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Consumer Goods

Improve revenue strategy with data-driven planning

  • Unlock trapped, syndicated data to identify which products are sold when, where, and at what velocity, along with real-time consumer engagement.
  • Leverage ML models and automation to predict assortment mix opportunities based on previous orders, current inventory, and market trends.
  • Reduce manual deck-building and analysis with democratized insights.

Data Sources Used

Marketing 1st Party Data
Ecommerce
Store Sales (IRI, Nielsen)
TPM, ReX data
POS or Scan Data from Retailers
Inventory Data
ERP
Demographic Data
Loyalty Data

Apply Insights and Predictions

By bringing together the data sources referenced in this use case, teams can build calculated insights or run predictive models with Data Cloud that will allow them to make smarter decisions or power new automations.

Calculated Insights Bring together customer information, sales, and inventory data to create insights related to customer lifetime value or product affinity scores.
Predictive Models Leverage machine learning models to predict the right inventory assortment or assess a customer's propensity to buy certain products.

What's the impact

Sales Revenue
Trade Promotion Effectiveness
Store Visit Revenue
Marketing ROI
Sales Productivity
Service Agent Productivity
IT Total Cost of Ownership

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