Amazon PPC

How to Read Amazon Advertising Reports (And What to Do With the Data)

Skale Strategy

Amazon Advertising gives you access to dozens of report types with hundreds of data points. Most advertisers either ignore the reports entirely or drown in data without extracting anything useful. Neither approach works.

After over a decade of managing Amazon ad accounts, here are the reports that actually matter and what to do with them.

The Search Term Report: Your Most Valuable Report

Pull this weekly. Not monthly, not quarterly — weekly. The search term report shows you exactly what customers typed before clicking your ad. It is the single most actionable report in Amazon Advertising.

What to look for: search terms with high spend and zero sales (add as negative keywords), search terms with high conversion rates in broad or auto campaigns (graduate to exact match), and search terms where your ACOS is significantly above or below target (adjust bids accordingly).

We process search term reports every Monday for every Skale client. On average, we add 15-30 negative keywords and graduate 5-10 high-performing terms per account per week. Over a quarter, that is 200+ negative keywords preventing wasted spend and 60+ proven terms getting dedicated exact-match bids.

The Placement Report: Where Your Money Goes

Amazon shows your ads in three placements: top of search (first page), rest of search, and product pages. The performance difference between these placements is dramatic.

Top of search typically converts 2-3x better than product page placements. That does not mean you should bid up for top of search across the board — that would blow your budget. Instead, use placement modifiers strategically. For your highest-margin, best-converting ASINs, increase top-of-search bids by 30-50%. For everything else, let Amazon distribute naturally.

Product page placements often have high impressions but poor conversion. If a campaign's product page ACOS is more than 2x your target, consider reducing the product page bid modifier or restructuring the campaign.

The Advertised Product Report: ASIN-Level Truth

This report shows performance broken down by individual ASIN. It answers the question every brand should be asking: which products actually benefit from advertising, and which ones are burning budget?

We regularly find that 20-30% of advertised ASINs in a portfolio generate 80%+ of ad-attributed revenue. The other 70% are either breaking even or losing money. That does not mean you stop advertising those products — some need ads for ranking — but it does mean you need to allocate budget proportionally.

Check this report monthly. If an ASIN has spent $500+ with zero attributed sales over 30 days, something is wrong. Either the listing does not convert (fix the listing before spending more on ads), the targeting is off (review search terms), or the product is not competitive at its price point.

New-to-Brand Metrics: Are You Growing or Recycling?

Amazon's new-to-brand metrics (available for Sponsored Brands and DSP) tell you what percentage of your ad-driven sales come from first-time buyers. This is one of the most underused data points in Amazon advertising.

If your new-to-brand percentage is below 40%, your ads are mostly reaching people who would have bought anyway. You are paying for sales you would have gotten organically. That is not necessarily bad — brand defense is important — but it should be a conscious choice, not an accident.

At Skale, we track new-to-brand metrics monthly and use them to calibrate the balance between brand defense and customer acquisition campaigns. The goal is not to maximize new-to-brand percentage — it is to know where every dollar goes and make intentional decisions about it.

Stop Reporting, Start Deciding

Reports are only valuable if they lead to actions. Every report you pull should answer a specific question and result in a specific change. If you are generating 40-page monthly reports that nobody reads, you are doing it wrong. Focus on the four reports above, pull them on a consistent cadence, and tie every data point to a decision.

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