Previously only available for Google, Yahoo, and Meta, the leading digital automation tool now suggests more optimal keyword and search query settings for Amazon Ads

Shirofune, the leading digital advertising automation management tool, announced an enhanced Improvement Suggestion feature that proposes optimal keyword and search query settings for Amazon Ads.

Shirofune’s Improvement Suggestion identifies keywords and search queries that increase costs without delivering the desired results, automatically listing those that need to be excluded or reviewed. It also recommends additional keywords anticipated to drive better performance. Additionally, the feature recommends excluding high-cost keywords and incorporating negative keywords, a capability not currently available in Amazon Ads. This feature helps reduce unnecessary expenses and allows ad campaigns to operate with a lower ACoS.

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This enhancement extends Shirofune’s improvement suggestion feature to its fifth supported platform, following Google Ads, Yahoo Ads, and Meta Ads. The feature has already delivered numerous optimizations across these platforms, and its integration with Amazon Ads promises even greater efficiency and performance for users.

“The expansion of our improvement suggestion feature to Amazon Ads marks a significant milestone for Shirofune,” said Tomomi Takeshita, Co-Founder of Shirofune. “This enhancement not only streamlines the ad management process but also empowers advertisers and marketers to achieve optimal performance with greater efficiency. By automating the identification and adjustment of keywords and search queries, our users can focus on strategic decision-making while ensuring their campaigns are continually optimized. This development reaffirms our commitment to providing advanced, user-friendly tools that drive success in digital advertising.”

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Typically, managing Amazon Ads involves manually adding or excluding keywords and setting search query exclusions based on data analysis and personal expertise. Shirofune’s advanced algorithm streamlines this process by analyzing the ideal settings and presenting the recommended changes as improvement cards on the management screen. Users can simply approve or reject these suggestions, ensuring daily optimization with minimal effort.