Don't drag your feet on upgrading to Google Shopping Campaigns. Once you've upgraded to the new system, you'll wonder why you didn't do it sooner.
Product Listing Ads (PLAs) have been a big hit for Google since the program's rollout in October 2012. In Q4 2014, PLA spending accounted for more than 20 percent of Google's paid clicks, according to numerous studies. Retailers have jumped on the PLA bandwagon because the ads work; according to Internet Retailer, PLA click-through rates (CTRs) are 47 percent higher than for ordinary text ads on Google's properties. I can tell you that my own clients using PLAs have seen very favorable return on investment (ROI), which is always good news.
At the same time, however, the people - at agencies or on e-commerce in-house teams - who manage PLAs on a day-to-day basis haven't exactly had an easy time of it. One big complaint has been the relative lack of transparency into the feed powering PLAs - some have called it "another black box" because metrics have only been available at the Campaign/AdGroup/Product Target levels. Another has been a somewhat confusing integration of PLA reporting data within the AdWords user interface (UI). The result is that managing and optimizing PLA campaigns has been a lot more difficult than it ever needed to be, and person-hours are wasted on setup time that could be better allocated elsewhere.
Here's the good news: In April, Google announced that Google Shopping Campaigns would replace the old-style PLA management system, with final switchover to happen in August 2014. This is great news for a number of reasons:
Shopping Campaigns let e-commerce merchants browse their inventory in one convenient place, right within the AdWords UI. Product Groups are the basic organizational units that segment the PLA data feed into meaningful categories. You can create Product Groups for your highest revenue-generating products, products you want to promote, or even down to the individual SKU unit level. This kind of multi-dimensional view of inventory provides very granular bidding, reporting, and opportunities for optimization. Not only does it make PLA management as straightforward and intuitive as managing a regular paid search campaign; it allows e-tailers to view ad performance in a language meaningful to them.
Custom Labels are a new, helpful feature allowing e-commerce merchants to easily assign identifiers for special categories of inventory, for example, seasonal clearance products, best-selling products, etc. Shopping Campaigns provide up to five custom labels with specific assignable definitions. Custom Labels will replace both the "AdWords Label" and "AdWords Grouping" descriptors used in old-style PLA campaigns. These labels do a lot to make PLA management less mysterious, more intuitive, and easier to cope with.
It's been difficult in the past to benchmark PLA performance, but Shopping Campaigns includes a bid simulator that lets campaign managers evaluate performance relative to their competitors. The Shopping Campaigns bid simulator collects data from the past seven days, and - provided that there was sufficient auction activity in this period - will let marketers predict the impact of bid changes on clicks, costs, and impressions.
Search marketers have, for years, known that setting up multiple campaigns can provide additional targeting flexibility. Shopping Campaigns provides a way to prioritize certain campaigns over others. By default, all Shopping campaigns are assigned an initial value of "low," so if a given product appears in multiple campaigns the bid price alone will determine which listing enters the auction. Assigning a higher campaign priority will override the bid price. Google recommends "prioritizing only a subset of the products you want to promote, such as items featured in a special sale, by combining a higher campaign priority with an inventory filter (which limits the products in your inventory available to the campaign)."
Google recommends a number of steps to upgrade from old-school PLA management to Shopping Campaigns. First, make sure that the data in your feed is suitable for creating meaningful Product Groups. Google recommends that "when reviewing your feed, consider how your product attributes, particularly product type and category, allow you to group and bid on products." Also, if you've been using "AdWords Labels" or "AdWords Grouping" attributes in your campaigns, you'll need to replace them with logical Custom Labels. Other attributes (for example, brand, product type, category, etc.) can be used to create appropriate Custom Labels.
The new system may also make it easier to test the impact of different pictures/images on feed performance. PLAs feeds have their own quality score and a better (more enticing to searchers) image will help your ad trigger at a lower bid.
Don't drag your feet on upgrading to Google Shopping Campaigns - Google is pulling the plug on the old system in August. And the earlier you can get your old campaigns upgraded, the sooner you can begin testing its advanced features. My prediction is that once you've upgraded to the new system, you'll wonder why you didn't do it sooner.
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Kevin Lee, Didit cofounder and executive chairman, has been an acknowledged search engine marketing expert since 1995. His years of SEM expertise provide the foundation for Didit's proprietary Maestro search campaign technology. The company's unparalleled results, custom strategies, and client growth have earned it recognition not only among marketers but also as part of the 2007 Inc 500 (No. 137) as well as three-time Deloitte's Fast 500 placement. Kevin's latest book, "Search Engine Advertising" has been widely praised.
Industry leadership includes being a founding board member of SEMPO and its first elected chairman. "The Wall St. Journal," "BusinessWeek," "The New York Times," Bloomberg, CNET, "USA Today," "San Jose Mercury News," and other press quote Kevin regularly. Kevin lectures at leading industry conferences, plus New York, Columbia, Fordham, and Pace universities. Kevin earned his MBA from the Yale School of Management in 1992 and lives in Manhattan with his wife, a New York psychologist and children.
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