3 Opportunities With Those New Google Shopping Campaigns

For those who are not necessarily familiar with Google Shopping campaigns — let’s clarify things straight away.

Product listing ads (PLAs) are remaining the same as an ad format for end users, whether search marketers are using “old PLAs” or new Shopping campaigns.

The novelty lies only on the campaign management side of things, including a layering system based of the Google Merchant Center feed directly in AdWords. But in my mind, some of the new Google Shopping features should have a significant impact for both advertisers and end users – here are a couple of initial thoughts.

1. More Control Over Search Query To Product Mapping

Your PLA campaigns will get simplified only after reorganizing your PLAs within the new Shopping campaign world.

While Google will provide a tool to transition from old PLAs to new Shopping campaigns, you’ll definitely want to review the new structure carefully to make sure you are leveraging all new features coming along with those Shopping campaigns.

Besides the look and feel in the AdWords interface, there are mostly two new features that I would like to shine a light on.

First of all, the way those catch-all product targets behave is changing. As Google says:

If an original ad group doesn’t have an “All products” product target, the ad group in the new campaign will be created with an excluded product group for “Everything else.”

In other terms, the new “Everything else” product targets should not overlap specific product targets, which should help mitigate intra-account cannibalization. This is a big change.

(Click to enlarge.)

(Click to enlarge.)

Secondly, you are now able to set campaign priorities from to “Low” to “Medium” to “High,” which should theoretically force query mapping. The time when you had to bid up to receive impressions across specific product targets might very well be over — at least in theory.

Layered on top of an intelligent use of those new catch-all targets, priorities can potentially help address the overlap issue, although one should not need priorities as long as your Shopping campaigns are mutually exclusive.

Also, note that negative keywords for PLAs are not going away, fortunately. They should still be crucial in general, but you should no longer have to worry about cross-product competition, and you can instead concentrate more on regular search query filtering.

So altogether, online marketers are getting much more control in terms of what ads are being served, thanks to those features that help address the overlap issue.

2. Improved Product Mapping Involves A Shift From Head To Tail Products

Because of the above reasons, search marketers should be able to serve better ads to end users. More specifically, here are a couple of effects online marketers can anticipate:

  • Because of the mapping issue being addressed — at least theoretically — marketers should be able to serve more specific ads with more specific promotion lines related to more specific queries.
  • If you are using the new Shopping structure correctly, you should expect a shift from a couple of generic product targets and the current “All Products” product target to more granular, long-tail product targets and those “Everything else” product targets. This should help with both the average click through rates and conversion rates due to improved relevancy in general.
  • Since every layer of product targets needs to have an “Everything else” product target, you’re likely to get more impression volume if you didn’t already have a catch-all ad group. That could be a hit or a miss, and you’ll want to make sure your “Everything else” product targets are doing what they are supposed to, i.e., catching incremental queries, as opposed to stealing impressions from the rest of the account.

As a result, one can expect an overall increase in impression and click volume due to those new ‘Everything else’ targets. And from a marketplace standpoint, one can reasonably expect increased cost-per-click levels since more advertisers are likely to show their entire product catalog due to the ‘Everything else’ product targets being active by default across the board.

3. Bidding On PLAs Is becoming More Complex & Long-Tail Heavy

Because of the expected shift from a few head product targets to many specific product targets as described above, building data models for PLAs can also be anticipated to get more sophisticated in the near future. So, if the new Google Shopping features work the way they should:

  • There will be more product targets with some cost and revenue data, hence more bid decisions to be made overall.
  • More product targets will have a limited amount of data, making it more relevant to be able to borrow data from other product targets in order to use statistically significant data models across the board.

Long story short, there is definitely a challenge ahead of search marketers in order to best leverage increased PLA data granularity, and this is something we see as an opportunity at my company as we are used to building sophisticated data models in a complex auction-based environment.

Conclusion

What seemed to be mostly an AdWords interface update in the first place might turn out to have significant effects on the PLA environment. More consistent product mapping should improve overall ad relevancy and user experience, and potentially increase traffic quality, too.

But online marketers will only take advantage of those new Google Shopping campaigns if using the appropriate campaign structure and bidding solutions out there. To be continued…

Opinions expressed in the article are those of the guest author and not necessarily Search Engine Land.

Related Topics: Channel: Retail | Google | Google: AdWords: Product Listing Ads | Google: Google Shopping | Paid Search Column

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About The Author: is a Business Analyst in the Digital Marketing team at Adobe, providing advertisers and account management teams with data-driven and actionable insights on strategies to optimize their online marketing mix. One of his specialties is to develop tools and simulators for analysts to use, and executives to use for making business decisions.

Connect with the author via: Email | Google+



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