Data Builder Guide

Data Builder Guide

Info
If you've ever spent hours rebuilding the same report for different clients or struggled to blend data from multiple ad platforms, Data Builder solves these exact challenges. It handles all the data preparation - organizing sources, selecting fields, and applying filters - so when your data reaches its destination, it's already business-ready and you can focus on what matters most.

What is Data Builder?

Data Builder is a data preparation tool within your Power My Analytics hub that allows you to:

  • Create business-ready datasets from your data warehouse
  • Blend data from multiple sources into unified tables
  • Control exactly which fields and date ranges to include
  • Send datasets to Looker Studio, BigQuery, etc.
  • Get AI-powered insights on your data

Think of it as your data workshop where you can craft exactly the data views you need for your reports and analysis.

Common Use Cases

For Agencies:
  • Create separate datasets for each client
  • Blend performance data across multiple sources
  • Blend client data for internal reporting
  • Get AI automated performance summaries for clients
For E-commerce:
  • Blend advertising costs with sales data
  • Calculate true ROAS across all platforms
  • Track product performance with filtered views
  • Identify anomalies and trends in your sales data with AI
For Marketing Teams:
  • Unify metrics across all channels
  • Create executive dashboards
  • Build campaign-specific analyses
  • Get proactive AI recommendations for optimization



Video Tutorials

How to Create a Dataset

A dataset is a container that organizes related data tables - like a folder for your marketing data. You might create separate datasets for each client, campaign type, or reporting purpose.


How to Create Data Tables

Data tables contain your actual metrics and dimensions. Examples include Facebook Ads campaign performance, Instagram engagement metrics, or Shopify product sales - each customized with only the fields you need.


How to Create Blended Data Tables

Blended data tables combine multiple data sources into one unified view. For example, instead of switching between ad platforms to compare campaign performance, you can see Facebook Ads, Google Ads, and LinkedIn Ads metrics side-by-side in a single table.


How to Send a Dataset to Looker Studio

Once your datasets are ready in Data Builder, sending them to Looker Studio is straightforward. You'll connect through the Power My Analytics connector to access all your prepared data tables in one clean dataset, ready for visualization and reporting.


How to Get AI Insights

Transform your marketing data into actionable intelligence with AI Insights. Learn how to automatically analyze your data tables and datasets to identify trends, spot anomalies, and provide strategic recommendations.





Step-by-Step Instructions

Step 1: Access Data Builder

Navigate to Data Builder in your hub's main navigation bar (located below Sources).

Step 2: Create Your First Dataset

A dataset is like a folder that contains one or more data tables.


Instructions:
  1. Click "+ Create Dataset"
  2. Name your Dataset - Choose a clear, descriptive name (e.g., "Client ABC Reports", "Social Media Performance", "Q1 Campaign Analysis")
  3. Set Available Data Range - Choose how much historical data to include:
    • This controls the maximum date range for all tables in this dataset
    • You can override this for individual tables later


Recommended Options:
  • Last 24 months: Ideal for year-over-year comparisons and trend analysis
  • Custom start to date: Perfect for growing datasets that expand over time
  • Last 60 days: Best for recent performance tracking with week-over-week and month-over-month comparisons
Idea
Choosing the Right Date Range

The date range you select depends on your reporting needs:

Running Date Ranges (e.g., Last 24 Months, Last 60 Days)
  • Best for: Year-over-year comparisons, seasonal analysis, recent performance tracking
  • How it works: Always shows the most recent X period of data
  • Examples:
    • "Last 24 Months" for annual trends and YoY analysis
    • "Last 60 Days" for recent campaign performance and quick pivots
Growing Date Ranges (Custom Start to Date)
  • Best for: Historical tracking, cumulative metrics, Looker Studio reports
  • How it works: Starts from a fixed date and grows as new data comes in
  • Example: Set start date to when you began managing an account - your dataset will include all data from that date forward
Fixed Date Ranges
  • Best for: Specific period analysis, quarterly reports
  • How it works: Shows data only between specific start and end dates
  • Example: Q2 2025 only (April 1 - June 30, 2025)

Step 3: Add Data Tables

Data tables are where your actual metrics and dimensions live.


Instructions:
  1. Click "Create Data Table" within your dataset
  2. Choose Your Sources:
    • Single Source: Select one platform (e.g., just Facebook Ads)
    • Blended: Combine multiple platforms (e.g., Facebook Ads + Google Ads + LinkedIn Ads)

  3. Select Your Fields:
    • Use the search bar to find specific metrics
    • Browse categories: "Most Popular" (expanded by default) or "All"
    • Toggle between Dimensions and Metrics
    • Drag fields to reorder them



  4. Configure Options:
    • Name your data table
    • Set sorting preferences
    • Apply filters if needed
    • Adjust row limits (default: 1,000,000)



AI Insights

What are AI Insights?

AI Insights is an automated analysis feature that provides:

  • Performance summaries with key metrics & trends
  • Anomaly detection and critical alerts
  • Period-over-period comparisons
  • Actionable recommendations
  • Strategic guidance based on your data

Two Types of AI Insights

1. Data Table Insights

Cost: 10 credits
  • Analyze individual data tables
  • Deep single-source analysis
  • Specific metric focus
  • Ideal for platform-specific optimization

2. Dataset Insights

Cost: 15 credits

  • Analyze entire datasets
  • Cross-platform pattern identification
  • Holistic performance view
  • Best for strategic planning

How to Use AI Insights

Instructions for Data Tables:

  1. Navigate to your data table
  2. Click the Action menu (three dots)
  3. Select "Get AI Insights"
  4. Configure your analysis:
    • Choose date range (e.g., "Last 3 months")
    • Toggle "Include Today" if needed
    • Review credit cost
  5. Click "Generate Insights"

Instructions for Datasets:

  1. From the dataset overview
  2. Click the Action menu
  3. Select "Get AI Insights"
  4. Configure and generate (same as above)

AI Insights Report Contents

Your AI-generated report includes:

Performance Summary

  • Key metrics overview
  • Trend identification
  • Success indicators

Most Significant Changes

  • Period-over-period analysis
  • Notable increases/decreases
  • Contributing factors

Critical Anomalies

  • Outliers and unusual patterns
  • Specific dates and metrics
  • Impact assessment

Recommendations

  • Optimization opportunities
  • Risk mitigation strategies
  • Areas for further investigation
  • Budget allocation suggestions

AI Credits System

  • Each account includes monthly credits based on plan
  • Additional credit packages available
  • Credits refresh monthly
  • View remaining credits before generating insights

Best Practices for AI Insights

  1. Field Selection is Key: Choose 5-10 strategic metrics that tell a complete performance story. Too few and you miss patterns; too many and insights lose focus.

  2. Use Cache Strategically: Running the same analysis twice? The second run is free. Plan your date ranges to maximize credit value.

  3. Start with Problem Areas: Generate insights for underperforming channels first - AI excels at finding hidden issues and missed opportunities.

  4. Dataset vs. Data Table: Run Dataset Insights for strategic planning, Data Table Insights for tactical optimization.

  5. Date Range Sweet Spots:

    1. monthly, quarterly, yearly for reports
    2. 60-90 days for trend analysis
    3. 14-60 days for campaign optimization
    4. 7 days for troubleshooting sudden changes
  6. Read Between the Lines: When AI flags an anomaly on a specific date, that's your cue to check what changed - new campaign, tracking issue, or market event.

  7. Export and Share: PDF exports make perfect client reports. Add your recommendations to AI findings for comprehensive analysis.


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