Track Google Ads Shopping performance in BigCommerce dashboard

Export Shopping campaign metrics

ConvertMate connects to your Google Ads account and automatically pulls performance data from your Shopping campaigns every hour. The system retrieves product-level metrics including clicks, impressions, cost, conversions, and conversion value for each item in your product feed. This eliminates the need to manually download CSV reports or navigate between multiple Google Ads dashboards to understand which products are driving results.

Process and normalize data

ConvertMate matches Google Ads product identifiers to your BigCommerce SKUs using multiple data points including product titles, GTINs, and custom labels. The system calculates essential metrics like return on ad spend, cost per conversion, click-through rate, and impression share for each product. Data is normalized to account for currency differences, time zone variations, and attribution windows so you see accurate performance comparisons.

Display metrics in admin panel

Performance data appears directly within your BigCommerce admin interface on individual product pages and customizable dashboard widgets. You can view which products generate the highest ROAS, identify items with high impressions but low clicks that need better product images, and spot conversion opportunities without leaving your store management workflow. Dashboard widgets update automatically so you always see current performance data alongside your inventory levels and sales metrics.

Identify underperforming products to pause or optimize

An outdoor equipment retailer running Shopping campaigns for 800+ products discovered that 23% of their products had high click costs but zero conversions over 60 days. By viewing Google Ads metrics directly in their BigCommerce product list, they quickly filtered by cost per click and conversion rate to identify problem products. They paused ads for discontinued items, improved product images for high-impression items with low CTR, and reallocated budget to their top 50 converting products, reducing overall ad spend by 18% while maintaining revenue.

Optimize product feed data based on ad performance

A home decor store noticed certain product categories had strong impression volume but poor click-through rates when viewing Shopping metrics in their BigCommerce dashboard. They filtered products by impression count and CTR to identify items with visibility but weak engagement. By updating product titles to include high-performing search terms and improving main product images, they increased overall Shopping campaign CTR from 0.8% to 1.4% within three weeks, generating 35% more traffic without increasing ad budget.

Prioritize inventory restocking using ad performance data

A fashion accessories brand used combined Google Ads and BigCommerce inventory data to inform purchasing decisions. When viewing products sorted by ROAS alongside stock levels, they identified high-performing items approaching stockout that were generating 4-6x return on ad spend. They prioritized reordering these proven winners and reduced orders for products with poor Shopping campaign performance, improving overall inventory turnover by 22% and reducing capital tied up in slow-moving products.

Create product bundles based on Shopping ad insights

A sporting goods retailer analyzed which individual products received high Shopping ad traffic but had below-average conversion rates. By viewing click and conversion data in their BigCommerce admin, they identified complementary products that customers frequently searched for but didn't purchase individually. They created product bundles featuring these high-traffic items at a slight discount, promoted the bundles through Shopping campaigns, and increased average order value by $34 while improving conversion rate on previously underperforming products.