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Audience Signal Analysis Deep Dive Guide

Table of Contents​

  1. Feature Overview
  2. Use Cases
  3. Data Preparation
  4. Operation Workflow
  5. Result Interpretation
  6. Export Functions
  7. Frequently Asked Questions

Feature Overview​

What is Audience Signal Analysis?​

Audience Signal Analysis is one of the three core features of this system, designed to help Google advertising sales teams generate professional audience tag recommendation plans for different advertising products (UAC, PMax, Demand Gen) based on Google Ads big data analysis.

Core Value​

  1. Multi-Product Support: Simultaneously generates recommendation plans for three advertising products: UAC (Universal App Campaigns), PMax (Performance Max), and Demand Gen (Demand Generation)
  2. Standardized Output: Ensures every analysis follows a unified methodology and output format, meeting Google DMS (Digital Marketing Strategist) delivery standards
  3. Data-Driven: Based on real big data analysis results from Google Ads, not subjective judgment
  4. Ready to Use: Generated tags can be directly added to the Google Ads platform for use

How It Works​

The system receives Excel files or Google Sheet links containing audience behavior data, analyzes the data through Google Gemini AI, and generates for each advertising product type:

  • Table Data: Recommendation lists containing Affinity (core interest audiences) and In-Market (high-intent market audiences) tags
  • Slide Content: Professional presentation content including strategy descriptions and 3 audience persona paragraphs

Use Cases​

Typical Application Scenarios​

  1. Client Proposal Preparation: Quickly generate professional data analysis reports when presenting audience signal recommendations to clients
  2. Advertising Optimization: Provide new audience tag suggestions for existing advertising campaigns to improve ad performance
  3. New Product Launch: Provide audience strategy support for newly launched advertising products (such as Demand Gen)
  4. Quarterly Review: Regularly analyze audience signal changes across different industries and update recommendation plans

Applicable Data Types​

  • Industry Dimension: Different industries (e.g., e-commerce, gaming, finance, etc.)
  • Behavior Dimension: User search behavior, app preferences, purchase intent, etc.
  • Tag Dimension: Affinity tags, In-Market tags, app preference tags, etc.

Data Preparation​

Data Source: Connect Benchmark (CBX)​

The data required for the Audience Signal Analysis feature comes exclusively from Google's internal Connect Benchmark (CBX) system. CBX exports a complex Excel file or Google Sheet containing dozens of worksheets, which includes rich data such as user search behavior and app preferences.

InsightHub is specifically designed to intelligently automatically filter and extract the required core data from this complex data file. You don't need to manually clean or delete any worksheets.

Data Format Requirements​

The system will automatically search for and parse the following 5 required worksheets in your uploaded file. Please ensure your CBX export file contains these worksheets (even if their names may be slightly different due to truncation or renaming, the system can intelligently identify them).

Required Worksheet NameDescription
inputInput configuration table. The system reads the overall industry name from cell B4 of this table.
user_behavior_Prod_Affinity_SearchSearch behavior data for core interest audiences (Affinity).
user_behavior_Prod_InMarket_SearchSearch behavior data for high-intent market audiences (In-Market).
user_behavior_AppAffinitiesUser app preference data.
AffinityGeminiOutputRaw persona data initially processed by Gemini AI.

Important Notes:

  • Intelligent Recognition: You don't need to worry about worksheet names being truncated by Excel (e.g., user_behavior_Prod_Affinity_Search becomes user_behavior_Prod_Affinity_Se) or renamed when exported from Google Sheets due to special characters. The system's intelligent matching algorithm can handle these situations.
  • Automatic Merging: In some cases, CBX splits ..._Search tables into ..._Vir and ..._Sea tables. The system can automatically identify and merge data from these two tables.
  • Automatic Ignoring: All other worksheets not in this list of 5 required worksheets will be automatically ignored by the system.

