Contents
- Manage campaigns:
- Optimize bids:
- Measure results:
Manage campaigns
New features in adaptive Shopping campaigns
Adaptive Shopping campaigns monitor your Merchant Center feed and automatically subdivide existing product groups by product ID based on the performance of the products in each group.
We recently improved adaptive Shopping campaigns with several new features:
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Goal-based breakouts: Adaptive Shopping campaigns now break out product groups based on a goal that you set up.
For example, you can set up a Shopping campaign that automatically creates product groups for products that:-
Generate similar amounts of revenue
or -
Generate a similar number of conversions
You can also specify which Floodlight tags or Google Analytics goals are relevant to your Shopping campaign, or specify a formula column that applies other custom logic to the data collected by your Floodlight tags or Google Analytics goals. Previously, Adaptive Shopping campaigns would only consider clicks and conversion rate from all Floodlight transaction tags when breaking out product groups.
Goal-based breakouts further align your adaptive goals with your bid strategy goals. For example, you can break out product groups based on revenue, and then create a bid strategy with a revenue goal. The bid strategy can then maximize overall revenue from the campaign by setting different bids for your higher-revenue and lower-revenue products. -
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Automatic cleanup of empty product groups: Product groups that stop receiving clicks for a period of time will now be automatically removed.
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Better recognition of customer intent: The adaptive algorithm has been tuned to better match the ways customers interact with your inventory. Specifically, advertisers who have lots of products with a fairly even distribution of traffic will see a greater number of product groups broken out based on customer response to your ads.
Optimize bids
Bid strategies expanded to manage AdWords remarketing targets
AdWords remarketing lists for search ads (RLSA) enable you to target customers who have previously visited your site by setting a bid adjustment percentage, for example, 35%, for the remarketing target. This means that the bids for the remarketing target will be 35% more than bids for the ad group’s keywords. You can set the bid adjustment from -90% to 900%. With this release, you can also let a bid strategy optimize or recommend the remarketing target bid adjustment. Learn more.
Use cross-device estimates to optimize mobile bid adjustments
In today's multi-device world, an increasing number of conversion funnels stretch across devices and web browsers. Given the way tracking and reporting systems work, there's no way to know for sure if a user who sees or clicks an ad on one device ends up converting on another. That makes it difficult to fully understand the role that mobile devices play in a conversion funnel, and therefore difficult to know how much to bid on mobile ads.
To bring insight into cross-device conversions, Floodlight activities can estimate the total number of conversions a keyword contributed to--including those that start on one device and end on a different device. DS bid strategies can then use those estimates to calculate the mobile bid adjustment that will most efficiently lead to conversions. Learn more.
Measure results
Report on Quality score and First page bids
As an agency, you put a lot of effort into adding negative keyword lists, tight match types, and other components to increase the quality score for an advertiser. To show the impact of your work, you can include AdWords Quality score (QS) and First page bids data in your DoubleClick Search (DS) reports. With this data, you can:
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See the current AdWords quality score and an estimate of the bid you need for a keyword to appear on the first page of search results.
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Chart the average quality score or first page bids over time for an entire account.
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Compare quality score changes over time, which help you track whether your changes are actually improving quality score.
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Track quality score changes against changes in clicks and cost to explain changes in cost per click (CPC).