With product listing ads (PLAs) now accounting for 30%-50% of paid search budgets, retailers must implement the right management and growth strategy in order to grow profitably. In this complimentary report, you'll learn five ways to grow your Google Shopping program. You'll also see how two retailers were able to achieve triple-digit growth in click-through rates, conversion, and revenue by implementing these tips.

1. FIVE KEYS TO
PROFITABLE
GROWTH WITH
GOOGLE SHOPPING
GOOGLE SHOPPING REPORT

2. The way consumers shop is changing. Gone are the days when a marketer had to run a simple radio
or television placement to convince a person to buy a product. Today, consumers have access to more
information than ever before. In 2011, the average shopper reviewed 10.4 pieces of information before
making a purchase decision1
. More and more shoppers are gathering this information online. But where
do they start their online research―a retail site or a search browser?
A Battle Begins
There is a quiet battle taking place for online retail dominance. Google’s top priority is to be the leading
destination for online shoppers while providing an exceptional customer experience, but Amazon has
proven to be a popular starting point for many online shoppers. In 2009, 24 percent of shoppers started
research for an online purchase on a search engine, while 18 percent started on Amazon. But in three
short years that trend has shifted. In 2012, 32 percent start on Amazon whereas only 13 percent start on
a search engine. The introduction of Google’s Product Listing Ads is no doubt a response to Amazon’s
visually appealing product search format on their site. While retailers are seeing good performance results
from Google’s new advertising opportunity, it is too early to tell who will win the battle for market share.
Where Shoppers Are Starting
2009
24% Search Engines
18% Amazon
13% Search Engines
32% Amazon
2012
1
Google, 2011
Google’s Latest Competitive Move
Google Product Search™ was a free service that retailers with a Google Merchant Center account could
leverage. In order to be successful, the most a retailer had to do was establish a clean product feed,
which they subsequently sent to Google. There was not a significant focus on optimization, which
often resulted in unorganized and inappropriate advertising. This caused it to lack the relavancy that
allowed Google’s pay-per-click (PPC) text ads to be so successful. Google determined that there was
value to this free service and decided to rebrand and productize the offering. What was once Google
Product Search became Google Shopping™, a pay-for-play picture ad service.

3. With the introduction of Google Shopping™ comes opportunity. Retailers have a new resource for
customer acquisition and improving market share, with a degree of control that was never offered by
Google Product Search. But simply participating in the program does not guarantee success. Retailers
must apply PPC best practices to their PLA program and continue to test, optimize, and learn.
There are many best practices that you can use to guide your PLA program, but there are five that have
proven to be the most valuable to Adlucent retail clients. In this report, you will see how retailers like
BabyEarth and Adorama have applied these best practices and the resultant performance gains they
have seen.
Many retailers work with a feed management company to maintain a clean product feed. This feed
contains a detailed list of products that a retailer offers. This feed is incorporated into a variety of Google
services and must adhere to specific formatting that is dictated by these services. Feed management
companies ensure that product feeds meet these specifications, but do not have the knowledge or
incentive to continually adjust feed information to help optimize a PLA campaign. This results in a
missed opportunity for retailers.
Adlucent views feed management through a PPC lens, and understands the impact that adjustments
to product feed attributes such as product titles and descriptions can have on their advertisements.
Through continuous testing, monitoring, and adjusting, Adlucent can ensure they show the most
relevant ads to potential customers. This, of course, leads to less wasted spend and higher conversions.
It is also important that a retailer’s product feed is regularly updated with new information. Adlucent
uses this information to create PLAs for products newly added to the feed, and can aggressively
promote them to gather data and decide the best strategy for optimization. Additionally, they can use
inventory data to understand whether or not the retailer will benefit from pausing and activating PLAs
based on their products’ availability, and employ the most effective strategy for that particular retailer.
The retailers who will be most successful with PLAs are the ones who continuously maintain and update
their product feed and use the resulting performance data as the basis for future optimization and
upgrades.
Five Keys for Profitable Growth with Google Shopping

