Adbrew Intelligence offers multiple AI agents designed to help you analyze data, optimize performance, build dashboards, and launch campaigns.
Each agent supports Context, which lets you define the scope of what the agent should focus on during a conversation.
Using context correctly ensures that the agent looks only at the data, entities, or rules that matter to your task, making responses more accurate and relevant.
Available Adbrew Intelligence Agents
Currently, Adbrew Intelligence includes four types of AI agents:
1. Deep Analysis Agent
Best for root cause analysis (RCA) and in-depth questions about account performance. This agent has access to multiple data points across your account and helps you understand why performance changed.
2. Dayparting Agent
Analyzes Marketing Stream data and recommends or creates dayparting strategies based on hourly performance trends.
3. Dashboard Agent
Helps create new dashboards or modify existing ones using natural language instructions.
4. Campaign Launcher Agent
Assists with creating and launching campaigns based on your inputs and predefined rules.
What Is Context?
Context defines the scope of your chat with an AI agent.
When context is applied, the agent:
Looks only at the selected campaigns, products, dashboards, or strategies
Ignores irrelevant data outside that scope
Produces more focused and actionable responses
Each agent supports different types of context based on its purpose.
Context Options by Agent
Deep Analysis Agent Context
You can limit analysis to specific parts of your account using:
Campaign
Select one or more campaigns to restrict analysis to those campaigns only.Campaign Label
Labels are Adbrew's way of grouping campaigns. Selecting a label applies analysis only to campaigns within that group.Product
Limits analysis to selected products. This is especially useful for deep dives on product or product-label performance.
When any of these contexts are selected, all questions and insights apply only to the chosen scope.
Dayparting Agent Context
The Dayparting Agent supports the following context options:
Dayparting Strategy
Select an existing strategy if you want to modify or improve it instead of creating a new one.Type
Specify the type of strategy you want to work on:Bids
Placements
Budgets
This ensures the agent creates or updates only relevant dayparting rules.
Dashboard Agent Context
Dashboard
Select an existing dashboard to make changes within it.
This is useful when you want to edit or extend a current dashboard instead of creating a new one from scratch.
New: Account-Level Context (Global Context)
Adbrew Intelligence also supports account-level context, which applies automatically across selected agents.
How to Set Up Account-Level Context
Navigate to Settings from the sidebar
Go to Add to Intelligence
Open the Account Context page
Click Create Context
You can configure the following:
Date Range
Bind context to a specific time period, or
Leave it universal by disabling the date range toggle
Agent Scope
Choose which agents this context applies to:
Deep Analysis
Dashboard
Campaign Launcher
Dayparting
Account Selection
If you manage multiple accounts, choose one or more accounts where this context should apply
Context Definition
Describe the rules, business details, or constraints you want the agent to consider
Once saved, the selected agents automatically fetch this context whenever they are used.
Practical Use Cases
1. Campaign Naming Conventions
If your team follows a strict campaign naming structure, you can define it once as account-level context.
Example:
“All new campaigns must start with the prefix Q4_IN_ followed by product name.”
When you use the Campaign Launcher Agent, it will automatically apply this rule while creating campaigns.
2. Business Events and Performance Context
You can add important business context for specific periods.
Example:
“During Q4, our top product went out of stock, which impacted overall performance.”
When you later use the Deep Analysis Agent to investigate a Q4 performance drop, the agent will:
Factor in the stock-out event
Combine it with advertising data
Provide more accurate explanations and recommendations
Why Context Matters
Using context helps:
Reduce irrelevant insights
Improve accuracy of recommendations
Personalize agent behavior to your business rules
Save time by avoiding repeated explanations