The hol­i­days are a hec­tic time for every­one, espe­cially for retail­ers try­ing to max­i­mize their sales per­for­mance dur­ing this cru­cial sea­son. This year brings an addi­tional chal­lenge (and oppor­tu­nity) with the tran­si­tion from free Google Shop­ping to paid Prod­uct List­ing Ads (PLAs). The for­merly free Google Shop­ping chan­nel has become a major paid chan­nel with a unique set of fea­tures to be mas­tered. With all the chal­lenges in this new space there is great oppor­tu­nity for those who can mas­ter the shift­ing land­scape. Here are some best prac­tices to both sur­vive and get ahead in this new marketplace.

Be There! First and fore­most – you need to be present. The traf­fic that was free through Google Shop­ping is gone, replaced by paid PLAs. So far this paid traf­fic has proven to be a sig­nif­i­cant and prof­itable source of traf­fic. We are see­ing PLAs typ­i­cally account for more than 10% of total search spend with a sig­nif­i­cant upside when fully built out and prop­erly man­aged. The eco­nom­ics to date have also been com­pelling as shown in the table below. To cap­ture as much of this traf­fic as pos­si­ble, make sure you are eli­gi­ble to serve for any search that is rel­e­vant to your catalog.

Early Per­for­mance Gains

Cost per Order Aver­age Order Value Return on Investment

Aver­age Across Advertisers






Be Gran­u­lar: Full cov­er­age is just the start­ing point. The more finely you can match each search to a spe­cific ad (and land­ing page) the more suc­cess you will see this hol­i­day sea­son. Pre­cise match­ing allows you to tai­lor bids to the eco­nom­ics of each search so the traf­fic get­ting served to your site mat­ters most to you.

For exam­ple, if you sell Christ­mas trees, but can­not dis­tin­guish between searches for “cheap Christ­mas trees” and searches for “Christ­mas trees,” you will find your­self pay­ing more for fewer con­ver­sions. If you show an expen­sive tree to cus­tomers look­ing for a cheap tree, they won’t buy it. On the bid­ding side, you need to be able to tai­lor the bid to the expected rev­enue per click. Assum­ing “cheap Christ­mas trees” has a lower rev­enue per click because of the lower order value then you should set a lower bid for these searches. Split­ting the traf­fic also frees you to bid more aggres­sively on high Rev­enue Per Click (RPC) traf­fic. Not only will you gar­ner more high RPC impres­sions, they will have a higher Click-Through Rate (CTR) and take rate with tar­geted ad, image, and copy.

Com­plex­ity should not be a bar­rier to gran­u­lar tar­get­ing. With the right tools and tac­tics, you can eas­ily scale up your account to mir­ror your true busi­ness. A well-built feed and PLA account can cover your whole cat­a­log at the SKU level. Updat­ing bids and cre­ative match­ing across a large account is com­plex, but straight­for­ward if you are using the right tools. For exam­ple, Adobe AdLens, the first uni­fied ad man­age­ment sys­tem for cross-channel opti­miza­tion, uses hier­ar­chi­cal mod­els to man­age sparse data across mul­ti­ple ad units. Lastly, prop­erly imple­mented neg­a­tive key­words will ensure traf­fic is fun­neled to the right ad and offer.

Be Nim­ble: The tran­si­tion from Google Shop­ping to PLAs is very new and there will be a lot of volatil­ity in the mar­ket­place this sea­son. Google is actively tweak­ing their ad treat­ments; vary­ing the num­ber, lay­out and loca­tion of ads on the results page. Many retail­ers are still fig­ur­ing out what PLAs are and how they can use them. As they move in and out of the mar­ket you can expect to see volatil­ity in Cost Per Clicks (CPCs). In this shift­ing mar­ket­place you will need to be able to quickly adjust your bids and tar­get­ing to make sure you can find pock­ets of opportunity.

While you can’t con­trol these exter­nal fac­tors, you can make sure your PLA cam­paigns are closely aligned with your inven­tory and pro­mo­tional activ­ity. If you have a tar­get that is per­form­ing well or receiv­ing increased com­pe­ti­tion, make sure you have enough inven­tory on hand before tak­ing action on that target.

Pro­mote: Make sure your PLA pro­mo­tions line up with any spe­cial pro­mo­tions you have hap­pen­ing. If ‘super toy of 2012′ is in stock and you’re drop­ping the price by 20% this week­end, make sure your pro­mo­tion line says that in it!

This is where gran­u­lar tar­get­ing is par­tic­u­larly rel­e­vant. Price dis­counts and other pro­mo­tions have a huge effect on the eco­nom­ics of a search (higher CTR, higher con­ver­sion rate, lower mar­gin). If Google can’t match your bid and offer to the cor­rect search, you will find your­self at a major dis­ad­van­tage. For exam­ple, if you have just one ad unit cov­er­ing ‘tools-wrenches’ but only one brand of wrenches is on sale, you will be forced to have one bid and one pro­mo­tional mes­sage for both products.

Think holis­ti­cally:  PLAs should fit into your larger mar­ket­ing efforts. We have seen sig­nif­i­cant inter­ac­tion between PLAs and reg­u­lar paid search. Across Adobe AdLens cus­tomers, we have seen more than 15% of pur­chases that start on Prod­uct List­ing Ads later con­vert through reg­u­lar paid search. Know­ing how traf­fic is flow­ing across PLAs, paid search, and other chan­nels allows you to attribute con­ver­sions cor­rectly and allo­cate your mar­ket­ing bud­get in the best way to max­i­mize ROI.

The tran­si­tion from Google Shop­ping to a paid for­mat is a major oppor­tu­nity for retail­ers. This chan­nel has already proven to be very prof­itable in its first few months. With so many retail­ers start­ing from scratch this sea­son, the peo­ple who best scale the learn­ing curve and man­age the com­plex­ity and volatil­ity of this mar­ket­place stand to gain a com­pet­i­tive advantage.

Adobe AdLens makes it easy to build out full cov­er­age of your cat­a­log while sophis­ti­cated mod­el­ing and work­flow allow you to match tai­lored bids and cre­ative to spe­cific audi­ences of searchers. For more details on how easy it is to imple­ment, tag, and man­age PLAs in AdLens, please watch our webi­nar here. Happy Holidays!

Con­trib­u­tors to this blog post include Adobe’s James Varugh­ese, Shay O’Reilly and the Adobe AdLens Ana­lyt­ics Team