As the marketing practitioner for the e-commerce business, I have created a journey to engage with approximately 10 million users during the Diwali sale and offer period. I now need to test the journey before publishing, as even a small issue in your journey can cause major problems, from broken flows to a poor customer experience. In this blog, we’ll walk through the different testing techniques available in Adobe Journey Optimizer(AJO) and how they help you deliver with assurance.
After creating the journey, we need to see how it interacts with real profiles. That’s where AJO’s Journey Test Mode comes in handy — it lets you test your journey using the test profiles you’ve set up in AEP.
At this point, we can test all the journey workflows with different test profiles that we created in AEP. Now we need to verify how the journey will interact with the real production data.
Journey Dry Run is like a safety net in Adobe Journey Optimizer. It allows you to test your journey with real production data, without ever contacting actual customers or modifying any profile details. It’s a great way to build confidence in your journey design and audience targeting before you hit that publish button.
Now we have tested all the journey workflows with the test profiles, and we know how many profiles will land on each node with the real data. We are now confident to publish the journey.
| Aspect | Test Mode | Dry Run Mode |
| Purpose | The test mode journey uses the test profiles from Adobe Experience Platform (AEP). | The dry run triggers the journey with real production data but without triggering actual actions or updates. |
| Profiles used | Uses test profiles you’ve explicitly created in AEP. | Uses actual production profiles without contacting real customers. |
| Simulated components | Events can be triggered for you with the required configuration. You can fast-forward, wait, and set timeouts. | The entire journey logic is simulated end-to-end with production data. |
| Ideal use case | To verify journey logic and flow using known test data. | To validate audience targeting and journey design in a production-like environment. |
| Publication mode | The journey is published in test mode (not live). | The journey is published in a special dry run mode (live). |
| Visibility of data impact | No impact on real customer profiles or data. | No impact on real customer profiles or data, but it helps you see how real profiles would flow. |
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