4. Successful PLA strategies employ micro-segmentation. Micro-
segmentation is analyzing advertisements’ performance at a variety of
broad or granular levels: categories, subcategories, product lines, model
numbers, SKUs, brands, etc. Retailers must be able to identify and analyze
these related segments of their product feed to create their PLA targets
and ensure maximum exposure for their ads.
At the broader, aggregate level, Google will deliver ads based on a large
group of products. For example, a PLA target created for a category such
as “televisions” would potentially be triggered by any searches related to
televisions. These broader groupings increase the number of captured
queries and therefore, traffic and revenue.
When you group products at a more granular level, you are able to connect ads to more explicit intent,
indicated by searches for specific products. For example, a PLA target created for a specific television
SKU would be trigged most often when a search query matches the particular SKU number, or specific
information located in the product title or description in the product feed for the SKU. The traffic will be
lower, but it will also be more qualified as it funnels customers to the most relevant product.
So which option will work best for you? It depends on your business. Start by testing related groupings to
see which strategy yields the best results against your program goals. Often, a combination of broad and
more specific product targets will result in the best balance in traffic and efficiency.
Micro-segmentation in Action: A Look at BabyEarth
Founded in 2003, BabyEarth is an online retailer that sells products for
newborns to children three years of age. BabyEarth has grown organically
over time, but they have also invested heavily in paid search to acquire
customers at a faster rate.
BabyEarth began running PLAs in August 2011, but quickly became overwhelmed by trying to manage
bids for over 10,000 SKUs. In addition to managing a high number of products, the in-house team
found it difficult to optimize ads and acquire granular reporting when working directly with Google and
CATEGORY
SUBCATEGORY
PRODUCT LINE
MODEL
SKU

5. other AdWords plug-in solutions. Managing to margin was a critical component of their goals, but they
were unable to effectively incorporate margin into their bidding strategy. With all of these challenges,
BabyEarth decided to seek out a partnership with a retail-focused paid search agency for both their PPC
and PLA programs.
BabyEarth selected Adlucent as their search partner in order to grow revenue while maintaining their
cost of sale. Initially, Adlucent started by expanding the PLA targets from less than a hundred to over
10,000, and this number has since grown to over 22,000. These targets include brands, categories, and
combinations of both, as well as grouping together related SKUs or SKUs that represent different styles
of the same product.
Getting Predictive
A key factor to the program’s success is predicting which products will perform over time. The concept
of predictive bid management requires retailers to create segments that will provide enough information
to make an informed decision. There are a variety of ways retailers can go about this. In the case of
BabyEarth, Adlucent started by comparing product level data and metrics from both paid search and
PLAs. Next, they reviewed search queries from PLAs and text ads to determine customer intent. Finally,
they looked at best-selling products, brands, and categories. All of this data helps predict which targets
to emphasize and the bid management strategy required to achieve the greatest return. Adlucent was
able to move targets that were predicted to perform well into a more aggressive position at both the
SKU and a related level as well as minimize uncompetitive advertisements.
Managing to Margin
Adlucent has also incorporated margin goals into BabyEarth’s overall management strategies for PLAs.
This means BabyEarth is aggressively promoting the products that provide them with the most value,
resulting in sustainable growth for their paid search program as a whole.
Explosive PLA Growth
129%INCREASED AVG.
REVENUE/MONTH
BABYEARTH PARTNERS WITH ADLUCENT
NEW TARGETS
10,000
Ensure you have
a clean data feed
Fill out all relevant
product information
Determine which products
you want to show up and feed
them into Google targeting
1 2 3
3 Tips for Product Listing Ads from BabyEarth CMO Steve Steinberg

