Products in Cluster
Last updated
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Last updated
The Products in Cluster report provides you with the most detailed level of analysis in Karsa Labelizer. It allows you to explore the performance metrics of each individual product assigned either to a specific cluster of your choice, or across all clusters within the entire clusterization.
Its main purpose is to:
Identify the most successful and problematic products: Quickly discover which specific products are driving your business (high ROAS, high conversion value) and which ones are lagging behind or generating losses.
Optimize product assignment to clusters: Analyze whether products are correctly assigned based on their performance and cluster characteristics.
Monitor performance at the product level: Track key metrics such as ROAS, CPC, CTR, number of conversions, and their value for each product individually.
After selecting a cluster or an entire clusterization, the "Products" report will show you a table with the following information for each product (data typically relates to the last 30 days):
Product ID: Unique identifier of the product in your system/feed.
Name: Product name from the product feed.
Cluster: Name of the cluster to which the product is currently assigned.
ROAS (Return on Ad Spend): Return on advertising investment for the given product.
CPC (Cost Per Click): Average cost per click on the advertisement of the given product.
CTR (Click-Through Rate): Click-through rate for the given product.
Cost: Total advertising costs for the given product.
Conversions: Number of conversions achieved by the given product.
Conv. value (Conversion Value): Total value of conversions generated by the given product.
Clicks: Number of clicks on advertisements of the given product.
Impressions: Number of impressions of advertisements of the given product.
Average product price: Average price of the product during the monitored period.
Filtering: Option to display products only from a specific cluster or from all clusters within the selected clusterization. You may also have more advanced filtering options based on the values of individual metrics.
Sorting: Products can typically be sorted by various columns (metrics). The default sorting is often by conversion value (Conv. value) or ROAS, which helps you quickly identify key products.
Visual Performance Highlighting (Percentile Coloring):
The report uses a sophisticated cell color coding system (similar to a heatmap) to visually emphasize the relative performance of products within the displayed set.
Red-yellow-green scale: For metrics such as ROAS and CTR, where higher values are better (green).
Green-yellow-red scale (inverse): For metrics such as CPC, where lower values are better (green).
Blue shades (or other neutral scale): For metrics such as Cost, Clicks, Impressions, Conv. value, Conversions, Average product price, where the color indicates the magnitude of the value.
Color highlighting is based on percentiles, which means that the cell color corresponds to the relative position of the value of the given product among all other displayed products for that metric. This allows you to very quickly identify products that are significantly above or below average in a certain metric.
Identification of "stars" and "dogs": Using sorting and color coding, quickly find products with the highest ROAS and conversion value ("stars") that deserve attention and possibly increased support. Similarly, identify products with high costs and low or negative ROAS ("dogs"), for which you should consider limiting promotion, adjusting price, optimizing the landing page, or completely removing them from active advertising.
Checking the correctness of cluster assignment: Check whether the performance of individual products corresponds to the overall characteristics of the cluster to which they are assigned. For example, if you find a product with very high ROAS in a "Low ROAS" cluster, it may be a candidate for movement (or a signal that its performance has recently improved).
Optimizing bids at the product level (if your strategy allows it): Although Karsa works with clusters as wholes, detailed data about products can help you better understand why some clusters perform better or worse, and possibly consider more detailed adjustments if the Google Ads platform allows it for the given campaign type.
Analysis of the relationship between price and performance: Observe how the performance of products differs across various price levels.
Uncovering problems with data in the feed: If a product shows unexpectedly poor performance (e.g., very low CTR despite a high number of impressions), also check the quality of its data in the product feed (title, description, image, price).
The "Products" report is an essential tool for anyone who wants to truly go in-depth with Google Shopping campaign optimization. It provides transparency down to the level of individual items and allows you to make highly informed decisions.
