Shopping Campaigns are designed to work with eCommerce websites. Product (ad) information is stored in a database known as a “Merchant Center”, which is connected to the PPC ad platform.
Are you feeling the Google Smart Shopping blues? Symptoms include irritability, restlessness, an inability to sleep, and a sickening feeling about what's happening to all your eCommerce ad spend.
Steve discusses 6 things to consider when deploying an eCommerce Shopping Campaign starting with “Smart Shopping” Campaigns vs. Standard Shopping Campaign
For eCommerce Shopping ad campaigns, conversion tracking setup is important because it allows for calculating the two most important metrics in paid search: return on ad spend, and advertising margin.
More importantly, it provides valuable information back to the automated bidding algorithms, which uses machine learning logic to maximize the performance of the campaign.
When a Shopping campaign sends accurate conversion tracking conversion values back to the automated bidding logic, automated bidding with machine learning can deliver significant performance improvements, and greatly reduce campaign management time.
Individual shopping campaigns are structured internally on two levels: Product Groups, and Ad Groups.
Product Groups provide a mechanism to group together similar products within the feed. You can create product groups using various attributes present in the feed. Typically this is used to bid similar products and product variants at the Product Group level.
Each product group is a subset of the feed. The bids are then controlled at the product group level. This can save a great deal of time while managing campaigns with sizeable feeds. When beneficial we utilize ad groups with ad-group level negative keywords to influence key-phrase matching.
Negative keyword discovery is feature that shouldn't be neglected when targeting a shopping ad campaign.
Negative keywords applied in a shopping campaign act as an inhibitor, or overlay on the positive targeting methods. They allow us to "shape" with a bit more more precision, who the ads serve to. For example, we might exclude certain age groups and/or income levels.
During the period immediately after a shopping campaign launch, we're monitoring impressions and CPC's. We're also on the lookout for major issues such as a single product group consuming excessive ad spend.
Conversion tracking is checked for functionality and accuracy. Geo-targeting is monitored for any anomalies, CPC’s are checked for any out of line behavior, and the campaign is scanned for errors or warnings.
This post-launch optimization phase typically lasts 3 to 6 weeks for an average scale shopping ad campaign. A Shopping campaign enters semi-automated "orbit" once it has transitioned onto automated bidding.
When setting up shopping campaign serving parameters, bidding is the central issue. Manual bidding at launch is the best way to force shopping campaigns to develop serving momentum quickly.
The manual bidding period provides a baseline to optimize against going forward. It also provides confirmation that we're bidding up to the "Benchmark" shopping bid level.
When setting up serving schedules, our scheduling preference is usually to allow the campaigns to initially run 24x7x365 Many campaigns perform well at surprising times, during days of the week and hours of the day you might not expect.
In some b2b eCommerce markets, we will run campaigns on weekdays only and perhaps not overnight. There are time zone spans to consider, for example in the US, making sure East coast campaigns stay on late enough to shop up for West coast end-of-day business traffic.
Each product search entered into a search engine creates one or more electronic auctions where advertisers bid for available ad slots on the Shopping ad "carousel being" being served to the prospective buyer.
We identify direct and indirect competitors, familiarizing ourselves with their products, services, and positioning in the market. We look at the advertising history, ad copy, ad spend, and market positioning of the most significant online competition.
While spidering competitive websites we can extract entire product feeds to examine feed attribute details. During this process, we gain a level of understanding which is uniquely useful in structuring and configuring Shopping campaigns.
Our shopping campaign performance management reports are designed to fit your eCommerce business objectives, product line(s), and campaigns. We include standard key performance indicators (KPI's), or we can implement custom KPI's most closely aligned to your business objectives.
One difference with our shopping reporting is our segmented performance tables. Many shopping campaigns advertise thousands of SKU's so it can be quite helpful to view performance in tabular form, with sorting.
Our tabular reports can be segmented and summarize performance by product line, ad group, product type, product group, or custom label parameter - whichever is most useful to your business.
Shopping campaign optimization is radically different from the optimization of the other three fundamental types of paid search campaigns.
Shopping campaigns operate on structured data, being driven by an eCommerce database, where text and images for each individual product reside. So shopping campaign optimization in part involves optimization of the text and images in the eCommerce database.
There are a number of different approaches to structuring shopping campaigns, and the structure has to be right or it will be more difficult to improve performance through optimization.
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