Promotions module
Causal baseline → incrementality → elasticity → optimization, chained into six views that end in a concrete action per customer.
Separate real uplift from what would have sold anyway, attribute halo and cannibalization, measure price and volume elasticity, and get an optimizer that recommends the right depth and mechanic per brand and sub-channel — not the deepest discount.
What's inside
Each page sits one click from the others. The filters you set — date range, channel, sub-channel, region, brand, mechanic — carry across the module so you're always slicing the same base.
Portfolio KPIs across volume and financials — baseline vs incremental volume, promo spend, incremental revenue and ROI — with a volume-decomposition chart, top brands by uplift, an uplift distribution, and your best optimization opportunities up top.
A five-tab deep dive — Summary, Uplift Analysis, Financials & ROI, Halo & Cannibalization, and Validation — that separates true incremental volume from the baseline that would have sold anyway, and shows the halo and cannibalization each promo creates.
Price and volume elasticity by brand with strength and calibration distributions, built from a dual-level model (SKU signal reconciled with brand × sub-channel), gated by an R² floor so only trustworthy fits ever feed optimization.
Scenario simulation across six discount depths with a profit-and-ROI objective, producing an action list, alternative scenarios, and a portfolio-health read — recommending the shallowest profitable depth, never a reflexive deeper cut.
Mechanic rankings (which promo type performs), consumer-mechanic breakdowns, best promo weeks, and a brand × sub-channel heatmap — so the calendar is built on what works, not on what was done last year.
Non-promo vs promo KPIs per customer with a clear action tag — Stop, Increase, Decrease or Maintain — turning the whole analysis into a single next step per account the field team can act on.
What you'll surface
The Promotions module is built around the conversations distributors and CPG manufacturers actually have — not generic BI. Each view is opinionated about the next question, and the filters carry you straight to it.
What we need from you
Map your existing spreadsheets to our canonical schema through the ingestion wizard — column names don't need to match ours. Required sources power baseline, incrementality and elasticity immediately; the cost file turns on profit-based ROI and the optimizer's profit objective.
| Source | Description | Required |
|---|---|---|
| sales | Sales transactions | Required |
| promo_calendar | Promotional calendar | Required |
| customer_master | Customer master | Required |
| product_master | Product master | Required |
| cogs | COGS — factory price | Optional |
Full schema details on the Data Schema page once you sign in.
Request a demo and we'll walk you through the modules with sample data shaped like yours.
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