By activating data-driven pricing and promotions with Dynamic Pricing powered by Rapid Pricer, a leading Latin American convenience retailer achieved a 7% margin lift in test stores and built a scalable, AI-driven framework for future growth. This approach reflects advanced retail pricing optimization strategies.
Client
A Fast-growing Convenience Leader Ready to Get More from Its Data
A leading convenience-store chain in Latin America, operating over 13,000 stores, wanted to make better use of the massive volume of data generated across its network.
For this multi-year initiative, the retailer focused on:
- 805 stores in priority regions
- 1,500+ SKUs across key convenience categories
- A cross-functional team spanning Analytics, Technology, and Consulting
The goal was clear: move from intuition-led and fragmented pricing decisions to a structured, analytics-driven approach that could scale across stores, categories, and regions.
Challenge
Data-rich, Insight-poor: Pricing and Promotions Misaligned with Strategy
The retailer had no shortage of data. What it lacked was a way to turn that data into decisions that consistently supported margin, revenue, and competitive goals.
Key challenges included:
- Underused data assets
Large volumes of transaction and store-level data weren’t feeding into advanced pricing analytics or - Fragmented and intuition-led pricingPricing, promotions, and markdowns weren’t tightly aligned with broader business objectives. Individual stores and teams often made decisions in isolation.
- Limited optimization of pricing levers
The retailer lacked robust strategies for:- Optimal everyday pricing
- Bundling and cross-promotion
- Category and item role-based pricing
- Impact on performance and competitiveness
- Unrealized revenue and inconsistent profit margins
- Limited ability to pinpoint high-performing SKUs and demand patterns
- Reduced agility in a dynamic, highly competitive market
The retailer wanted to change the game: build a structured, data-driven pricing and promotion optimization framework that could scale to hundreds of stores, thousands of SKUs, and a wide range of local market conditions.
Solution
Dynamic Pricing Powered by Rapid Pricer: An End-to-end Framework from Data to Decisions
To tackle these challenges, the retailer implemented Dynamic Pricing powered by Rapid Pricer, tailoring it to the realities of a large convenience network. The solution focused on building a solid data foundation, robust pricing analytics models, and an execution framework that teams could trust—ultimately driving sustainable retail margin improvement.
Strong data foundation and product intelligence
- Comprehensive data collection and preparation across 805 stores and 1,500+ SKUs
- Clear product attribute definitions to support differentiated strategies by role and category
- Alignment with the retailer’s merchandising structure and promotional calendar
Real-time competitor and market visibility
- Competitive price analysis to identify real-time competitors for each store cluster
- Definition of Key Value Items (KVIs) to protect price perception and traffic
- Continuous competitor and price tracking to stay aligned with market dynamics
Custom analytics models for pricing and promotions
- Tailor-made mathematical models that incorporated:
- Store-level demand behavior
- Seasonality and geography
- Competitive intensity and consumer sensitivity
- Optimization for both everyday pricing and promotion optimization strategies, including bundling and cross-promotions
Strategy aligned to business objectives
- End-to-end framework: data ingestion → analysis → recommendations → implementation → measurable results
- Pricing and promotion strategies designed to support margin, revenue, and traffic goals—not just short-term sales spikes
- Store-level insights that guided localized decisions while maintaining a coherent, enterprise-wide strategy
Deep cross-functional collaboration
- Analytics team: data preparation, validation, and insight generation
- Technology team: integration, scalability, and performance
- Category management team: category roles, assortment, and change management
- Rapid Pricer experts: data engineers, statisticians, pricing analysts, and consultants co-creating the solution with the retailer’s teams
Benefits
Margin Up, Decisions Sharper, And A Pricing Engine That Can Scale
The retailer quickly began to see the impact of a more structured, data-driven pricing and promotions approach.
Immediate benefits
- 7% margin improvement in test stores compared to control stores
- Significantly better pricing outcomes driven by:
- Demand-sensitive models
- Location-specific pricing and promotion optimization strategies
- Clearer understanding of competition and relative market position
- Defined category and item roles that informed assortment, pricing, and promotional priorities
Long-term business impact
- Stronger competitive positioning and improved store-level profitability
- Adoption of a data-driven culture for pricing and promotions, replacing fragmented, store-by-store decision-making
- Increased foot traffic powered by a more relevant product mix and smarter promotional strategies
- A scalable optimization framework that can be extended to more stores, regions, and categories
Measurable outcomes
- 7% margin lift in test stores
- Improved promotional efficiency and more optimal product mix decisions
- A robust blueprint for broadening the deployment across the network
Behind the numbers, this transformation also gave teams a common language and toolkit for pricing—grounded in data, aligned to strategy, and flexible enough to adapt to local realities.
Summary
From Fragmented Decisions to a Unified, Ai-Driven Pricing and Promotions Engine
This engagement shows how a large, complex convenience retailer can turn its data into a true competitive advantage.
With Dynamic Pricing powered by Rapid Pricer, the retailer has:
- Built an end-to-end framework that links data, pricing analytics, and in-store execution
- Aligned pricing and promotions with broader strategic objectives across 805 stores and 1,500+ SKUs
- Enabled local, store-level nuance without losing central governance or strategic direction
- Created a scalable foundation for:
- Expanding optimized models to additional stores and categories
- Incorporating more data sources for faster, more responsive decision-making
- Deploying predictive analytics and real-time dashboards
- Establishing continuous improvement loops for ongoing optimization
For retailers facing similar challenges—lots of data, inconsistent pricing, and pressure on both margin and growth—this journey illustrates what’s possible when AI pricing optimization, retail pricing optimization, promotion optimization and pricing analytics come together in a single, coherent pricing and promotions engine.
Want to turn your pricing and promotions data into a competitive edge?
Discover how Dynamic Pricing powered by Rapid Pricer helps convenience and retail brands lift margins, sharpen price perception, and scale smarter decisions across every store.
