You cannot see which products each channel overlooks
Connect your product feed with Google Ads, Meta Ads, GA4 and store data by product or variant ID. Cross-channel analysis reveals exposure and sales differences before you use a custom label to activate selected products.
Cross-channel analysis
- Feed label
- cl_channels
- Required data
- Google Analytics 4
- Type
- Products
Why does it matter?
- Separate reports make assessment harder
Without a shared view, comparing the same products is difficult. A product or variant identifier connects data from different sources.
- Channels promote different products
A product that performs well in one channel may receive little exposure in another. This calls for a review of campaign structure and budget allocation.
- Measurement can be incomplete
GA4 revenue and orders can differ from store data. These discrepancies affect the choice of segmentation source.
How to diagnose the problem?
Open Views → Products Performance and analyze products, brands or categories.
- 1
Compare impressions and spend for the same products in Google Ads and Meta Ads.
- 2
Find products with high revenue in Google Ads or GA4 but few impressions in Meta Ads.
- 3
With an API connection, compare store Net Revenue and Orders against GA4 Net Revenue and Purchase Quantity, accounting for metric definitions.
Action strategy
- AInvestigate overlooked products
Check whether exposure differences result from algorithms or campaign structure. For a larger group of effective but overlooked products, consider a separate Meta Ads campaign.
- BChoose your segmentation source
If revenue and order discrepancies between GA4 and your store exceed 15%, consider using store data for segmentation. First check that date ranges and metrics are comparable.
What to measure?
- Impressions
Compare product exposure across advertising platforms.
- Spend and revenue
Look for differences between product funding and performance in individual channels.
- Data discrepancies
Monitor revenue and purchase-data differences between GA4 and your store.
Cross-channel analysis is not a standalone bidding strategy. It provides the shared data view needed to choose products, channels and segmentation sources.
More frameworks
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cl_returns- IdoSell
- #11Products
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cl_new_products- IdoSell
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cl_margin- IdoSell
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Black Week customers
lista_bfcm- IdoSell
- Google Ads
- Meta Ads
Frequently asked questions
Can Google Ads and Meta Ads revenue be added together?
That sum should not be treated as store revenue because both platforms may claim the same purchase. Data Octopus helps compare sources, but attribution still needs to be considered.
Why does a product fail to match across sources?
Check whether each source uses product or variant IDs and whether their formats agree. In Data Octopus, a shared key is essential for correctly matching performance.
Do Orders and Purchase Quantity mean the same thing?
Do not assume they are equivalent: order counts and purchased unit counts can differ. Before comparing these columns in Data Octopus, check their source definitions.
Do few impressions mean a product has little potential?
No. Limited exposure is not proof of weak demand. In Data Octopus, check sales in other channels before deciding to exclude a product.
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