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MarTech » Data » Key Learnings On The PLA Marketplace

Key Learnings On The PLA Marketplace

Google’s switch to an all-paid shopping search experience, featuring Product Listing Ads (PLAs), was the single largest change to the retail paid search landscape last year, and the offering continues to evolve as the official release of PLAs on smartphones was announced last month. PLAs are not only a new ad format but also a […]

Kohki Yamaguchi on April 11, 2013 at 9:30 am

Google’s switch to an all-paid shopping search experience, featuring Product Listing Ads (PLAs), was the single largest change to the retail paid search landscape last year, and the offering continues to evolve as the official release of PLAs on smartphones was announced last month. PLAs are not only a new ad format but also a new marketplace, with auctions running independently of traditional text ads although they’re often being served alongside them on search result pages.

Now that the new market has had time to mature, we can take the opportunity to step back and review what we have learned about this new marketplace and how it interacts with traditional paid search.

Cannibalization Between PLAs And Text Ads

Cannibalization has always been a concern with PLAs, as they compete against traditional text ads for the same impression and click opportunity. We looked at a month’s worth of search query data across a number of retail advertisers, and found that, on average, 34% of all search queries that resulted in the display of a text ad, also had a PLA displayed. Of search results that had a PLA displayed, 49% also had a text ad displayed. This means that as much as half of volume gained on PLAs may be taken from text ads.

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Unfortunately, there is little that can be done about this overlap. We can compare the parallel-auction system to a poker game that allows each person to play two hands at once: folding one hand decreases competition evenly across all players, so you end up holding the short end of the stick by having only one hand to compete with instead of two.

With this system, retail marketers have little choice but to accept that some cannibalization in inevitable, and continue to enter both auctions to maximize reach and volume. This is especially true since PLAs and text ads have fundamental differences in how they behave, and neither is a complete substitute for the other.

PLA Scalability Is Limited

One major difference is that the scalability of PLAs is limited in comparison to text ads. There are two main reasons for this:

  • PLA impressions are dependent on the inventory you have in your merchant center feed.

PLAs have less impression opportunity compared to text ads in that Google knows your inventory and pricing, which makes your ad unlikely to show for a search query describing an item that does not exist in your feed. For instance, the search query “red boots” is unlikely to show your ad if you only have black or brown shoes in stock, and similarly for “cheap boots” if your inventory is priced higher than competition.

image002

  • PLAs only show for product-related queries, and becomes increasingly likely to show as the product description in the search query becomes more specific.

For example, a search for “shoes” yields plenty of text ads but no PLAs due to the category being too broad. Similarly, “zappos”, an online shoe retailer, shows no PLAs, nor does a search for “nike”, a shoe manufacturer and brand. However, a more targeted query such as “nike shoes” starts to yield PLAs – but still only one or two for any given impression — while a specific product query like “nike running shoes” results in a full block of 5 or more PLAs.

The limited scalability of PLA campaigns is one reason why it is a bad idea to forego text ads entirely, even if PLAs are performing better. In terms of striking the ideal balance of spend between the different ad types, it becomes important to determine how much each PLA campaign can scale while maintaining efficiency.

Spend And CPC Inflation On PLAs

For text ads, marketers typically use average position (ad rank) as an indicator for how much room there is left to scale. However, there is currently no positional information available for PLA campaigns. Though one was temporarily in place last year, Google decided to retract this feature, claiming that they are working on fleshing out a better position calculation for PLAs.

Looking at how average spend share, click share, and impression ratio of PLAs vs. text ads has trended since last summer, we see that impression ratio and click share plateaued in January, while spend share on PLAs continued to rise. In aggregate, we see average CPCs on PLAs with respect to text ads rising almost 18% from December to March, despite there being little change in actual clicks gained. This means that advertisers are pushing spend onto PLA campaigns seeking additional volume that does not exist.

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In search, it is common practice to shift spend towards campaigns that are more efficient, except when the high-efficiency campaign is already bid up to a very high position, in which case any marginal volume can only be gained at a hefty price. The lack of such an indicator for PLAs is likely playing a part in the CPC inflation we see currently.

PLA Impressions Are More Binary

So how do we prevent this inflation? There are several ways to do this, the simplest being to always make sure that increased investment always results in greater click and impression volume as well. If it does not, then you are trying to push more money into the campaign than is optimal.

If we lower the bid on a text ad while competition holds steady, the average position for the ad is almost certain to drop, which in turn decreases click-thru rate (CTR). However, this is not necessarily the case for PLAs: as all ads shown for a given impression is displayed within a block, the effect of display position on click-thru rates are likely to be much smaller. In this sense, PLAs function more like display ads than search ads.

It is possible for Google to influence CTR by varying the number of PLA ads displayed based on the bid distribution, but we do not see this happening at scale: a majority of PLA blocks on desktop devices seem to be delivered either as a 5-ad box in the left column above organic results, or as an 8-ad box in the top right.

This means that for any given product target, once a certain bid level is reached, there may be little benefit to raising the bid further. If you raise or lower your bids on a PLA target and see very little change to impression or click volume, this is a good indication that bids and CPCs can be lowered further to increase efficiency without sacrificing volume.

Takeaways:

  1. Always play both hands, PLAs and text ads, even if one is performing considerably better with respect to the other. Spend can be shifted between the two ad types depending on relative performance, but never put all your eggs in one basket.
  2. When pushing spend on PLAs, make sure to do so only to the extent where you are seeing an increase in impressions and clicks. Bidding up beyond that point will only result in unnecessary CPC inflation with very little incremental volume to be gained.
  3. Be wary about applying the same set of rules or ROI goals to both PLAs and text ads. Scalablility differences mean that the point where their performance converges is not always the most efficient.

Opinions expressed in this article are those of the guest author and not necessarily MarTech. Staff authors are listed here.


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About The Author

Kohki Yamaguchi
Kohki Yamaguchi leads product marketing at Origami Logic, a cross-channel marketing intelligence solution for modern marketers. With a career of 8 years in marketing and analytics spanning various functions, Kohki's focus has always been on translating data into strategy, simplifying the complex, and bridging the gap between data and organizational silos.

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