When you are thinking about facilitating your customer’s buying journey with relevant content, two of the most common use cases are:

Matching content to a specific Role in the buying journey

Matching content to a specific Product that is part of offer to the customer

In your Salesforce org, these are typically stored in Related Lists within the Opportunity object. The standard Salesforce objects for these related lists are Contact Role and Opportunity Product respectively.

Setting Up Predictive Content

The key to setting up Seismic Predictive Content in Salesforce is creating your Seismic Data Source correctly. Since related list fields are separate from both standard and custom fields in the parent object (for example, Opportunities), this can be a frustrating task. Here’s a simple “how-to” for using related list fields for Predictive Content:

1.0 In the Library, navigate to your dedicated folder for Data Sources (MPI-Tip #1: It’s best practice to have a dedicated Data Sources folder under your top-level Admin folder) and select “+ New” and then Data Source.

2.0 Give the Data Source a unique name, select Salesforce.com as the Source Type and select your target Salesforce org.

3.0 Select your Base Object. MPI-Tip #2: Instead of using the Parent Object, such as Account or Opportunity, we’re going to use the Related List object as our Base Object. In this example, we’re building a Data Source for a product-match predictive rule, so we are going to select “Opportunity Product” as our Base Object. (If you were building a predictive rule for a persona or role, you would choose “Opportunity Contact Role” instead.) Click “Next.”

4.0 Select the following fields from the OpportunityLineItem (that’s the standard API name for Opportunity Products) list displayed:

4.1 Id (Line Item ID)

4.2 MPI-Tip #3: Expand the Opportunity item in the list, click Load More until you can see “Id (Opportunity ID),” and select that field. If you plan to use Sales Stage in conjunction with Products, select the “StageName (Stage)” field as well.

4.3 Finally, expand the “Product2 (Product)” item and click Load More until you see the “Name (Product Name)” field. Select that field. MPI-Tip #4: Do not use the “Name” field you may have seen earlier in the list, as that is the long name for Opportunity Product and won’t match with your content property values.

4.4 Click “Confirm.”

5.0 Finish creating your Data Source with the following steps. Refer to the screenshot below.

5.1 Verify the correct fields are selected. In the example, we added Opportunity_StageName so that we could use Stage in our predictive filter later.

5.2 Create a parameter that the Data Source will use as the “Input Id” for the filter. MPI-Tip #5: Use a clear, descriptive name such as “InputId.”

5.3 Create a filter using MPI-Tip #6, not the Base Object Id field, rather the Opportunity_ID field. It’s best practice to highlight the field and then click “Add Selected Fields.” That avoids any typos, which will render the Data Source dysfunctional. No one likes a dysfunctional Data Source.

5.4 Optionally, click “Generate” to preview the SQL query.

5.5 Click “Finish.”

MPI Tip #7: Test your new Data Source. Find an opportunity in your Salesforce org that has Opportunity Products assigned to it. Copy the Opportunity ID for that opportunity from the address bar in the browser. It should look something like this. Copy and paste in the highlighted part.


That’s it, you’ve done it! Now you can proceed to create the Predictive Content rule in Seismic by navigating to System Settings and selecting Predictive Content. Name your new rule, select the Data Source you just created, and follow the normal procedure for the remaining Predictive Content fields.

MPI-Tip #8: Make sure 1.) your Content Property values are identical to their related values in the Salesforce object you are working in, 2.) your Content Properties are assigned to content pieces correctly, and 3.) your content is published in a Profile or Collection visible to the end-user.

Next time we’ll dive into some tips for creating the Predictive Content rule.

Written by Market-Partners Inc.
Posted August 1, 2022

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