Why Doesn’t Google’s Shopping Campaigns Whitepaper Mention Item-Level Targets?
Google’s recently released whitepaper outlining recommendations for the soon to be mandatory Shopping campaign model offers up best practices for feed optimization, campaign structure, bid management, and mobile strategy. This comes ahead of the scheduled transition from Product Listing Ad campaigns to Shopping campaigns as the default product ad campaign model at the end of August.
While there’s plenty to dissect in this whitepaper, I found it interesting that Google chose not to mention item ID level targets at all in their structural recommendations.
Instead, advertisers are encouraged to group like items together into broader targets for easier management, and find ways to divide these groups further if they find that one or two targets are garnering all of the traffic. No mention of breaking out high traffic products into ID level targets.
Even for well-performing products, Google recommends that advertisers group these together to bid them differently as a whole, rather than break them out individually.
Considering item level IDs are the most granular possibility for bidding and performance tracking, it stands to reason that advertisers should want to make use of these targets in Shopping campaign strategy. So why no love?
ID Level Targets Have Had Their Issues in the Past
As many marketers who have been studying PLAs over the past few years have recognized, Google’s PLA serving practices have not always been the most logical. One consequence of this has been that the old model typically saw reductions in traffic and performance when trying to target all products through ID level targets, with some case studies published to this effect. This resulted in best practices that utilized a hybrid approach of targets varying in granularity.
Part of the reason we believe Google had these issues is that they were tracking history (and thus, quality) at the target level, such that new targets had a harder time getting off the ground than older, more established targets with history.
In the new Shopping campaigns model, however, this issue should be solved as performance history is supposed to be stored at the product level, giving a product its own history independent of the target it gets served through.
Our hope is that this means ID level targets can be launched in bulk in the new Shopping campaigns without the same issues that plagued such attempts in the past, which would allow us to bid at the most granular level possible.
With RKG’s Adaptive Portfolio Bidding® technology, we’re able to handle calculating bids for product targets on our side of things, even when they don’t have significant data to be bid on their own. This makes grouping products into broader targets unnecessary for effective management.
Early tests have shown that launching all item level targets from a category seems to result in approximately the same traffic levels as launching just a category level target at the same bids. This is good news for advertisers and agencies looking to utilize the most granular targets, and apply greater bidding segmentation, but we are continuing to test to ensure there are no negative performance consequences to campaign structures that rely heavily on item ID targets.
Hoping for the Best with Shopping Campaigns
While Google has been slow in providing API and bulk editing functionality for the new Shopping campaigns, we’re hopeful that this update will result in more consistent target serving as well as the possibility for greater use of ID level targets. That Google fails to mention such targets in their structural recommendations seems odd, and is hopefully not an indicator that the same issues that abounded in older PLA campaigns will persist.
As with all Google product releases and updates, only rigorous testing can ensure your Shopping campaign structure is optimized and delivering your account as much out of the product ad format as possible.