Cloud Connect Introduction
Cloud Connect allows you to surface results of SQL-based segmentation from your data warehouse and send audience membership directly to downstream marketing tools or into your Lytics audience builder. For a high-level overview of why Lytics created this new offering, see our blog post Introducing Lytics Cloud Connect.
What use cases does Cloud Connect enable?
Cloud Connect unlocks many use cases enabling marketers to segment their customers based on any attributes stored in their database. A few examples include:
- Time Window: All users who did not log in last month.
- Joins (B2B): All users associated with accounts who have not used X feature.
- Lifetime Value (LTV) or Rollup: All users who have a premium subscription and have purchased at least two products.
Using Cloud Connect, you can write SQL queries to create segments as simple or complex as needed for your marketing use cases.
How do Cloud Connect and Decision Engine work together?
Lytics' flagship platform, the Decision Engine, with real-time activation capabilities is designed to work in tandem with Cloud Connect.
The key difference between a Cloud Connection and standard Integration is that Cloud Connect only pulls in audience membership into Lytics based on your query to your database. No other data will be pulled in directly from your data warehouse. Lytics Cloud Connect is designed to allow marketers to access their existing “source of truth” customer data in their data warehouse without importing and duplicating it to create Lytics audiences that are activated in downstream tools.
As an example, let’s compare setting up a BigQuery Cloud Connection (new capability) and setting up a BigQuery Import Activity Job (existing capability).
When creating an Import Activity Job in Lytics, you are streaming that user and event data from Google BigQuery into Lytics’ real-time pipeline. This allows your BigQuery data to inform Lytics Behavioral Scores, Affinities, Lookalike Models, and more. For data that is meant for real-time activation, this workflow is still an essential part of leveraging Lytics.
However, there is a downside to directly importing data from your warehouse; it essentially duplicates a subset of your customer data, now living in BigQuery and Lytics. Bringing in too much data can cause your Lytics user profiles to become bloated and slow down processes. Additionally, much of your batch data is valuable but doesn’t need to live directly on user profiles, such as purchase history or contextual user information.
When creating a Connection to BigQuery, you are gaining direct access to your database without streaming that data of interest into Lytics. You are essentially querying for an answer about your customers and adding that resulting audience membership information to Lytics user profiles.