Welcome to the Abandoned Browse for Composable CDP solution accelerator for ecommerce businesses. Abandoned browse is a common ecommerce problem where users show interest in products but don't complete a purchase. It is also referred to as "shopping cart abandonment," "abandoned basket," or "abandoned cart." Despite how common it is, it is still a challenge to implement a successful re-engagement campaign when using traditional marketing tools because they lack all the context needed to create a compelling personalized message.

This accelerator demonstrates how to build an effective re-engagement strategy for ecommerce sites leveraging Snowplow event data. Rather than acting on a basket being abandoned, we will use the product that was engaged with the most to lure the customer back to making a purchase. This provides a more personalised experience and demonstrates the benefits of combining Snowplow, Snowflake and Census. It offers a practical guide for developers to set up tracking, model data, sync audiences with Reverse ETL, and build automated campaigns in Braze.

The accelerator is inspired by a typical ecommerce scenario where potential customers view product pages but leave without purchasing. The goal is to create personalized email campaigns to re-engage these users and drive conversions using enriched Snowplow event data.

Use Cases

• Abandoned browse recovery
  Send personalized reminders to users who showed interest in a product but did not purchase.
• Personalized re-engagement campaigns
  Utilize product view time and engagement data to tailor email content.
• Behavioral segmentation
  Segment audiences based on time spent on product pages and past engagement history.
• Campaign performance tracking
  Measure the effectiveness of re-engagement campaigns through Snowplow event data.
• Dynamic audience updates
  Automatically adjust campaign audiences using Reverse ETL workflows with Census.

Infrastructure Overview

The infrastructure for this accelerator includes:

• Snowplow JavaScript Tracker
  Captures events such as product views, engagement time, and add-to-cart actions on an ecommerce site.
• Snowplow
  The Snowplow pipeline processes and enriches events, loading them in real-time into Snowflake for analysis and data modeling.
• Snowflake
  Snowflake stores and enables data to be modeled and queried. You can use an alternative data warehouse of your choice.
• Census Reverse ETL
  Syncs modeled data to Braze, enabling automated, personalized marketing campaigns.
• Braze
  Builds and executes abandoned browse email campaigns, utilizing personalized product data and engagement metrics modeled in the warehouse.

Additional Insights

This framework can be adapted to other ecommerce scenarios, such as, product recommendations, and personalized promotions. The solution can also be extended to incorporate advanced audience segmentation, A/B testing, and integration with additional marketing tools.

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