Retail/Marketing · metric Paid

Promo-Elasticity Gap

Identify underperforming promotional investments to reallocate trade spend toward high-elasticity categories for maximum revenue lift.

Refresh: daily
History: single vintage
Plan: Paid

Stable

📈 Live history is activating for this object — the automated backfill is in progress.

⌁ mcp.call("adw-016") v1.0

Forward outlook

Prediction

Horizon: —
Recommended use: Identify underperforming promotional investments to reallocate trade spend toward high-elasticity categories for maximum revenue lift.

Methodology

How it's built

Calculate price elasticity of demand using historical sales volume and discount depth data, then compute the gap between actual promo ROI and the theoretical maximum ROI to generate a prioritization s

Internal POS transaction logspromotional calendar dataand competitor pricing feeds from public web scraping or free market reports.

Version 1.0 · validated to beat a naive baseline · benchmark: NielsenIQ-adjacent

Live response

The object an agent receives

One call returns the answer with its reasoning attached — the live Intelligence Object for ADW-016.

GET /v1/intelligence/adw-016

{}

IOM schema

The agent-callable contract

Every product conforms to the Intelligence Object Model — typed, versioned, and discoverable.

product_id
entity
score
trend
confidence
top_drivers
prediction_horizon
recommended_use
methodology_version
freshness
coverage
source_lineage
allowed_use

MCP tool: adw.adw_016

Access options

Consume it your way

Dashboard
Read the score + drivers in the console.
REST API
/v1/intelligence/adw-016
MCP tool
adw.adw_016
Marketplace
Discoverable by any MCP agent via the MCP registry.
White-label
Embed under your own brand (Platinum).

Plan requirement

Depth scales with the plan

Free Sample object — current score only
Gold Full drivers + history + confidence
Platinum White-label + bulk + SLA

Compare plans →

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