What should we recommend or bundle?
Measure product affinity and basket relationships to prioritise cross-sell, recommendation and bundle tests.
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GN eCommerce Decision Pack · eCommerce Decision Intelligence
Package customer and transaction data into the next commercial move.
Use orders, customer behaviour and product data to decide what to recommend, who to retain, which audiences to target and where demand or basket value can move.
Decisions this pack supports
Turn digital behaviour into commercial choices.
Who is worth retaining or targeting?
Use lifetime value, churn, repeat-purchase and propensity signals to focus commercial effort.
What will sell, and where should we plan for it?
Forecast orders, revenue, categories or products at the level where inventory and marketing decisions are made.
Models inside this pack
One product bundle around a recurring business decision.
GN eCommerce combines the models, business logic and constraints needed to move from your operating data to a decision-ready recommendation.
DECISION PACKGN eCommerce
Built aroundOrders · customers · products · campaigns · inventory
Basket / Affinity ModelFinds product relationships, bundle candidates and cross-sell patterns from order-level behaviour.
Customer Value + PropensityEstimates CLV, repeat-purchase likelihood, churn and response propensity.
Demand ForecastingForecasts orders, revenue, categories or products at the planning level that matters.
Assortment / Merchandising ModelCombines demand, affinity, margin and stock constraints to compare catalogue choices.
Next-Best-Action OptimisationRanks candidate products, offers or audiences under margin, stock and contact constraints.
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.
- Audience
- product
- offer
- inventory move
- Expected impact and supporting evidence
- Configured around your real operating constraints
Basket / Affinity Model
Finds product relationships, bundle candidates and cross-sell patterns from order-level behaviour.
Which product pair, bundle or recommendation should be tested.
Customer Value + Propensity
Estimates CLV, repeat-purchase likelihood, churn and response propensity.
Who to retain, target or suppress from costly outreach.
Demand Forecasting
Forecasts orders, revenue, categories or products at the planning level that matters.
Where inventory, budget and campaign capacity should be placed.
Assortment / Merchandising Model
Combines demand, affinity, margin and stock constraints to compare catalogue choices.
Which products deserve visibility, range space or bundle support.
Next-Best-Action Optimisation
Ranks candidate products, offers or audiences under margin, stock and contact constraints.
Which commercial action should happen next for each audience or product.
Pack anatomy
One repeatable path from commerce data to action.
Prebuilt decision patterns, configured around your catalogue, customers and economics.
Your commerce data
Orders, customers, products, baskets, campaigns, channels, inventory and relevant behavioural signals.
Predictive and affinity models
Propensity, CLV, churn, segmentation, basket analysis, forecasting and other models selected for the decision.
Commercial constraints
Margin, stock, audience limits, suppression rules, campaign capacity and other conditions that make an action usable.
A recommendation ready to activate
Return the audience, product pair, offer, forecast or prioritised action into the existing commerce or CRM workflow.
Prebuilt + configured
The decision pattern repeats. Your catalogue and customers do not.
Graphite Note reuses proven modelling and decision workflows while configuring the objective, data mapping, product economics, intervention set and business rules around your operation.
Example decision
Which product pair should we test next?
Use basket-level transaction data to rank candidate combinations, then measure whether the recommended bundle increases attach rate, average order value or conversion.
Direct answers
Questions about the GN eCommerce Decision Pack.
What is the GN eCommerce Decision Pack?
It is a packaged Decision Intelligence solution for recurring commerce decisions across product affinity, customer value, targeting, retention and demand.
What data does it use?
Typical inputs include orders, customers, products, basket contents, campaigns, channels and inventory. The exact input set depends on the decision.
Does it replace our eCommerce platform or CRM?
No. Graphite Note acts as a decision layer. Its outputs can be activated through the commerce, CRM, warehouse and marketing systems already in place.
What comes out?
Examples include ranked customer audiences, product affinities, retention priorities, forecasts and recommended next actions with supporting evidence.
Decision IntelligenceFrom signal and prediction to a governed business action.AutoMLAutomate repetitive model-building work without losing business context.Causal Machine LearningSeparate drivers from correlations and estimate intervention effects.Predictive AnalyticsForecast demand, score customers and anticipate business outcomes.Decision OptimisationCompare feasible actions and rank them by expected business impact.Forecasting vs OptimisationSee where prediction ends and the business decision begins.Decision APIDeliver recommendations, expected impact and evidence into workflows.Embedded Decision IntelligenceAdd a decision layer to ERP, CRM, BI, workflow and vertical software.Build vs BuyA practical framework for deciding whether to build, buy or embed.
Bring one recurring eCommerce decision.
We will scope the data, models and action around the commercial outcome you want to move.