6. Revenue
2011 vs. 2012
Conversion Rate
2011 vs. 2012
Click-through Rate
2011 vs. 2012
Google’s Product Listing Ads are a complementary media type to search text ads and a natural
extension of the core paid search program. As such, both programs can be used to influence one
another. Product-related keywords and queries that have been successful in your PPC program may
translate well into PLAs and vice-versa. Continuous search query mining and expansion of coverage
are critical to PLA growth.
Using PPC to Influence PLA Performance: A Look at Adorama
Adorama is one of the nation’s largest photo retail and mail order suppliers,
supporting both professionals and amateurs in the photographic, video, and
digital imaging field for over 35 years.
Adorama began investing in paid search in 2003, and teamed up with Adlucent to drive greater
performance. In mid-2011, Adorama added Product Listing Ads to their search portfolio. Adlucent
applied micro-segmentation to Adorama’s PLA program, using analytics and performance data from
search text ads to determine which product ads would be successful based on product performance
and consumer intent. By utilizing this data, Adlucent was able to quickly launch Adorama’s PLA program.
With the knowledge of top performing products, Adlucent is able to adjust bids at a product level and
to optimize columns in the feed to maximize performance. The resulting revenue driven from improved
performance and efficiency has enabled Adorama to continue investing in their PLA program.
Adorama Doubles Conversion Rates Efficiently
In just one year, Adorama’s average click through rate has increased 176 percent and their conversion
rate has increased 100 percent, all the while outpacing spend, which was held at 73 percent YoY
growth. PLA revenue grew 63 percent from Q1 to Q2, and continues to trend upward. By utilizing
Adlucent’s click funnel analysis by channel, Adorama has found that PLA clicks impact nearly half of
their overall non-brand revenue.
100%176%
63%

7. It is important for retailers to make informed investment decisions. For paid search, this means
putting dollars to their best use on the top performing advertisements and optimizing the feed so that
PLAs match customer intent. Retailers can mine customer search queries to find which queries are
converting on both the aggregate and granular PLA levels. Target matching these should be pushed
aggressively in a bid management system and, if necessary, more targets should be launched in order
to drive the most quality traffic to the retailer.
Just as it is important to mine queries for those that are successfully converting, special attention
should also be paid to search queries that are not performing well. These include queries that
are being matched to the wrong target or that have very little chance of converting. For example,
BabyEarth was receiving a significant amount of traffic for the term “elmo”—as a result of a variety
of Elmo themed products―but the traffic was not converting. This query was quickly identified and
negated from the account and spend was redirected toward keywords that were driving revenue within
their margin goals.
Retailers must continually mine queries in order to control their investment and to ensure dollars are
directed toward the advertisments that will deliver the best return on their investment.
Aggregate Targeting Precision Product Matching
Good Performing Product
Poor Performing Product

8. Product feed optimization begins with adjustments to product titles and descriptions, which are used
by Google to match advertisements to queries. But there are a variety of other optimizations that can
significantly improve performance for retailers.
Retailers can leverage their landing page strategy from text ads for their Product Listing Ads. They
should design and test various landing pages on a product-specific level to determine what converts
fastest. If possible, landing page testing automation should be leveraged so that tests end and winning
landing pages are fully implemented as soon as there are statistically significant results.
Google also allows promotional text and promotional pricing in the feed. Promotional text in PLAs
is not always shown, but when it is it can be used to display competitive advantages such as free
shipping offers that help a retailer’s ad to stand out.
PLAs
Text Ads
Ad Text Testing

9. Product Listing Ads are still in their infancy. As retailers are able to understand the return from their
PLA investment, they will allocate more spend towards them and competition will rise. At Adlucent, our
clients are seeing 20 percent higher CTRs with 15-25 percent lower CPCs than text ads. Although these
are strong numbers, we can expect the cost of CPCs to increase as more retailers participate, possibly
surpassing text ads. We can also expect Google to continue to closely monitor and adjust the search
engine results page, with PLAs gaining higher positioning and prominence.
To learn more about product listing ad services, please visit adlucent.com or call 1.800.788.9152.
About Adlucent
With the evolution of Google Shopping, SKU-level paid search may be a new initiative for many retailers,
but Adlucent has been managing PPC through micro-segmentation for over 10 years, starting with their
first client, Amazon. Adlucent manages paid search programs for some of the world’s leading brands
including Free People, Harry and David, and Oriental Trading Company. Through their predictive bid
management technology and analytics platform, Adlucent is able to grow revenue profitably for their
retail clients.
Interested in learning more about Adlucent?
adlucent.com
1-800-788-9152
solutions@adlucent.com
Twitter: twitter.com/adlucent
Facebook: facebook.com/adlucent
LinkedIn: adlucent