Types of Recommendations Provided by Amazon Ads Analytics

Core Recommendation Types Explained

Most Amazon Ads analytics modules, such as the Amz Ad Waste Detector, offer several types of automated and manual suggestions. Key recommendation types include:

• Negative keyword additions: Block underperforming or irrelevant search queries to improve ad targeting and lower wasted spend.
• Bid adjustments: Suggest bid increases to capitalize on effective keywords or reductions to control costs on low-performing terms.
• Match type changes: Modify how closely a user's search must match your keyword, enabling broader or more specific targeting based on results.
• Campaign actions: Propose pausing campaigns or ad groups that aren't meeting objectives, or resuming them when market conditions improve.

Using Recommendations for Practical Optimisation

Implementing these recommendations helps streamline campaign management and improve profitability. By reviewing and acting on analytics-driven advice, users can more effectively allocate their budgets, reduce inefficient spending, and target their best opportunities for growth. Exporting decision logs provides a record of all actions taken, supporting accountability and future analysis.

When This Matters Most

Applying these recommendations is especially beneficial during periods of high advertising spend, seasonal promotions, or when launching new campaigns. Regular review ensures you adapt to changing trends promptly and protect your ROAS goals.