Product descriptions are a key part of your potential customer's decision-making process. 87% of consumers rate product content extremely or very important when deciding to buy. Better product descriptions generated by professional AI content generators can increase conversion rates by up to 60% compared to human-written descriptions.
Your product title is the first thing customers see when visiting your detail page. Amazon uses the words in product titles to display your products in search results. A concise (maximum length of 80 characters) and relevant title will drive traffic to your product.
Example: XYZ Brand Women’s Plus Size Cable Knit Cardigan
The Key Product Features bullets on the detail page tell the customer the details of your product and can influence the customer purchase decision. The description helps customers evaluate a product, so any non-product-specific information can distract from a customer’s purchase decision. Customers use this section to get a snapshot of the product. They may use this section to finalize a purchase decision or it may interest them enough so they will then read the full product description.
As you describe your product, you might want to include some key features listed in your bullet points. However, go beyond a simple to-the-point description. Well-written product descriptions help the customer imagine the experience of owning or handling your product. Put yourself in your customers' shoes: what would they want to feel, touch, ask, and want? Incorporating information about the feel, usage and benefits of your product can fire the customer's imagination. This is as close as you can come to creating an in-store experience. Product Descriptions are limited to 2000 characters.
The Amazon listing creator designed by Kua.ai is based on the above elements. Therefore, compared to the results generated by common prompts, the results generated by Kua.ai will be more in line with Amazon's clothing listing best practices, resulting in higher conversion rates.
When you only have very basic product information from the supplier, how do you use AI to generate a meaningful, high-conversion-rate product description?
Aside from the AI model design itself, another important factor affecting the output result is the input content. AI is not a magician. It cannot understand your product better than you, nor can it create a unique selling point for your product out of thin air. Therefore, only when you understand your product like your own child, and provide AI with a basic direction, can AI give you meaningful feedback.
If the original product information you provide is not sufficient, it will cause the AI to lack background information at some critical points, and it will only use generic information, resulting in poor output results.
The workflow designed by Kua.ai for product descriptions generates the most compliant best practice results through multiple outputs. The benefit of doing this is that it increases the feasibility of manual intervention in suitable places, making the generated results more meaningful, instead of generating nonsense applicable to all products. It also prompts you to think about product selling points, simplifying your thought process.
Below, we will use a product on Ali-express as a detailed example.
It is recommended to manually complete the Not Available part and add missing important information to obtain better output results later.
If the original product information does not provide enough selling points, you need to make further manual adjustments to the generated results based on the selling points of the product, in order to obtain better output results later. It is more recommended to provide more comprehensive and detailed selling points when creating product information in Infobase.
This step has high requirements for the input content. If the input content is a vague and generic selling point, the result generated by AI will inevitably be a vague and generic result. You can look at the following example.
Without manual intervention, the output results of the Special Benefits and Advantage and Style tips sections did not capture the most characteristic selling points of the product, resulting in a lack of correlation between the AI generated results and the characteristics of the product itself. They are meaningless nonsense, such as "The dress sports a flattering v-neck, full sleeves, and comes in a range of sophisticated colors - wine, black, dark purple, and dark green, ensuring there's one for every mood and occasion. ".
The output results have improved after more detailed manual intervention:
By following these steps and providing comprehensive and detailed selling points during the input process, Kua.ai can help businesses generate meaningful, high-conversion Amazon clothing listings.