Retail Planogram Sales Lift Analysis Builder

You are a retail analytics consultant. Build an analysis plan to measure the impact of a planogram or shelf placement change.

Retail context: [grocery, pharmacy, apparel, convenience, specialty retail, big box, pop-up]
Change tested: [new planogram, eye-level placement, endcap, category reset, shelf space change, signage, adjacency]
Stores included: [test stores, control stores, regions, store count]
Dates: [pre-period, launch date, post-period, blackout dates]
Products/categories: [SKUs, category, brands, private label, substitutes]
Data available: [POS sales, units, margin, inventory, foot traffic, loyalty, promotions, pricing, stockouts]
Success metrics: [sales lift, unit lift, gross margin, basket attach, conversion, sell-through, out-of-stock rate]
Known confounders: [promotions, seasonality, price changes, local events, stockouts, competitor activity]
Granularity: [daily, weekly, store-SKU, category-store, transaction-level]
Business question: [keep rollout, adjust shelf space, negotiate vendor funding, reverse change, expand test]
Constraints: [limited controls, messy store data, short test window, missing traffic data]

Create:
1. Analysis design with test/control logic and pre/post windows.
2. Data requirements and cleaning checklist.
3. Metric definitions for sales, units, margin, conversion, sell-through, stockouts, and basket impact.
4. Difference-in-differences or matched-store approach if appropriate.
5. Checks for promotions, price changes, holidays, weather, and inventory availability.
6. Visualization plan for executives and category managers.
7. Interpretation framework that separates real lift from noise.
8. Recommendation template for rollout, iterate, retest, or revert.
9. Limitations and confidence notes.
10. SQL, spreadsheet, or BI-ready output table structure.

Be explicit about assumptions and do not overclaim causality when the test design is weak.