PPCProduct Listing Ads Click-Through Rate 21% Higher Than Text Ads [Study]

Product Listing Ads Click-Through Rate 21% Higher Than Text Ads [Study]

Marin Software released a report examining the performance of product listing ads (PLAs). The research found that PLAs not only have a higher click-through rate (CTR) than text ads, but PLA CTRs have increased each month since February.

Marin Software today released a report that showed Google’s Product Listing Ads (PLA) are winning in the paid search results with PLA click-through rates (CTR) remaining higher than standard text ads since November 2012.

“Shoppers continue to find PLAs, rather than standard text ads to be more relevant to their product searches regardless of seasonality,” Marin stated in its report.

In June and July 2013, PLAs had a record 21 percent higher CTR than text ads, according to Marin’s findings. In July 2013, PLA CTRs had increased 19 percent year over year, and have increased each month since February, when Marin last checked in with a study on the huge growth of PLAs during Q4.


And even though Marin said PLAs are cheaper and perform better than standard text ads, PLA CPCs increased 53 percent year over year as of July 2013. Text ad CPCs shot up as well by 10 percent.

Kye Mou, senior product marketing manager at Marin Software, gave four tips on how to maximize performance of PLAs:

1. Map Product IDs or SKUs to Individual Product Targets

In general, the more granular the product target, the more likely a relevant ad will be delivered for a corresponding product search. Instead of grouping multiple products together into a single product target, search marketers who map product IDs or SKUs to individual product targets are able to tie the performance of each target directly back to the individual product.

Optimizing with this level of visibility and control allows retailers to not only align product targets with product-specific business goals, but also calculate optimal bids that maximize revenue across the entire product inventory.

2. Organize Promotional Text Granularly

Promotional text, which is optionally set at the ad group level, benefits from granularity and is best leveraged with a tightly themed set of product targets. By organizing product targets that are consistently promoted together into separate ad groups, or the same ad group – such as by brand or product category – retailers can significantly differentiate their PLAs from their competitors.

Keep in mind, promotional text applies to all the products targeted in a specific ad group. Thus, messaging should be applicable to all products under each product target and should be updated regularly to reflect changes to promotional offers.

3. Prioritize Top-Performing Product Targets

Similar to paid search keywords, prioritizing top performing product targets provides retailers with more control over their revenue outcomes. By increasing exposure for these products, whether through an aggressive bidding strategy, separate ad groups and product targets, or through product feed optimization, search marketers can acquire more revenue while investing less time in management and optimization.

For example, increasing product target bids or testing new images for popular products are two common strategies for increasing visibility among shoppers. Additionally, leveraging “dimensions” or “labels” along with recurring reports allow search marketers to quickly take action on top-performing product targets when they’re impacted by sudden shifts in the auction environment.

4. Exclude Poor-Performing Products

In contrast, products with low margins or products that perform poorly with standard text ads might also perform poorly with PLAs. By excluding these products from product targets or setting product filters to define which products can appear for PLAs, retailers can avoid bidding on these unprofitable products and exhausting their campaign budgets.

In addition, to limit the product searches for which PLAs will show and further improve relevance and performance, always research and implement appropriate negative keywords.

For the full report by Marin Software, go here.


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