Ad Performance Analysis a Chaotic Mess? Don’t Know Where to Start? It’s Because You’re Missing This.

As a qualified Amazon seller, analyzing ad data is a necessary skill. By analyzing ads, we can identify many potential customers and seize profitable opportunities. Simultaneously, we can use ad data to think from the customer's perspective, discover operational loopholes, optimize them, and ultimately increase sales and profits.

However, when presented with ad data, it can initially feel overwhelming. It's a dense mass of numbers, and manually organizing reports downloaded from Amazon Seller Central—how to organize, how to sort—it's a complete mess. Many sellers are truly bewildered by this, unsure of how to begin analyzing and optimizing their ads.

Actually, before analyzing and optimizing ads, we can first clarify which key metrics to focus on, such as: Impressions, Clicks, Click-Through Rate (CTR), Orders, ACOS, etc. Then, based on the metric performance, combined with the factors influencing these metrics, identify problems and optimize promptly.

Four Analysis Direction Suggestions:

I. High Impressions + High Clicks + Low Conversion

1. Are the keywords driving traffic not precise enough?

Optimization Strategy: Reconfirm the relevance to the product. If the relevance is weak, consider directly negating the keyword or removing it directly from the product description.

2. Is the product Listing not good enough to attract customers to place orders?

Optimization Strategy: Adjust Listing details such as A+ Content, Q&A, Reviews, etc., to make the product description more appealing.

Note: Do not rule out that poor performance is due to chance. At this time, you can try re-opening ad groups and conducting multi-group campaign testing.

II. High Impressions + Low Clicks + Low Conversion

1. Is the product not relevant to what customers are looking for?

Optimization Strategy: Adjust keywords in Listings and ads, and remove weakly relevant keywords.

2. Are the product image, price, and title uninteresting to consumers at first glance?

Optimization Strategy: Optimize the main image, title, and price, etc., to make them more attractive.

III. Low Impressions + Low Clicks + Low Conversion

1. Issues caused by various factors such as page, keywords, images, or product itself.

Optimization Strategy: Consider a major overhaul of the Listing, starting with comprehensive optimization of basic information such as product title, images, and description.

IV. Low Impressions + High Clicks + High Conversion

1. Is the keyword ad bid too low?

Optimization Strategy: Increase the bid for this keyword to get more impressions and clicks.

Even with analysis directions, downloading ad reports and merging multiple reports is still cumbersome. If you are not proficient in Excel and want to analyze directly, it is quite challenging. At this point, we can use tools to improve our efficiency in analyzing ads!

Open the [Ad Management] feature of Youmacloud, and we can see all the ad data in the store, directly skipping the report organization step and getting straight to the analysis.

It divides ad data into six main dimensions: Campaigns, Ad Groups, Promoted Products, Keywords, Product Targeting, and Search Terms.

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Enter the corresponding data module. First, use the filter bar at the top to select the ad objects to be analyzed. Campaigns, Ad Portfolios, and Ad Groups can be multi-selected, suitable for unified analysis of ad performance.

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After finding the ad objects, click on relevant metrics such as Impressions, Clicks, Click-Through Rate, and Orders. By sorting, you can roughly understand the overall data performance of these ad placements.

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After having a certain grasp of the overall ad data, click to enter the [Analysis] feature, further refine the data range according to ad metrics, and conduct precise analysis.

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The [Analysis] feature includes a total of 25 ad metrics, and you can set data ranges for multiple ad metrics simultaneously, providing multi-dimensional analysis directions.

For example, by setting the range of Impressions, Clicks, Click-Through Rate, and Orders, you can directly view which ads have High Impressions + High Clicks + Low Order Conversion. After identifying them, further confirm whether there are issues with the keywords or product descriptions of these ads, and how to adjust them, etc.

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At the same time, if we currently have a fixed analysis mode, such as: Click-Through Rate ≥ 7%, ACOS < 30%, Low Impressions + Low Clicks + Low Conversion, etc., after determining the filter conditions, we can directly save this mode. The next time you enter analysis, you can quickly filter data in this mode, saving time and improving efficiency!

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Quickly query and analyze data:

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In ad placement, data analysis is a very important part. Good methods and tools are indispensable and can help us improve efficiency and achieve twice the result with half the effort.

Simultaneously, it is recommended to adopt different ad products, formulate an overall strategy to control the big picture, master Amazon ad data analysis skills and directions, and drive operational decisions through data feedback analysis from various modules. This can help increase revenue, improve ad placement efficiency, and at the same time reduce risks and control costs.