The bleeding bottom line
As demand patterns and price sensitivity became critical, this ecommerce retailer’s ability to liquidate piled-up stock started impacting the bottom line. The inability to anticipate demand spurts and to price competitively vis-a-vis other retailers further aggravated the situation. The retailer wanted a “just right” solution that they could afford to deploy without significant capital investments but could instantly provide results. That quest was not meant to be easy.
The devil in the details
A deeper analysis of the way data was managed within the enterprise revealed multiple inconsistencies. Data was highly disaggregated across the enterprise with accuracy issues – both at a reporting and analysis level. Unifying the data ecosystem was expected to provide greater clarity with better decision intelligence. The dynamic demands of pricing meant that decision intelligence needed to be directed in real-time. The ability to update price changes and dynamically update pricing in accordance with the changing market conditions could well be the answer.
Price right with AI
Hypersonix deployed an AI-driven pricing solution for the retailer, allowing them to integrate and account for all data sources, competitor pricing, inventory availability and more.
Managers used AI/ML to discover a weekly optimal markdown price that would move any perishable products before they expire, delight their customers with a great price, and maximize profit. In addition, Hypersonix allowed managers to respond to market conditions in real-time, offering personalized assortments that are in line with the core values of their key consumers.
Increase in sales and customer loyalty
Within weeks of implementing Hypersonix, the company witnessed a steep incline in sales by 30%, and steady growth since. The accuracy of data delivered went up to 90%, along with 2x efficiency gains. Hypersonix’s pricing recommendations allowed for 7 to 9% lower prices for the customers, which reduced customer churn by 50%. Intelligent insights and recommendations in real-time also allowed data analysis teams to make better decisions on promotions, which increased footfall in stores across the 9 states by over 120% in 2 months.