Data Quality Checks​

The system automatically performs the following checks before analysis:

  1. Required Worksheet Validation: Ensures all required worksheets exist
  2. Data Completeness Validation: Checks whether each worksheet contains valid data
  3. Industry Name Extraction: Reads the industry name from cell B4 of the input worksheet; uses default value if empty

Operation Workflow​

Step 1: Log In to the System​

  1. Access the system URL (provided by administrator)
  2. Click "Sign in with Google"
  3. Authorize the system to access your Google account information (for authentication and Google Sheet access)

Permission Notes:

  • The system needs access to your Google account information (name, email)
  • If using Google Sheets, read-only access to Google Sheets is required
  • All permissions are used only for feature operation and will not be used for other purposes

Step 2: Select Feature​

  1. Click the "Audience Signal Analysis" card on the system homepage (Dashboard)
  2. Enter the Audience Signal Analysis page

Step 3: Upload Data​

The system supports two data input methods:

Method A: Upload Excel File​

  1. Click the "Upload Excel File" button
  2. Select your Excel file in the file selection dialog
  3. The system will automatically validate the file format and display file information

File Limitations:

  • File size: Recommended not to exceed 10 MB
  • File format: .xlsx (Excel 2007 and above)
  • Number of worksheets: Must contain all required worksheets
  1. Copy Link: Directly copy the target Google Sheet's URL in your browser.
  2. Paste Link: Paste the link in the InsightHub page input box.
  3. No Sharing Required: Thanks to the Google OAuth permissions you granted during login, the system can directly and securely access spreadsheet data you have permission to view. You don't need to configure any "sharing" settings, such as "Share with anyone who has the link."
  4. Click Load: Click the "Load" button, and the system will begin reading data.

Permission Check:

  • The system will automatically verify whether your currently logged-in Google account has access to that Sheet.

Step 4: Configure Analysis Parameters​

  1. Select Industry: Choose the industry you want to analyze from the dropdown menu
  2. Set Query Language: Select the query language you want Gemini AI to use
  3. Set Output Language: Select the language for the final report
  4. Edit Prompt: The system has built-in targeted prompts; generally no modification needed

Step 5: Start Analysis​

  1. Click Analyze: Click the "Start Analysis" button to launch the analysis process
  2. Wait for Results: The analysis process may take a few minutes, please wait patiently

Results Page Details​

Similar to Market Opportunity Analysis, the Audience Signal Analysis results page is also carefully designed as a "what you see is what you get" slide preview mode, ensuring the professionalism and consistency of the final deliverables.

1. Page Layout​

The results page also uses a multi-tab layout, with each tab corresponding to a Category. Each category's results include the following core elements:

  • Slide Canvas: The entire content area is designed as a 16:9 slide canvas, containing all standard elements such as titles, charts, insight summaries, and footnotes.
  • Left: Trends and Insights Chart
    • Core Chart: The core of this feature is a comprehensive Table, not a bubble chart. This table clearly displays key signal metrics for each sub-category.
    • Key Metrics:
      • Search Interest Index: Reflects the popularity of the sub-category among audiences.
      • Year-over-Year Growth Rate: Reveals the growth trends and potential of the sub-category.
      • Competition Level: Shows the competitive situation in this field.
      • Average CPC: Provides cost reference for advertising.
    • Visual Aids: Key data in the table (such as high growth rates) will be highlighted through colors or icons, helping users quickly identify important signals.
  • Right: AI Insight Summary:
    • Core Insights: Two-level priority analysis (Priority 1 & Priority 2) automatically generated by Google Gemini AI based on the left table data.
    • Core Highlights: Summarizes the key findings for that priority, such as "high growth with moderate competition" blue ocean opportunities.
    • Strategy Recommendations: Based on core highlights, proposes specific marketing or product strategies.
  • Footer: Clearly labels the data period on which this analysis is based.

2. Interactive Features and Highlights​

The results page is not just a static display but also provides rich interactive features to enhance usability and flexibility.

