For merchants with thousands—or even millions—of SKUs, merging multiple data feeds is more than a convenience; it’s a necessity. Large catalogs demand constant updates to pricing, stock levels, and performance metrics across dozens of sales channels. Manual adjustments simply can’t keep pace. By combining data from inventory systems, analytics platforms, and marketing tools into a single, unified feed, marketers gain real-time control and the agility to scale campaigns without sacrificing accuracy. This makes advanced tactics such as automated repricing, margin-based bidding, and dynamic best-seller segmentation not just valuable but essential for staying competitive.
Large retailers and marketplaces often need extra flexibility—such as advanced automation, custom workflows, and dedicated support—to keep very large catalogs synchronized across multiple channels. If you’re exploring options for this level of scale, you can learn more in the DataFeedWatch for Enterprise overview.
If your data feed contains product data like gross margin, stock, cpc or price-rank, you can optimize your ppc-campaigns very effectively. Merging various sources into one feed enables you to achieve exactly that!
Data driven online marketing
Like most marketing efforts, online marketing is increasingly becoming data driven. Unfortunately the data that you would like to use is never available with the touch of a button.
However, when you put enough attention to your data integrity, you can enrich your data easily and optimize your online marketing efforts.
DataFeedWatch offers you the possibility to merge numerous feeds together containing product data from different sources or more interesting containing additional information about your products.
Optimize bids by margin
There are quite a few sources that you could use to add relevant information to your product data. Let’s start with your purchasing data or sales administration system, it contains all information needed to generate information like margin by product or product group.
Enriching the data of your product input feed offers you various ways to optimize your campaign performance.
For example by adding custom labels based on margin categories to your Google feed and use them in your Google Shopping campaigns to set more optimal bids.
Stock accuracy
The availability of current stock data is essential for successfully operating an eCommerce business. The growing number of marketplaces and other channels selling your products make it even more important to organize your stock data flow.
Merchants often use a Product Information Management system (PIM), ERP or other tool that contains their stock data.
Merging this data with your product data feed and updating your output feeds multiple times a day offers you the ability to instantly stop advertising products with insufficient stock levels and vice versa start selling products that are back in stock.
Stop advertising products that are (nearly) out of stock saves you CPC but more importantly prevents from having disappointed customers.
Repricing
Being successful in the hunt for the online consumer is primarily based on offering the right price. Repricing is a very important tool, especially for retailers selling comparable products in a competitive environment.
Merchants often use a third-party tool to monitor and update prices based on current competitor data.
Merging repricer data offers various opportunities. For example, excluding all products that have a price rank > 3 and therefore are not among the 3 cheapest, and include them again when their price rank improves.
Or include all products if competitor A, B or C is out of stock. And if your price-data is coming from the repricer-app instead of directly from your shop, merging enables you to add the most current price data to your feed.
Dynamic Best-Seller Segmentation
A great example of the power of merging multiple data feeds is the dynamic best-seller segmentation strategy, as shown in this video by Austin Becker. It demonstrates how combining product feed data with sales performance can create fully automated, data-driven campaigns.
Here’s how it works in four simple steps:
- Import Active Item IDs – Pull only live product IDs from DataFeedWatch (e.g., daily at 2 a.m. Eastern).
- Import Revenue Data – Collect the last 30 days of revenue from Shopify, Magento, or GA4 (via tools like Adveronic or Supermetrics), usually around 4 a.m. Eastern.
- Assign Best-Seller Rank – Use formulas in a lookup table like this one: Best Sellers Rank Lookup Table (thanks to Austin Becker) to label products as “top 10,” “top 25,” or “top 50,” based on their revenue compared to other items.
- Apply Custom Labels – Import the ranks into a custom feed attribute (e.g., custom label zero). The feed management tool (like DataFeedWatch) then automatically segments products for campaigns on Google Ads, Meta, and more.
Integrating this method with Google Sheets adds even more flexibility. You can filter, sort, and apply formulas to quickly identify top-performing products, giving you real-time visibility and control over your segmentation. Combined with automated ranking and feed merging, this creates a powerful system for targeting the right products to the right audiences and optimizing ad spend.
Why this sheet is useful:
- See exactly how item IDs, revenue, and ranks connect in real time.
- Easily adjust thresholds for “top 10” vs. “top 25” as needed.
- Turn a complex, technical process into something actionable and manageable.
Summary
Merging multiple data feeds transforms scattered product information into a single source of truth. Whether you’re optimizing bids by margin, keeping ads in sync with real-time stock levels, reacting instantly to competitor pricing, or running advanced strategies like dynamic best-seller segmentation, the ability to unify and automate your data is what allows large and small merchants alike to scale efficiently. By centralizing these feeds, you reduce errors, save time, and ensure that every ad dollar targets the right product at the right moment.
