Consumer packaged goods AI development
AI for CPG planning and execution
Plan a scoped software pilot for demand forecasting, trade promotion analysis, product content or distribution workflows. Start with the decision your team needs to make and the evidence required to accept the result.
TensorBlue develops AI applications and integrations. A CPG proposal should define the data assessment, evaluation method, system interfaces and ownership of ongoing operations.
Discuss a CPG AI pilotChoose the workflow and its evaluation
Demand planning across products and channels
Separate sell-in shipments to distributors from consumer sell-through. Join order history, available inventory, promotions, lead times and distribution coverage using consistent product and location identifiers. Account for pack-size changes, launches, discontinued products and stockouts; shipment timing can reflect channel inventory rather than consumer demand.
Pilot evaluation
Compare forecasts with a seasonal or existing planning baseline using historical cutoffs. Evaluate by SKU, channel and planning horizon, including bias and intermittent demand. Test the resulting replenishment decisions under lead-time, capacity and shelf-life constraints. Better forecast error alone does not establish less waste or more revenue.
Trade promotion evaluation
Create a promotion calendar with spend, discounts, retailer coverage, execution records and sales outcomes. Define the business question before selecting a model: forecast promotional demand, compare scenarios, or estimate incremental contribution. Record concurrent changes such as distribution gains and competitor activity.
Pilot evaluation
Use an appropriate comparison where feasible and document attribution assumptions. Include discount funding, trade spend, cannibalization and post-promotion demand changes. Report uncertainty. A model that predicts promotional sales does not automatically identify the sales caused by a promotion.
Product content and campaign workflows
Scope a reviewed workflow for product copy, catalog enrichment or creative variants. Use approved product facts and brand guidelines, record input permissions and let reviewers inspect the source of factual statements. Define the handoff into the existing product-information or campaign system.
Pilot evaluation
Measure factual errors, reviewer editing time and accepted outputs on representative products. Campaign evaluation should use controlled comparisons where feasible and include media and production costs. Generating more assets or improving click-through rate does not by itself establish profitable growth.
Distribution and field execution
Combine distributor, store-visit and inventory records to identify coverage gaps or tasks for review. If images are involved, collect representative examples across lighting, packaging and shelf conditions. Show missing or stale data so a field team can distinguish a model alert from a data problem.
Pilot evaluation
Track verified issues, false tasks and action completion. Assess results by channel and territory, and record whether the suggested action was actually performed. Start with an advisory queue and agreed review rules before automating operational updates.
Prepare data and integration requirements
Map product, pack, retailer and distributor identifiers across ERP, planning and product-information systems. Document units, timestamps, returns, delayed postings and permitted uses. Audit a representative sample before choosing the modeling approach. Features used during training must also be available when the live prediction is made.
Define approved exports or APIs, refresh intervals, access permissions and failure handling. Begin with read-only inputs and recommendations visible to a planner or reviewer. Order, price or catalog writes need agreed approval limits, audit records, duplicate prevention and rollback behavior.
A staged pilot and full-cost assessment
- Choose a product category, channel or document collection. Deliver a data-quality review, baseline and acceptance plan.
- Evaluate candidates on separate historical periods or representative reviewed examples. Document errors and limitations before integration.
- Run an observation or controlled workflow trial. Record user decisions, system failures and business outcomes.
- Release the accepted scope with monitoring, escalation and update ownership. Expand only when the evidence supports it.
Include data preparation, integration, infrastructure, reviewer time and maintenance in the economic assessment. Adjust for seasonality and distribution changes when interpreting results. Cost and delivery timing depend on data readiness and interfaces; request a proposal that separates discovery, evaluation, rollout and recurring costs.
