Google Shopping campaigns offer an intuitive way to advertise your products. Shopping has been out of beta for a few months now and I’ve had great success on the platform.

If you haven’t heard, Shopping campaigns will completely replace PLAs in August. As a result, it is important that you are both prepared to transition as well as manage the new campaigns.

Many of the basics principles will remain as they were. Bid changes and product segmentation will make up a bulk of your optimization strategy. These two methods will get you pretty far along in order to become profitable in Shopping.

There are new features in Shopping campaigns which should provide more granular optimization. What is the best way to take advantage of the new features and squeeze even better performance out of your campaigns?

New Metrics to Watch

Two big metrics were added to Google Shopping from the start. These include both benchmark CTR and benchmark CPC. The naming is straightforward and you can probably guess what they do.

The two benchmarks provide reference numbers for your competitiveness in Shopping ads. The CPC shows the average price your competition is paying. The CTR offers a similar metric, showing how engaging other advertisers’ ads are.

On their own these metrics don’t tell us a whole lot, but they do provide great references for performance. The benchmark CPC offers a great starting point for new product groups. You won’t have to spend nearly as much time finding an acceptable bid. Simply adjust it to the benchmark range and make modifications as needed. Similarly your CTR lets you know how well your ads perform compared to others.

What really makes these powerful is the addition of impression share metrics. Similar to the search side, impression share shows the ratio of ads shown to eligible auctions. By taking the impression share into consideration you can better diagnosis issues and project changes.

Making Use of New Metrics

If your CTR is much lower than the baseline you should take the opportunity to review your shopping feed. Anything from images to product descriptions to product categorization could be holding performance back. Through feed optimization you should be able to bring the CTR back up. Optimizing the feed will not only create more compelling listings but ensure that your ads are showing for the right queries.

Another scenario is a low impression share, even at a higher than average bid. If this is the case, there may be a few advertisers with bids way above the benchmark. Using this metric you know that performance is great at its current level but the only limitation is exposure. You can then proceed to gradually bump up bids until you find the right performance point.

Analyzing Your Products

Now that data is stored at the product level, you can easily tie metrics back to specific IDs or categories. This makes it simple to see which products are driving conversions and revenue and which are struggling.

To see these metrics, go to the dimension tab of your campaign or ad group. Under the “View” menu you’ll see a tab for “Shopping.” The options will let you analyze from the site categories such as product type, brand, item ID and more.

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If you aren’t currently segmenting your products beyond brand or type, this could be a great opportunity to find top convertors to break out into new product groups. Using this strategy you can focus your bids, negative keywords, and benchmarks more specifically to these higher converters, rather than an aggregate of products.

Putting It All Into Action

I recently conducted a test where I segmented a line of shoes from a very popular brand. While every single style has a slightly different purpose, for the longest time performance was so great across the board that they were kept together in one product group.

After launching a large portion of the feed, I went back to segmenting the product groups. I split them into groups by the top-level item IDs. Interestingly enough there were emerging discrepancies amongst the benchmarks. While each group sold well I found one in which the benchmark CPC was much lower than the max CPC I had been using. This means I could have been overpaying on these shoes and could increase the ROAS even higher by slightly pulling back on bids.

I also found another line, which must have had more competition in Shopping. This group now had a much higher benchmark CPC than the previous aggregate benchmark. For those shoes, my max CPC was much closer to the competitors CPCs and I may have potentially started losing conversions.


As anything in paid search your individual strategies and tactics will change from account to account. Hopefully this overview and examples give you a bit of a head start in the mindset you can use to optimize your own shopping campaigns.

Have you found any useful tricks or heuristics for the Shopping campaigns? Or is it still the same old tactics you used in PLAs? Let us know in the comments!