Explore Real-Time Features in Data Cloud
Learning Objectives
After completing this unit, you’ll be able to:
- Explain which features in Data Cloud have real-time capabilities.
- Explain how those features support a real-time use case.
In this unit, we look at each feature that powers Data Cloud in real time. Then, walk through a detailed use case of how Northern Trail Outfitters (NTO), a retail company, implements real-time product recommendations.
Real-Time Data Cloud Features
These features work together to ingest, analyze, and respond to real-time customer data. Data model objects (DMOs) are used in each of these features. A DMO is a grouping of data, made up of attributes, created from data streams, insights, and other sources.
Feature | Description | How to Set Up |
|---|---|---|
Real-time data graphs | Access and update customer data, such as customer 360 profiles, in milliseconds with real-time data graphs. Data graphs combine and transform normalized data from DMOs into new views of your data. Because the data is precalculated and stored, you can access and update data in milliseconds. Real-time data graphs refresh continuously and are up to date with changes in the DMOs for all real-time events, while normal data graphs are on a refresh schedule. Real-time data graphs are required to use other real-time capabilities. | Create a real-time data graph with a Profile DMO, such as the unified individual DMO. Learn more about the steps to set up this feature in Create a Data Graph. |
Real-time data ingestion | Ingest user engagements and events from your app or website into Data Cloud in milliseconds. | Create a web or mobile app data stream, or create a data stream using Ingestion API. Map the new data streams to DMOs and then add the DMOs to a real-time data graph. Learn more about the steps to set up this feature in Web and Mobile App Connector and Create an Ingestion API Data Stream. |
Real-time identity resolution and matching | Link users to unified profiles in milliseconds. | Each ruleset creates a unified DMO. Create a real-time data graph with the DMO to set up real-time matching. Learn more about the steps to set up this feature in Configure Real-Time Matching. |
Real-time calculated insights | Calculate metrics such as lifetime value or user visit history in milliseconds. Use these metrics to personalize the customer’s experience through your website, chatbot, and service agents. | Create real-time insights based on interaction data from a real-time data graph. Learn more about the steps to set up this feature in Create a Real-Time Insight Using Builder. |
Real-time segments | Evaluate user engagements based on segment attributes and build audiences in milliseconds. | Create a real-time segment based on a real-time data graph. Learn more about the steps to set up this feature in Create a Real-Time Segment. |
Real-time data actions | Add real-time data actions to a flow and trigger Data Cloud events in milliseconds with Flow Builder. | Create a custom real-time Data Cloud event and use it in a flow. Learn more in Create a Real-Time Data Action in Data Cloud. |
Next, see how these features work together through Northern Trail Outfitter’s use case.
Implement Real-Time Product Recommendations
Meet Northern Trail Outfitters (NTO), a retail company that specializes in outdoor gear and clothing. NTO’s conversions are low because of outdated product recommendations. The company wants to use Data Cloud in real-time to improve its product recommendations and boost conversions. Here’s an overview of the steps NTO takes to implement real-time product recommendations for its commerce site.
- Create a web data stream mapped to the individual DMO and the engagement DMO. This ingests profile and user engagement data from the commerce site into Data Cloud.
- Create and run an identity resolution ruleset. The ruleset creates a unified individual DMO.
- Create a real-time data graph with the unified individual DMO and engagement DMO. Now you can instantly match customer profiles.
- Create a real-time insight to calculate metrics on a user’s browsing and purchase history.
- Feed this information to a personalization tool to generate real-time product recommendations and promotions a user might be interested in.
- Display the recommendations in real time on NTO’s commerce site.
Next, NTO gives personalized product recommendations in real time as a customer browses its website. Here’s what that might look like.
The customer logs in to the website and clicks on a blue jacket. The customer then leaves the product listing without adding the jacket to their cart. With Data Cloud, NTO ingests these user engagement actions immediately. By matching credentials to the unified profile, NTO is able to link the customer to Rachel Rodriguez’s unified profile in real time.
Through insights, NTO discovers that Rachel purchased multiple jackets from NTO and is a gold-tier repeat customer. NTO feeds this information to a personalization tool. The personalization tool generates a promotional offer on jackets based on Rachel’s eligibility, past purchases, and recent actions.
- Eligibility: Rachel’s a gold-tier customer, so she’s eligible to buy some jacket styles at a discount.
- Past purchases: The personalization tool curates which styles it recommends based on Rachel’s past purchases. Rachel historically purchased athletic jackets, so the recommended product type is athletic.
- Recent actions: Finally, the personalization tool considers Rachel’s recent actions. Rachel was looking at blue jackets, so the personalization tool focuses on blue jackets.
After considering all these factors, the personalization tool recommends a blue athletic jacket at a promotional discount.
The site displays the promotion to Rachel: “Special 15% discount on this product plus free shipping. For Gold-Tier customers only!"
All of these steps happen in milliseconds: Rachel sees the promotion as soon as she clicks away from the product listing for the other jacket. Rachel’s thrilled that she has a discount, and she loves the style of the recommendation. She buys the jacket!
Wrapping Up
With real-time Data Cloud, NTO can respond to user actions in real time and give personalized responses, which boosts its user engagement, conversion, and revenue per visit. Real-time Data Cloud brings current customer actions to the forefront of every interaction with every team in your company.