Documentation Journey Optimizer Journey Optimizer Guide

Use Decisioning in a code-based experience with Content experiment

Last update: February 10, 2025

Topics:
Decisioning

CREATED FOR:

Intermediate
Experienced
User

This use case presents all the steps needed to use Decisioning with the Journey Optimizer code-based channel.

In this example, you are unsure if a specific ranking formula will perform better than the pre-assigned offer priorities. To measure which one performs best for your target audience, you create a campaign using Content experiment where you define two delivery treatments:

The first treatment uses priority as the ranking method.
The second treatment uses a formula as the ranking method.

Create selection strategies

First, you need to build two selection strategies: one with priority as the ranking method, and another one with a formula as the ranking method.

NOTE

You can also create single decision items without having to run through a selection strategy. The priority set for each item will apply.

Create a strategy using priority

To build the first selection strategy with priority as the ranking method, follow the steps below.

Create a decision item. Learn how
Set the Priority of the decision item compared to others. If a profile qualifies for multiple items, a higher priority grants the item precedence over others.

NOTE
The priority is an integer data type. All attributes that are integer data types should contain integer values (no decimals).
Set the decision item’s eligibility:
- Define audiences or rules to restrict the item to specific profiles only. Learn more
- Set capping rules to define the maximum number of times an offer can be presented. Learn more
If needed, repeat the steps above to create additional decision items.
Create a collection where your decision item(s) will be included. Learn more
Create a selection strategy and select the collection that contains the offer(s) to consider.
Choose the ranking method to use to select the best offer for each profile. In this case, select Offer priority: if multiple offers are eligible for this strategy, the Decisioning engine uses the value set as Priority in the offer(s). Learn more

Create another strategy using a formula

To build the second selection strategy with select a formula as the ranking method, follow the steps below.

Create a decision item. Learn how
Set the decision item’s eligibility:
- Define audiences or rules to restrict the item to specific profiles only. Learn more
- Set capping rules to define the maximum number of times an offer can be presented. Learn more
If needed, repeat the steps above to create additional decision items.
Create a collection where your decision item(s) will be included. Learn more
Create a selection strategy and select the collection that contains the offer(s) to consider.
Choose the ranking method you want to use to select the best offer for each profile. In this case, select Formula to use a specific calculated score to determine which eligible offer to deliver. Learn more

Build a code-based experience campaign

Once you configured the two selection strategies, create a code-based experience campaign where you define a different treatment for each strategy, in order to compare which one performs best.

Create a campaign, and select the Code-base experience action. Learn more
From the campaign summary page, click Create experiment to configure your content experiment. Learn how
From the campaign summary page, select a code-based configuration, and click Edit content.
From the content edition window, to start personalizing Treatment A, click Edit code.
From the code editor, select Decision policy, click Add decision policy and fill in the decision details. Learn more
In the Strategy sequence section, click the Add button, and choose Selection strategy. Learn more

NOTE
You can also select Decision item to add single items without having to run through a selection strategy. The priority set for each item will apply.
Select the first strategy that you created - the one with priority as the ranking method.
Save your changes and click Create. The new decision is added under Decision policy.
Click the Insert policy button. The code corresponding to the decision policy is added. Then add all the attributes you want to the code, including profile attributes. Learn more
Save your changes.
Go back to the content edition window, select the + button to add Treatment B, select it and click Edit code.
Repeat steps 5 and 6 above to create another decision policy and select the second selection strategy that you created - the one with the formula as the ranking method.
Edit your decision policy as wanted (see steps 8 and 9 above).
Save your changes and publish your code-based-experience campaign.

After running the experiment, track how your campaign treatments are performing with the experimentation campaign report. You can then interpret the results of your experiment. Learn how

If the result is conclusive:

You can push the treatment with the best performing ranking to all your customers.
Or you can create a new campaign using the selection strategy where the best performing ranking method is replicated.

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