• MerryWhy

    Hey Ginny,

    The link is broken here, but great stuff!

  • Ginny Marvin

    Fixed! Sorry about that.

  • MerryWhy

    Thanks, you are awesome! Excited to hear what strategies people are using on PLAs!

  • Sam Mazaheri

    Ya, I’d love to hear everyone’s opinion on this debate

  • Doug

    As a product photography strategist I do find value in A/B testing the images of identical products using specific groups, but generally once a particular style of photo is working I group the number of related products accordingly.

  • http://www.rimmkaufman.com/ George Michie

    We manage more PLA spend than any other agency. We find that there is no one-size-fits-all approach that maximizes performance. Product level ad groups work best for some advertisers. Some benefit from more aggregated groupings. The mistake people make is “set it and forget it.” You have to test different targeting strategies to find what works best for a particular account.

  • Mark Roudy

    I am already running my campaign in the same path….Thanks

  • d_a_t

    Were the old targets simply paused when they launched the new Prod ID targets? In this case, you would expect to see a drop off in performance as the new targets have no history and thus less quality in Google’s eyes. By reactivating the old targets, which is what I assume happened in the recovery phase, you get all of that history back. Thus, this could just be a case of the older targets performing better because they’re older, not because using Prod IDs doesn’t work.

  • Hamid Saify

    It’s a similar approach that was used for keywords in the mid 2000s. One keyword per ad group, match type, most relevant creative. Of course, that become a nightmare to manage & with matching updates, unnecessary. But, the proof here is what? One case study, for one client, in a highly specific vertical. I’d hardly call that case study material refuting a strategy. But well played, I read it.

  • http://cpcstrategy.com/ Josh Brisco

    It is the product IDs, GTIN and general data feed information which carry the product relevancy and not the targets. In taking over many existing campaigns and building out a new one from scratch with new product targets, I can say that there is usually little to no negative change in performance with the new targets in place.

  • http://www.cpcstrategy.com/ Rick Backus

    George – I 100% agree and this is exactly what we say in the guide (excerpt below):

    “As with all online advertising there is not one strategy that guarantees optimal results in every case. smart retailers looking to get the best return on their ad spend understand the importance of testing and evaluating multiple strategies.”

    The point of the guide was to debunk the myth that SKU level build outs are the most sophisticated way to manage a PLA campaign. It’s all about getting the client the best ROI possible and if the ONLY strategy is a SKU level build out, you’re doing it wrong.

  • http://www.cpcstrategy.com/ Rick Backus

    @hamidsaify:disqus that’s a fair critique and I could see how you could feel duped. The data in the guide is only for one of our clients but we manage over 30 million a year in ad spend across 200+ clients and we have seen this trend across the majority of our clients. We should have made that evidence more clear in the guide.

  • d_a_t

    Product relevancy does lie in the data feed, but quality score does not. Having seen specific instances of product IDs being launched at significantly higher bids than broader targets with more history, yet the broader target continues to get all of the traffic for that product (we database the final destination of every click to match up what products are served through broader targets), indicates to me that Google does assign some sort of quality score to the target itself based on history. Otherwise, why would they serve the broader target with the lower bid?

    Also, your study’s conclusion is that launching all of these product IDs did hurt performance, which seems in contrast with what you’ve just said, ‘that there is usually little to no negative change in performance with the new targets in place.’

  • Lucas von Fürstenberg

    With an ever changing product inventory I see value in grouping SKUs by category and brand. Especially when going as granular as having separate targets for every size available, grouping them together ensures that Google at least has some idea as to how a target might perform. Otherwise you may end up with very little data per adgroup.