Retail

Provide shoppers personalized recommendations and offers.

  • Increase customer engagement and build stronger relationships with customers through personalized shopping experiences on your website.
  • Build personalized marketing and commerce experiences with AI grounded in your data.
  • Deliver content in the right context, through the right channel, at the right time.

Data Sources Used

Demographic & Psychographic
Google Audience Insights
Transactional Data
Customer Feedback
Market Trends & Competition
Weather & Supply Chain
Real Time Marketing Engagement Data
Loyalty Data
Retail Store Expertise

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 Use browsing behavior and past purchases to develop insights related to shopping preferences. Bring together online and offline purchases to build a complete picture of customer lifetime value. Leverage web browsing and email data to build insights related to overall level of interest for certain products.
Predictive Models Help marketers understand their highest value segments — the likelihood of a customer responding to specific promotions when prioritizing and ranking segments. Provide your agents and staff with AI-driven guidance on what the next best action is to engage a customer or create a unique moment during a service engagement.

What’s the impact?

Real Time Inventory Updates
Increase in Customer Lifetime Value
Increase Conversion Rates
Increase in Revenue Channels