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GN Retail Decision Pack · Retail Decision Intelligence

Retail decisions, packaged around the actions teams make every week.

Use first-party transaction, customer, product and store data to decide where demand is moving, which customers matter most, and where stock, targeting or store-level action should change.

Decisions this pack supports

Start with the choice, not the model.

Demand

Where will demand move?

Forecast at store, category, product or regional level so stock, staffing and planning decisions happen where the business operates. See what happens after the forecast.

Customer value

Which customers are worth prioritising?

Use CLV, churn or repeat-purchase signals to focus retention and acquisition effort where expected value is highest.

Assortment

Which SKUs should each store or channel carry?

Balance local demand, substitution, cannibalisation, margin and operating constraints instead of ranking products on sales alone. See assortment optimisation.

Commercial action

Who or what should receive the next action?

Combine propensity, value and operational constraints to prioritise targeting, offers, inventory or store interventions.

Models inside this pack

One product bundle around a recurring business decision.

GN Retail combines the models, business logic and constraints needed to move from your operating data to a decision-ready recommendation.

DECISION PACKGN Retail

Built aroundTransactions · customers · products · stores

Demand ForecastingForecasts demand at store, category, product or regional level with uncertainty where useful.
Customer Value + PropensityEstimates customer value, repeat-purchase likelihood, churn or response propensity.
Assortment OptimisationCombines local demand, product value, substitution, cannibalisation and operating constraints.
Promotion + Price EffectSeparates observed lift from credible incremental effect and models response to commercial interventions.
Decision OptimisationCombines predictions, expected effects and real constraints into a feasible ranked action.
OUTPUTDecision support your team can use

Models are combined only where the decision needs them. The pack returns a business-ready action with supporting evidence and expected impact.

  • Stock
  • assortment
  • targeting
  • store action
  • Expected impact and supporting evidence
  • Configured around your real operating constraints

Demand Forecasting

Forecasts demand at store, category, product or regional level with uncertainty where useful.

What to stock, where to allocate it and when plans should change.

Customer Value + Propensity

Estimates customer value, repeat-purchase likelihood, churn or response propensity.

Which customers deserve retention, acquisition or campaign priority.

Assortment Optimisation

Combines local demand, product value, substitution, cannibalisation and operating constraints.

Which SKUs each store, channel or customer set should carry.

Promotion + Price Effect

Separates observed lift from credible incremental effect and models response to commercial interventions.

Which promotion or pricing action is worth repeating, changing or stopping.

Decision Optimisation

Combines predictions, expected effects and real constraints into a feasible ranked action.

What stock, targeting, assortment or store-level move should happen next.

Pack anatomy

One repeatable path from retail data to action.

Prebuilt where the decision pattern repeats. Configured where your business is different.

01 / DATA

Your operating data

Transactions, customer history, products, stores, campaigns, inventory, pricing and relevant external drivers.

02 / MODELS

Predictive, causal and optimisation models

Use the modelling layer needed for the question rather than forcing every use case through the same algorithm.

03 / DECISION LOGIC

Your objectives and constraints

Encode the business objective, available interventions, budgets, capacity or policy rules that make the recommendation feasible.

04 / ACTION

A ranked next move

Return a forecast, prioritised audience, store action, intervention or recommended allocation with evidence and expected impact.

Prebuilt + configured

Reusable decision IP without pretending every retailer is identical.

Graphite Note reuses decision workflows, modelling patterns, evaluation methods and output structures. We configure the objective, constraints, data mapping and intervention set around how your retail business actually works.

REUSABLE

Decision workflow

Model patterns, evaluation, governance and output structure.

CONFIGURED

Business logic

Objectives, interventions, constraints, thresholds and data mapping.

YOUR ADVANTAGE

First-party context

Your customers, products, stores, economics and operating knowledge.

Direct answers

Questions about the GN Retail Decision Pack.

What is the GN Retail Decision Pack?

It is a packaged Decision Intelligence solution for recurring retail decisions across demand, customer value, targeting and store-level planning. It combines reusable decision workflows with the retailer's own first-party data, objectives and constraints.

What data can the pack use?

Typical inputs include transactions, customer history, products, stores, campaigns, inventory, pricing and relevant external drivers. The exact dataset depends on the decision being made.

What models sit underneath?

Depending on the problem, Graphite Note can use predictive machine learning, AutoML, causal methods and optimisation. The pack is organised around the decision, not around a single model type.

What comes out of the pack?

The target output is a business-ready decision such as a forecast, prioritised customer or store list, recommended intervention or allocation, together with the evidence and expected impact needed to act.

Bring one recurring retail decision.

We will scope the data, models, constraints and action around the outcome you need to move.