Lesson
Case Study: Calorie Rocket Data Mapping
Explore how Calorie Rocket, a fictitious food delivery app, developed a campaign strategy, identified the necessary data for execution, and mapped their data architecture for the campaign.
Background
Calorie Rocket is currently facing challenges with increased customer churn, leading to revenue loss. Their primary business objective is to reduce churn and boost revenue by increasing purchases from lapsed users. For their top-priority campaign, Calorie Rocket will launch a lapsed user initiative, targeting inactive users with push notifications featuring personalized offers.
Campaign Plan
Calorie Rocket has completed a campaign planning session and has identified the data required to execute this campaign in the following table.
Campaign Name | Lapsed User Promotion |
|---|---|
Desired Use Case | Send a personalized offer to encourage lapsed users to make a purchase on our app. |
Business Priority | P1 |
Channel | Push |
Action Based, Scheduled, API Triggered | Scheduled |
Segment / Target Audience | Users who have not made a purchase in the past 30 days and are subscribed to push notifications. |
Personalization | first_name, favorite_restaurant |
Conversion Event | purchase_completed |
Custom Event Name | purchase_completed |
Custom Event Properties | name_of_restaurant |
Custom Attribute Name | first_name |
Notes | The most popular restaurant is defined as the restaurant from which the user has made the highest number of purchases, rather than the total amount spent. |
Learn more about Calorie Rocket’s campaign planning process in the Campaign Planning course on Braze Learning.
Watch
In the following below, learn how Calorie Rocket mapped their data architecture for their "Lapsed User Promotion” campaign.