making pricing and merchandising decisions.

Happiest Minds PRIcing and MERchandising Cognitive Solution offers an automated and data science-driven approach for price review and retail price management across multiple channels to large retail enterprises. This solution enables retailers to maximize sales, reduce manual effort, drive profits, and build customer trust by leveraging powerful insights. The solution helps our clients to:

  • Idenitfy key price drivers attributes by product category to understand price-attribute co-relations
  • Establish consistent pricing model across similar products and eliminate price discrepancies
  • Maintain uniformity and progression within product variants and withcompetition with automated price relationship model
  • Ensure price integrity across product variants by implementing consistent price changes.
  • Account for vendor cost escalations, demand-supply constraints, changing customer preferences, and liquidation needs of current stock in pricing strategy
  • Automate repetitive tasks to enhance efficiency of internal teams

Built on open source technologies and powered by machine learning, our solution eliminates the need for manual reviews and intelligently applies comprehensive pricing analytics and price management techniques across multiple channels of customer engagement.

Features & Benefits

Features
  • Automated data science driven approach to price maintenance and product line reviews.
  • Generalized algorithmic models that take data inputs to automatically decipher the key attributes or value drivers which influence price variation of items.
  • Output engines that classify the items into price groups based on key attributes and determine price relationships within own assortment
  • Competition benchmarking to identify opportunities for price optimization
  • Automated mechanism to Identify existing price inconsistencies or pricing anomalies.
  • Business UI layer for configuration, price reviews, and validation for pricing users.
  • Available in Managed Services Mode with regular refresh and algorithmic model updates over the period of contract.
Benefits
  • Significant reduction in manual effort
  • Address incorrect price perceptions internally and with compeition
  • Simplify price setup for new product
  • Enhance product data quality
  • Improve product recommendation and related product models

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