Dia Patel P. Email & Phone Number

New York, Ny, Us

New York City Metropolitan Area

Building the most powerful RETAIL PRICING ENGINE that can save hours and hours of work, and help the category teams make right scientific pricing decisions in a jiffy.Using BRIO (Automated engine) retailers and brands can:1. Forecast Demand, 2. Predict Prices, 3. Track Competitor Pricing and Assortment4. Analyze store-level performance in real timeI can get your pricing engine implemented in less than a week!

New York City Metropolitan Area

> Spearheaded the launch inventory strategy for a large private label brand, encompassing lunch meat and snacking categories. > Established a data-driven framework and communication protocols for future food and beverage private label launches within the Meat and Seafood Division, serving as the Owned-Brand Captain.> Leveraged point-of-sale (POS) analysis to identify consumer trends and recommend strategic assortment adjustments in the snacking categories.> Led the “back-to-school” season inventory management strategy, achieving a +0.1% share gain and a +4.2% unit sales increase at Target compared to the rest of the market (ROM), while reducing markdowns by $1 million. > Facilitated cross-functional collaboration between product development, merchandising, pricing & promotions, marketing (both internal and at Target), and vendors to optimize inventory management for two categories, generating $207 million in annual sales. > Implemented innovative promotional forecasting methods as a Promotional Captain, leading to improved compliance and accuracy standards across processed meat categories.

> Leveraged SQL, R, and Excel to extract actionable insights from raw customer, digital, and email data. > Established a unified data pipeline for seamless integration of diverse data sources, enabling comprehensive business performance analysis and data-driven decision-making.> Developed interactive dashboards that showcased complex customer trends with clarity, empowering senior leadership to make strategic decisions with a data-centric foundation.> Optimized the effectiveness of digital campaigns during critical periods by implementing data-driven strategies based on insights from the email and sms marketing methods> Constructed Python-based forecasting models to improve the accuracy of traffic and sales predictions, resulting in optimized resource allocation strategies.

New York, New York, United States