  • In-Place Content Editing:
    • Design Philosophy: Like Market Opportunity Analysis, all text elements on the results page—from main titles, subtitles, to every AI-generated insight summary and strategy recommendation—support click-to-edit.
    • Implementation: Achieved through the EditableText component, users can directly fine-tune AI-generated content on the page to meet business needs, ensuring exported content perfectly fits delivery scenarios.
  • Rich Export Options:
    • Download Session (ZIP): Packages and downloads all outputs from this analysis (including raw data, result data, images, PPTX files, and metadata) for easy archiving or sharing.
    • Export as PPTX: One-click download of the current category's slides as a .pptx format file.
    • Export as Google Slides: Through "template replacement" mode, automatically fills results into a preset Google Slides template.
    • Export as Image (PNG): Downloads the slide canvas or individual table as high-resolution PNG images.
    • Copy to Clipboard: Quickly copies slide or chart images to the system clipboard.
  • Table Interactions:
    • Sorting: Clicking table headers can sort any column in ascending or descending order, allowing users to examine data from different dimensions (e.g., highest growth rate, lowest competition).
    • Filtering and Search: Built-in search box can quickly filter sub-categories containing specific keywords.

Result Interpretation​

Table Data Interpretation​

Each advertising product type's (UAC, PMax, Demand Gen) table contains the following columns:

Column NameDescriptionExample
Signal TypeTag type"Affinity" or "In-Market"
Audience Signal / NameTag name"Technology Enthusiasts"
Professional AnalysisAI-generated selection rationale"This tag is based on Google Ads big data analysis..."

Key Interpretation Points:

  • Affinity Tags: Indicate users' long-term interest in this field, suitable for brand building and user cultivation
  • In-Market Tags: Indicate users are actively seeking related products or services, suitable for conversion optimization
  • Professional Analysis: Explains why this tag was selected, based on insights from Google Ads big data analysis

Slide Content Interpretation​

Each slide contains the following sections:

1. Title Area​

  • Description Text: Such as "Audience Signal Methodology | UAC"
  • Main Title: Advertising product type name

2. Subtitle​

  • Content: Approximately 100-word strategy description
  • Purpose: Summarizes the audience signal recommendation strategy for this advertising product

3. Audience Persona Paragraphs (3)​

Each audience persona paragraph contains:

  • Title: Persona name (e.g., "Professional and Semi-Professional Creators")
  • Description: 20-30 word explanation describing the characteristics of this audience
  • Tags: 3 tags, each containing:
    • type: Tag type ("Affinity" or "In-Market")
    • name: Tag name

Persona Distribution:

  • First Persona: Primarily based on Affinity tags (all 3 tags are Affinity)
  • Second Persona: Mixed Affinity and In-Market tags (total of 3 tags, can be mixed)
  • Third Persona: Primarily based on In-Market tags (all 3 tags are In-Market)

Differences Between the Three Advertising Products​

UAC (Universal App Campaigns)​

  • Use Case: Mobile app promotion
  • Tag Characteristics: More focused on app preferences and in-app behavior
  • Persona: Biased toward mobile app user characteristics

PMax (Performance Max)​

  • Use Case: Omnichannel advertising
  • Tag Characteristics: Balanced Affinity and In-Market tags
  • Persona: Covers broader audience characteristics

Demand Gen (Demand Generation)​

  • Use Case: Demand mining and brand building
  • Tag Characteristics: More focused on Affinity tags for cultivating potential demand
  • Persona: Biased toward interest and value characteristics

Export Functions​

Export Options​

The system supports multiple export formats:

1. Download Session ZIP​

Contents:

  • YAML configuration file (contains all analysis metadata)
  • XLSX detailed data tables (one worksheet per advertising product)
  • PPTX presentation (contains slides for all advertising products)
  • PNG image files (slide images)
  • Original data file (if Excel was uploaded)

File Naming Convention:

InsightHub-YYYYMMDD-HHmmss-{sessionUUID}-{fileTypeLabel}-{languageLabel}.zip

Use Cases:

  • Complete backup of analysis results
  • Share with team members
  • Archive storage

2. Export PPTX​

Contents:

  • One slide per advertising product
  • Complete strategy descriptions and persona content

Use Cases:

  • Direct use for client presentations
  • Integration into existing presentations

3. Export Images​

Contents:

  • Slide PNG images (one per advertising product)

Image Quality:

  • Resolution: Automatically optimized based on screen resolution
  • Format: PNG (supports transparent background)
  • Clarity: Suitable for printing and presentation use

Use Cases:

  • Insert into other documents
  • Use for social media sharing
  • Print output

4. Copy to Clipboard​

Supported Formats:

