Why I Built SKU Analyzer

I have worked with tens of different Google Ads accounts, most of them with some sort of shopping campaigns—either normal Shopping campaigns, Performance Max, or Smart Shopping (R.I.P.). One thing has always been constant when I analyze results or try to optimize and grow these accounts: getting a good picture of product performance, especially on larger product catalogs, is an absolute nightmare.

The Google Ads UI Problem

Google Ads UI is absolutely horrible for analyzing product-level data. You can usually see just one table with summary data and one or two metrics. Not visually pleasing, but more importantly, not optimal. It makes understanding product/category trends really hard, comparing is impossible.

Splitting by product types, custom labels, brand, or any other segment is hard. Comparing different segments is also hard. Recognizing what products and categories are working, what should be scaled—all possible, but requires manual work and is slow.

Google Ads custom reports and Looker dashboards definitely help, but they are very limited as well. They also show just Google Ads data, and some scopes are limited. Looker dashboards have their own issues when you have enough data. Taking data to something like BigQuery through APIs and from there visualizing it somewhere is plausible, but requires a lot of work and know-how.

The Merchant Center Disconnect

Google Ads API is one thing, but then there's the other side: Merchant Center and the data it offers. There is so much useful information—from the product feed itself to competition benchmark prices per product and beyond. These are COMPLETELY SEPARATE, so taking use of both is not possible, except checking one first and the other after that.

Merchant Center has a very basic Google Ads connection, but the data visualization is abysmal there—just one summary table of imported conversions from Google Ads. So again, in theory it is possible to connect data sources. In practice, not really. Going through the competition pricing benchmarks in Merchant Center UI is also painful.

What I Actually Needed

So I wanted a tool that:

• Combines Merchant Center data (product feed, all variables, competition price benchmarks, etc.) with Google Ads shopping performance data (cost, clicks, all conversion metrics, impression share, etc.)
• Allows me to easily visualize product-level Google Shopping ads performance data in different formats, and most importantly allows me to filter the data based on ANY feed variables (not just those that Google Ads UI allows you to use)
• Allows me to cross-analyze this data: Is a product selling better because our prices are lower than competition on average? How much of the shopping ads market do we have in terms of impression share? Can we scale this product or category further?

The Search for an Existing Solution

After putting three different AI tools on deep research mode to find me this sort of service I could buy, and all of them coming empty-handed, I realized I need to build my own.

There are many feed management tools like Channable and Producthero, and analytics middleware like Supermetrics (I'm a big fan and user of many years). None of these really fit the bill in terms of the tool I was looking for. I wasn't looking for a product feed labelizer or feed management tool. I wanted a reporting platform that helps me make sense of product-level performance data.

SKU Analyzer

So SKU Analyzer was born. Generic and boring name, I know, but in my defense: a) it describes what the product does, and b) it started as a placeholder name and then before I realized it, I was too far into building. Switching takes too much effort, so SKU Analyzer it is.

This landing page and website contains enough videos, images, and info on the dashboard features, so I won't go into detail here. I will just say that this was born out of my own frustration with the difficulty of analyzing shopping ads, which in ecommerce context are often the backbone of any Google Ads account—and thus, huge budgets are allocated to these campaigns.

It is crazy to me that shopping campaigns that companies spend huge amounts of money on are so hard to really analyze properly. My hope is that my tool helps advertisers optimize their own campaigns better to improve ROAS, CPA, or whatever metrics you are aiming for.

—Samuli