Getting Started with Bluecore Margin Optimization

Learn more about Bluecore's Margin Optimization Recommendations to improve profit margin across Bluecore programs.

Updated over a week ago

Bluecore Margin Optimization is a suite of analytics and product recommendation features that provides actionable insights to improve email program profit margin and align business and merchandising goals, without sacrificing performance or personalization.


  • With the Margin Optimization Dashboard, you have greater visibility into your overall email program and individual campaigns to better understand your margins.

  • With Margin Optimized Recommendations, you can update any existing campaign and product recommendations strategy to automatically optimize to display higher margin products without sacrificing email performance.


Get started with these steps via the below documentation:

Activate Margin Optimization on low performing campaigns by editing the campaign’s existing product recommendation block (next best purchase, best sellers, etc.) to prioritize highest margin products.


The first step is to import relative or actual margin data for your products to the Bluecore product catalog. Please review this article for exact data requirements and steps to import this data. After the data is imported, please be sure to validate your data using the import summary screen and check products within the product catalog to ensure it’s being passed to Bluecore correctly.

Once data has been imported into Bluecore, please contact your CSM to enable the Margin Optimization features for your account.


Once margin data has been uploaded to Bluecore, and the feature has been enabled by your CSM, the Margin Optimization Dashboard will begin updating on a daily basis to provide insight into overall and campaign-level performance of your Bluecore email campaigns.

Use these insights to track overall and campaign-level trends over time and make decisions around which campaigns may benefit from using Margin Optimized Recommendations.

Below is a summary of each of the key sections of the dashboard.


What is the overall average margin of sales attributed to my Bluecore campaigns? How does this performance compare to last month?

This section of the dashboard will provide insight into the month to date (MTD) average margin performance of your Bluecore campaigns and an indication of how much that is over or underperforming as compared to the previous month.


What campaigns should I focus on improving margin from? How much improvement should I expect?

This section of the dashboard is highlighting campaigns that are underperforming against your overall average during the prior 30 days. These are the campaigns with the most room for improvement in terms of margin performance gains and good candidates for Margin Optimized Recommendations.


What is the long term trend of margin performance for my Bluecore campaigns? Should I expect any seasonality in margin performance?

This section of the dashboard shows the overall average and median margin performance by month of Bluecore campaigns over the last 12 months.


What is the average margin of sales attributed to each of my Bluecore campaigns? How does this performance compare to previous months?

This section of the dashboard provides insight to margin performance at a campaign-level including month-over-month change and associated email metrics for each month such as total delivered, unique open rate, and unique click rate.

As you begin to implement Margin Optimized Recommendations in your campaigns, this data will provide insight into the impact this strategy is having on your campaign-level margin performance over time.


Margin Optimized Recommendations can be used with any of your Bluecore campaigns and is applied as part of your personalized product recommendation rules assigned within the campaign workflow.

As shown below, to apply margin optimization to your product recommendation strategy, simply select Highest Margin from the Sorted by drop-down. Once selected, this will sort the personalized recommendations generated for each customer in descending order based on the margin value of each recommended product. This approach ensures that each customer is still getting a highly personalized set of product recommendations while at the same time optimizing for the business goal of improving margins by prioritizing the highest margin products from within that set of products.

Margin Optimization can be used with the following product recommendation strategies:


Q: What data do I need to provide in order to use Bluecore Margin Optimization features?

  • A: To begin using these features, you will need to provide product-level margin data as a numerical value that can be mapped to your existing Bluecore catalog product ID’s. Click here to learn more about importing product margin data.

Q: What if I’m unsure about how this will impact the current engagement metrics of my personalized Bluecore campaigns?

  • A: Our campaign A/B testing options are a great method to validate the performance of Margin Optimized Recommendations. Simply select a campaign to test with and create a 2 variant test where: Variant A reflects the current campaign and recommendation strategy. Variant B reflects the exact same campaign and recommendation strategy but also selects the Highest Margin sorting option within the rules assignment step.

Q: How can I see how the use of Margin Optimized Recommendations is impacting margin performance of my Bluecore campaigns over time?

  • A: The Bluecore Margin Optimization Dashboard will provide complete insight into margin performance overall and across each of your Bluecore campaigns including month over month comparisons. Learn more about this dashboard under the Using the Enhanced Analytics: Margin Optimization Dashboard headline above.

Q: The email campaign I want to use Margin Optimized Recommendations on has multiple product blocks, which one should I use this feature on?

  • A: In this scenario, you should apply Margin Optimization to any of the recommendation blocks that are using a strategy that has the sort by Highest Margin option available.

Did this answer your question?