DRPD Automates and Optimizes Ad Feeds with Feedonomics Surface

SOLUTION

Automating feed build and data synchronization.

To start, Feedonomics Surface provided the automation that DRPD needed to improve its feed performance and streamline operations.

In a matter of clicks, Retrum was able to connect his BigCommerce store to Feedonomics Surface, rely on Surface to automatically build a feed for Google Shopping, and sync his products to the Google Merchant Center. All of this was possible without changing his source data in BigCommerce.

"Feedonomics Surface just figures it all out. And I just think about all the hours that we wasted trying to map all that stuff in the past," Retrum said.

With automated syncing, sellers can keep inventory, prices, and stock availability up-to-date across channels, which means customers can trust the ads they’re seeing.

Optimizing data with custom transformation rules.

For a retailer whose customers often search by specific part numbers, ensuring product data is clean, precise, and platform-ready is essential.

Surface introduced a powerful layer of customization through its transformer tools. Retrum used these to clean up part number formatting, optimize product titles, and ensure variant data matched platform requirements.

With Feedonomics' transformer functionality, DRPD could manipulate data at a granular level — such as removing comma-separated European part numbers from the Google size field to prevent feed errors. 

He also optimized product titles for each variant, going beyond the platform’s default formatting to ensure consistency and clarity. These transformers proved especially valuable given DRPD’s catalog structure. Instead of listing 30 nearly identical socket variants as individual SKUs, DRPD uses a single parent product with child variants — creating a more professional, shopper-friendly experience. 

“Having the transformers available to go in and manipulate titles was super helpful,” Retrum said. “Feedonomics has really helped us organize those variants in a way that lets us leverage the UI benefits on the shopping side.”

These kinds of flexible adjustments let DRPD tailor product listings to each channel’s exact formatting requirements without changing the underlying BigCommerce data. Retrum described it as “the best of both worlds” — automated syncing to the BigCommerce data source paired with powerful, hands-on control to make adjustments.

Simplifying error resolution through a centralized dashboard.

One of the most immediate benefits DRPD saw from Feedonomics Surface was the ability to quickly identify and resolve feed issues. Before Feedonomics, errors in Google Merchant Center often went unnoticed. Without a centralized view, issues like missing SKUs or invalid UPCs can quietly degrade ad performance for weeks or longer.

Feedonomics Surface changed that with its centralized error dashboard, which consolidates all feed issues in one place. The dashboard doesn’t just display errors; it organizes them by type and frequency, allowing DRPD to prioritize fixes based on the number of affected products. When the same error appeared across dozens of listings, Retrum could investigate and resolve the root cause quickly, saving time and preventing future data disruptions.

“The level of confidence we have now that the data is clean is great, because you’re spending money on advertising, and you’re relying on that data,” said Retrum. “If the data is garbage, you’re going to get garbage results.”

Retrum found it extremely effective in surfacing data issues — not just in the feeds, but in their BigCommerce catalog as well. The visibility prompted DRPD to clean up core data that had previously gone unflagged, improving the quality of both their ecommerce store and their advertising feeds.