1. Role Purpose
The Pricing Intelligence Lead is responsible for transforming data into clear pricing decisions that
improve margin, price perception, and commercial effectiveness.
This role bridges data and business, ensuring pricing is not only analyzed but also executed with
impact across categories, promotions, and supplier strategies.
The goal is to move from reactive price checks to structured, insight-driven pricing decisions.

2. Key Responsibilities
Pricing Intelligence
• Build and manage the pricing intelligence framework:
o Price index vs competitors
o Margin pool by category and SKU
o Traffic drivers vs profit generators
• Translate data into clear actions:
o Where to invest price
o Where to optimize margin
o Where to adjust assortment
Pricing Analytics & Simulation
• Develop practical models to support decisions:
o Price elasticity (business-focused)
o Impact of price changes on volume and margin
o Promotion ROI and cannibalization
• Provide scenario analysis and evaluate pricing actions
Commercial Integration
• Work closely with Category, Marketing, and Supply teams
• Convert insights into:
o Promotion plans
o Pricing strategies
o Supplier negotiation inputs
• Ensure pricing recommendations are adopted and executed
Competitive Intelligence
• Monitor competitor pricing and positioning
• Identify:
o Price gaps
o Traffic-driving SKUs
o Margin risks
• Translate insights into actionable recommendations
Governance & Execution
• Support pricing rules and guardrails by category
• Ensure consistency across stores and channels
• Track execution vs strategy
Data & BI
• Work with Data and BI teams to ensure reliable data structure
• Develop dashboards focused on decision-making, not reporting
• Improve automation and reduce manual reporting

3. Key Deliverables
• Pricing dashboard (action-oriented)
• Monthly pricing opportunity map
• Pricing simulation tools
• Promotion ROI analysis
• Category pricing recommendations

4. Success Metrics
• Gross margin improvement
• Promotion ROI uplift
• Accuracy of pricing decisions
• Adoption by commercial teams
• Speed of decision-making

Job requirements
• 3–6 years in analytics, business development, or commercial roles
• Strong experience in performance analysis and reporting
• Retail or FMCG experience preferred

Skills
• Strong analytical thinking
• Ability to convert data into business actions
• Good commercial understanding
• Strong communication and stakeholder management

Technical
• Power BI, Excel
• Machine Learning & AI
• Data automation and integration
• Familiar with SAP, market data, traffic data and other retail operational data