Neon Blue supports personalized creative generation and experimentation using product recommendations, but it is not a product recommendation engine itself.
To generate personalized content such as cross-sell emails, post-purchase upsells, or on-site creative tied to a specific product, Neon Blue must be provided with the recommended product for each user. This recommendation must exist as data that Neon Blue can access at generation time.
Neon Blue focuses on generating, testing, and optimizing creative around a provided recommendation, not deciding which product to recommend.
What Neon Blue Does and Does Not Do
What Neon Blue Does
Uses an existing product recommendation as an input
Generates personalized creative for that product
Runs experiments and optimization across creative variants
Personalizes messaging per user based on context and data
What Neon Blue Does Not Do
Decide which product should be recommended
Replace or replicate a recommendation algorithm
Generate content against recommendations that only render at send-time and are not exposed as data
How Product Recommendations Must Be Provided
For Neon Blue to generate content tied to a recommended product, that product must be available as a variable before send-time.
This variable can come from:
A third-party recommendation system
An internal data model or database field
A predefined single product selected for a given campaign or flow
As long as a user-level or message-level product variable exists, Neon Blue can fetch it, render it, and generate creative against it.
Supported Recommendation Approaches
1. Third-Party or Internal Recommender (Preferred)
If your organization uses a recommender system that outputs a recommended product per user (for example, via your data warehouse, CDP, or custom service), that product can be passed into Neon Blue as a variable.
This is the most common and highest-performing setup in ecommerce personalization.
Example use cases:
Cross-sell recommendations based on purchase history
Post-purchase upsells driven by internal models
On-site personalization using session-based recommendations
Once provided, Neon Blue can:
Generate personalized creative for that product
Experiment across messaging strategies
Optimize performance over time
2. Fixed Product Cross-Sell
If no recommender exists, a campaign can be dedicated to a single product.
In this setup:
One product is selected as the cross-sell or upsell
Neon Blue personalizes the creative, not the product choice
All users receive creative variations for the same product
This approach works well for:
Launches
Strategic product pushes
Low SKU count companies
High-margin or seasonal items
Unsupported Recommendation Approaches
ESP-Native Recommenders (e.g. Klaviyo)
Neon Blue does not work with ESP-native recommendation blocks such as Klaviyo’s built-in product recommender.
Reason:
These recommenders are rendered inside the email template at send-time
The recommended product is not exposed as a usable variable beforehand
Neon Blue cannot access, tag, or generate content against something it cannot see prior to send
Even if:
The product feed is updated
The email is already configured with a recommender block
The recommendation remains inaccessible to Neon Blue.
As a result:
Neon Blue cannot generate creative tied to those recommendations
The ESP recommender can still be used independently without Neon Blue involvement
Refer to your ESP’s documentation for configuring those recommenders.
Frequently Asked Questions
Can Neon Blue tag or reference a Klaviyo recommender product as a variable?
No. ESP-native recommenders are template-level constructs that only resolve at send-time and are not available as data inputs.
Can we make this work if our data team stores recommendations internally?
Yes. If your internal systems store a recommended product in a user or message-level field, that field can be passed to Neon Blue.
Does it matter whether the recommendation comes from a third party or internal system?
No. The only requirement is that the recommended product exists as a variable Neon Blue can access before generation.
What is the minimum requirement for using recommendations with Neon Blue?
A user-level or campaign-level product variable. If that exists, Neon Blue can manage creative generation and experimentation around it.
