What Is Product Insights?
Product Insights is an analytics section that provides deeper knowledge of product and product group performance. It validates currently running campaigns and informs future campaign creation by revealing patterns and opportunities at the product level that aren't visible in Meta Ads Manager.
By integrating Google Analytics with Meta advertising data, Product Insights closes the analytics gap and provides an unbiased perspective on item-level performance. When used effectively, it helps you exclude spend wasters, promote winners, and identify catalog pain points to optimize your Dynamic Product Ads.
How Product Insights Works
Prerequisites
To access Product Insights, you need:
Active DPA campaigns running through Hunch
Meta authorization for both Campaigns and Catalogs sections
Google Analytics authorization (optional, but recommended for complete post-click attribution data)
Product Insights appears as a new tab in the main navigation. If you don't see data yet, you'll find instructions on setting up the required prerequisites to start collecting insights.
Core Interface
Product Insights combines catalog data with performance metrics from Meta (pre-click and post-click) and, optionally, Google Analytics (post-click with different attribution). The interface is organized into several key sections:
Page Configuration:
Page Preset - Quick-start configurations with pre-applied filters for common optimization tasks
Last Sync Time - Shows when catalog data was last updated
Data Selection & Filtering:
Group By - Choose whether to group products by brand or product type (determines which groups are displayed in Groups View and affects search behavior)
Search - Find specific groups or items by name or ID (search scope adapts based on current view)
Source - Filter data by specific campaigns, ad sets, or individual ads
Date Period - Define the timeframe for performance data
Sorting - Order by metrics (ascending/descending) or by brand/product type name (A-Z or Z-A)
Filters Panel:
Catalog Selection - Persistent filter to choose which catalog to analyze within the selected account (cannot be cleared)
Add Filter - Add catalog data filters (brand, product type) or metric filters (ROAS, Spend, CTR, etc.)
Table View
View Tabs (left side of table header):
Groups View - Analyze performance by brand or product type (which groups are displayed depends on Group By selection). Select individual groups (checkboxes appear on hover) to filter the data and focus on specific brands or product types for deeper analysis.
Items View - Review individual product performance for granular optimization. This view enables the Actions Bar for creating or modifying product sets.
Column Presets - Save and apply custom metric combinations for the table
Charts / Analysis Tools (right side of table header) - Opens item distribution chart panel for visual pattern analysis
Table Data - Product or group rows with performance metrics
Summary Row - Aggregated totals at bottom of table
Actions Bar (floating above summary, visible in Items View):
Action scope selector (first X items or X percentage)
Preview in Charts button
Include/Exclude from Set button
Create Set button
Key Features
1. Multi-Dimensional Filtering
Combine multiple filters to surface actionable insights. The platform helps you start with recommended page presets that apply proven filter combinations for common optimization tasks.
Best practices:
Exclude outliers by filtering out items with zero spend, impressions, or clicks
Focus on statistically significant data by setting minimum thresholds
Use metric filters to isolate specific performance segments
2. Visual Pattern Recognition
Item distribution charts reveal patterns at a glance by plotting products across two key metrics. Each chart preset is designed for specific optimization goals:
Budget Allocation Chart - Compare spend against revenue to identify both high-performers and budget waste
Performance Chart - Spot efficiency opportunities and scaling candidates
Conversion Chart - Diagnose click-to-conversion issues
Use charts for quick filtering by selecting areas of interest, then validate your selection with the expanded view for more clarity before taking action.
3. Direct Campaign Actions
Transform insights into campaign optimizations without leaving Product Insights:
Create Set - Build new product sets from filtered or selected items
Include in Existing Set - Add high-performers to active sets
Exclude from Existing Set - Remove poor performers from active sets
Understanding Product-Level Metrics
While the metrics in Product Insights match those available in the Campaigns section, their behavior and interpretation differ at the product level:
Key differences:
Individual products experience higher volatility than campaign-level aggregates
Statistical significance requires minimum thresholds for spend, impressions, and conversions
The relationship between metrics reveals different patterns (e.g., high CTR with low CVR indicates product-page issues rather than targeting problems)
Common filtering patterns:
Exclude products with insufficient data (< minimum spend/impressions)
Filter out products with revenue but no clicks (likely cross-sell/upsell rather than direct ad performance)
Remove products with impressions but zero clicks (creative or relevance issues)
Page presets and chart configurations are designed to guide you toward these filtering best practices automatically.
General Workflow
Starting from scratch:
Select your desired date period to analyze
Choose whether to analyze all campaigns or filter by specific source (campaigns, ad sets, or ads)
Apply filters to exclude irrelevant items (zero spend, insufficient impressions, etc.)
Use item distribution charts to identify patterns and narrow your selection
Sort by relevant metrics and use the action scope selector to choose the portion of items you want to work with
Take action: preview in charts for validation, then create or modify sets
Starting with page presets:
Select a page preset that matches your optimization goal
Review the pre-configured filters and date range
Adjust filters as needed to refine your analysis
Use the results to update existing sets or create new ones
Important Notes
Data Attribution: Meta provides both pre-click (impressions, clicks, CTR) and post-click (conversions, revenue) metrics. Google Analytics integration is optional but recommended for post-click data with different attribution modeling, which often provides a more complete view of the customer journey. For the most reliable insights when using GA, ensure it's properly tracking your product pages and conversions.
Statistical Significance: Product-level data is more volatile than campaign aggregates. Always use minimum thresholds for spend, impressions, or conversions to ensure you're making decisions based on meaningful data rather than noise.
Set Management: Actions taken in Product Insights affect your product sets immediately after catalog sync. If modified sets are used in active campaigns, changes will impact those campaigns once the sync completes.
Troubleshooting
Issue | Solution |
No data appearing in Product Insights | Verify Meta and Google Analytics authorizations are active; ensure DPA campaigns have run during selected date period |
Metrics don't match Ads Manager | Product Insights uses Google Analytics for post-click data, which may differ from Meta's attribution; check GA tracking implementation |
Charts showing unexpected patterns | Check for outliers by applying minimum spend/impression filters; verify date period includes sufficient data volume |