  • Images (PNG format)
  • HTML code (for web embedding)

Use Cases:

  • Quick paste into other applications
  • Insert images in emails
  • Insert content in documents

Export Operation Steps​

  1. On the results page, find the content to export (table or slides)
  2. Click the corresponding export button ("Download," "Copy," etc.)
  3. Complete the operation according to prompts

Notes:

  • Exporting large amounts of data may take some time, please wait patiently
  • If export fails, the system will display error information; please retry according to prompts

Frequently Asked Questions​

Q1: Why did my Excel file upload fail?​

Possible Reasons:

  1. Incorrect file format (must be .xlsx format)
  2. Missing required worksheets
  3. File size exceeds limit
  4. File is corrupted or unreadable

Solutions:

  1. Confirm file format is .xlsx
  2. Check if all required worksheets are included (input, user_behavior_Prod_Affinity_Search, etc.)
  3. Try re-saving the file in Excel
  4. Check if the file is being used by another program

Possible Reasons:

  1. Incorrect link format
  2. No access permissions
  3. Sheet has been deleted or moved
  4. Missing required worksheets

Solutions:

  1. Confirm link format is: https://docs.google.com/spreadsheets/d/...
  2. Check the Sheet's sharing permissions
  3. Confirm the Sheet contains all required worksheets
  4. Try logging in to the system again

Q3: What if the number of generated tags doesn't meet expectations?​

Possible Reasons:

  1. Incorrect quantity requirements in prompt configuration
  2. Insufficient available tags in input data
  3. AI understanding deviation

Solutions:

  1. Check quantity requirements in the prompt (affinityCount and inMarketCount)
  2. Confirm input data contains sufficient tag data
  3. Try editing the prompt to provide clearer guidance
  4. Contact system administrator to report the issue

Q4: How do I add generated tags to Google Ads?​

Operation Steps:

  1. On the results page, find the tag names you want to use
  2. Log in to the Google Ads platform
  3. Enter the corresponding advertising campaign settings
  4. In the "Audiences" or "Audience Signals" section, search and add tags

Notes:

  • Ensure tag names exactly match standard tag names in the Google Ads platform
  • Some tags may only be available in specific advertising products
  • It's recommended to verify tag effectiveness in test campaigns first

Q5: Can I analyze multiple industries simultaneously?​

Yes, but it's recommended:

  • Each analysis session focuses on one industry for more precise recommendations
  • If you need to analyze multiple industries, create separate analysis sessions
  • The system automatically saves all historical analysis records for easy viewing and comparison later

Q6: How do I save analysis results?​

The system automatically saves analysis results to browser local storage (IndexedDB). You can:

  1. View History: View all historical analyses in the Dashboard
  2. Export ZIP: Download the complete analysis results package
  3. Reload: Click on history records to view results again

Note: Data stored in browser local storage may be lost after clearing browser data. It's recommended to regularly export ZIP files for backup.

Technical Details (Optional Reading)​

Data Processing Workflow​

  1. File Parsing: Uses XLSX library to parse Excel files, or reads data through Google Sheets API
  2. Data Normalization: Automatically cleans formatting characters, unifies field names, validates data types
  3. Data Validation: Checks required worksheets, handles null values, identifies duplicate data
  4. AI Processing: Performs data analysis and tag recommendation generation through Google Gemini API
  5. Result Storage: Saves results to browser local storage (IndexedDB)

AI Analysis Mechanism​

The system uses Google Gemini 2.5 Pro model for the following analysis:

  1. Tag Matching: Matches tags in input data with standard Audience List
  2. Tag Recommendation: Recommends the most suitable tags based on advertising product characteristics and industry features
  3. Professional Analysis Generation: Generates professional analysis descriptions for each recommended tag
  4. Persona Generation: Generates 3 audience persona paragraphs based on tag data

Tag Matching Algorithm​

The system uses a fuzzy matching algorithm to match tag names in input data with the standard Audience List:

  1. Similarity Calculation: Uses string similarity algorithm to calculate matching degree
  2. Type Identification: Automatically identifies tag type (Affinity or In-Market)
  3. Validation Mechanism: Ensures matched tags exist in the standard list

Related Documentation: