1.1.2 Adobe Marketing Agent with ChatGPT

Video

In this video, you’ll get an explanation and demonstration of all the steps involved in this exercise.

1.1.2.1 Create custom app in ChatGPT for Adobe Marketing Agent

NOTE
Using Adobe Marketing Agent in ChatGPT requires the following:
  • a paid version of OpenAI’s ChatGPT
  • using the ChatGPT web client

Go to https://chatgpt.com/ and log in using your account details. Once you’re logged in, you should see this. Click your username.

ChatGPT

Select Settings.

ChatGPT

Go to Apps and then select Advanced settings.

ChatGPT

Turn on Developer mode and then click Back.

ChatGPT

Click Create app.

ChatGPT

Fill out the fields like this:

  • Name: Adobe Marketing Agent
  • MCP Server URL: check with your Adobe representative
  • Authentication: OAuth

Check the checkbox for I understand and want to continue.

Click Create.

ChatGPT

ChatGPT will now attempt to connect to your Adobe account. Select Allow Access and then you’ll have to log in with your Adobe account.

ChatGPT

Once you’ve logged in successfully, you should see that your Adobe Marketing Agent is now connected successfully.

ChatGPT

1.1.2.2 Set context in Adobe Marketing Agent

Close this window.

Agent Orchestrator

You should then see this. Click the + icon, go to More and then select Adobe Marketing Agent.

Agent Orchestrator

Before interacting further with Adobe Marketing Agent through ChatGPT, the context needs to be set.

For this exercise, the context needs to be set to use:

  • Sandbox: Prod - Accelerate (VA7)

The Sandbox setting helps to identify which sandbox AI Assistant should look at when asking questions.

  • Dataview: Accelerate 2026 B2C

The Dataview setting helps to identify which dataview AI Assistant should look at when asking questions.

Enter the following Prompt and click the send button.

list sandboxes

Agent Orchestrator

You should then see a similar list of available sandboxes. The current sandbox in this example is set to prod.

To change that to the sandbox that needs to be used, enter the following Prompt and click the send button.

switch to sandbox accelerate

Agent Orchestrator

You should then see this. Click Set Context.

Agent Orchestrator

You should then see this. Enter the following Prompt and click the send button to set the dataview to use.

list dataviews

Agent Orchestrator

You should then see a similar list of available sandboxes. The current sandbox in this example is set to prod.

To change that to the sandbox that needs to be used, enter the following Prompt and click the send button.

switch to Accelerate 2026 B2C

Agent Orchestrator

You should then see this. Click Set Context.

Agent Orchestrator

You should then see this.

Agent Orchestrator

Your context is now propermy set, so you can start sending specific prompts next.

Intent

Get a toplevel pulse on category demand—Mobile, Landline, Internet, TV, Fiber—specifically for the most recent 60 days. This sets baselines for seasonality, promo effects, and regional variance after the New York rollout.

Enter the following Prompt and click the send button.

Show me purchases by mainCategory over the last 2 months.

Agent Orchestrator

You should then see this:

Agent Orchestrator

Enter the following Prompt and click the send button.

Show me purchases by mainCategory = Fiber over the last 2 months per week

Agent Orchestrator

You should then see this, which drills down into Fiber-specific trends.

Agent Orchestrator

1.1.2.4 Correlate Orders with Content Preferences

Intent

Test the hypothesis that a preference for a specific genre (e.g., SciFi, Sports, Drama) predicts broadband upgrade behavior—especially for high bandwidth needs.

First, you need to find out which field is used to store the genre preference.

Enter the following Prompt and click the send button.

Which field is used to store the preferred genre in the sandbox accelerate?

Agent Orchestrator

You should then see this, which shows that the field used for genre is _experienceplatform.individualCharacteristics.preferences.preferredGenre.

Agent Orchestrator

With that information, you can start drilling down in the purchase data.

Enter the following Prompt and click the send button.

Show me ordersYTD by preferredGenre for the last 2 months

Agent Orchestrator

You should then see this. Click Research.

Agent Orchestrator

You should then see this.

Agent Orchestrator

Scroll down to see more information.

Agent Orchestrator

1.1.2.5 Identify Existing Fiber Journeys

Intent

Discover which active or recently concluded journeys include “Fiber” in the title—e.g., “Fiber Upgrade NYC – Sept”, “Fiber Trial – Streaming Bundle”.

Enter the following Prompt and click the send button.

What journeys exist?

Agent Orchestrator

You should then see this. Click Research.

Agent Orchestrator

You should then see a list of journeys.

Agent Orchestrator

Enter the following Prompt and click the send button.

Which of these journeys has 'Fiber' in its name?

Agent Orchestrator

You should then see this. Click Research.

Agent Orchestrator

You should then see this.

Agent Orchestrator

Scroll down to see more details.

Agent Orchestrator

Enter the following Prompt and click the send button.

show me the details of the journey 'CitiSignal - Fiber Max Launch Promotion'

Agent Orchestrator

You should then see this.

Agent Orchestrator

1.1.2.6 Validate journey performance via fallout analysis

Intent

You want to understand journey performance fallout to know if there are any nodes or conditions within the journey that are experiencing a large percentage of profiles being dropped. This is helpful in understanding if additional adjustments are needed in the journey.

Enter the following Prompt and click the send button.

Create a fall-out report on the "CitiSignal - Fiber Max Launch Promotion" journey

Agent Orchestrator

You should then see this.

Agent Orchestrator

Scroll down a little bit. You can now review the table by inspecting each node and its respective enter numbers, fallout numbers, and fallout rate.

Agent Orchestrator

Scroll down a little bit more to see observations and recommendations.

Agent Orchestrator

You’ve now completed this lab.

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