![\"\"](\"https:\/\/e-dialog.group\/wp-content\/uploads\/2025\/08\/produktportfolio_analyse_im_ecommerce_teil_2_01.png\")
\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/p>\nHence, in this case the analysis was carried out at a product category level. Attention: the performance of an online shop can be examined at different levels; depending on the scope of the product range and the expectations of the analysis. You should therefore carefully consider in advance which variant will achieve your goal.<\/p>\n
If the range is very small, an analysis at product level definitely makes sense. In general, the company’s analysis requirements and product range determine the ideal approach.<\/p>\n
In our specific example, we differentiate between tower and pedestal fans. Of course, you could break this down even further, e.g. categorizing according to power consumption or manufacturer.<\/p>\n
Entire product categories can also be compared with each other, in this example household appliances vs. consumer electronics.<\/p>\n
Theoretically, it would be entirely possible to analyze each individual electrical device and compare them with each other. At the product level, the analysis in this case would be too complex, confusing and not meaningful enough for operational use. Apart from the fact that the focus here is on the overall performance of the online shop and not that of an individual product.<\/p>\n
Evaluating individual products makes sense at regular intervals, for example after the introduction of a new product. This guarantees regular monitoring of the product portfolio.<\/p>\n
Back to the fans: an ideal placement would therefore be characterized by a high number of product views and at the same time a high product conversion rate.<\/p>\n
\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/p>\n
That’s the wishful thinking, but in reality the results usually look different.<\/p>\n
If, for example, a product category is rarely clicked on but is bought comparatively often online, a hard-to-find placement in the online shop could be to blame. However, speculation will not get us anywhere in the long term. Using further techniques and analyses, we find out which product is becoming a slow seller in the online shop and why and offer well-founded optimization approaches.<\/p>\n
A web analysis tool that natively supports the tracking of product views (in contrast to page views) and ideally also displays numerous product attributes such as categories, properties, etc. We will be happy to support you with selection, introduction and use!<\/p>\n
PS: We are currently happy to receive offers for stationary air conditioning systems – the fans only provide cooling to a limited extent <\/p>\n","protected":false},"excerpt":{"rendered":"
Let’s go back to the example from last time and remember:<\/p>\n
Each product category was assigned a total of three values: number of product views, product conversion rate and gross product sales<\/p>\n","protected":false},"author":1,"featured_media":4804,"comment_status":"closed","ping_status":"open","sticky":false,"template":"post-old.php","format":"standard","meta":{"_acf_changed":false,"footnotes":""},"categories":[5,445],"channel":[456],"goal":[463],"technology":[],"c-year":[73],"class_list":{"0":"post-12646","1":"post","2":"type-post","3":"status-publish","4":"format-standard","5":"has-post-thumbnail","6":"hentry","7":"category-analytics","9":"channel-shopping","10":"goal-digital-strategy","11":"c-year-73"},"acf":[],"yoast_head":"\n