Few online stores do without product descriptions. To attract the attention of potential buyers and convince them to buy the offered goods, you can not reply to personal messages, but ready answers to questions about the composition, quantity, material of manufacture, price. High-quality product descriptions help buyers get all the necessary information about the product, compare it with competitors and make the right choice. But those who have faced with filling a website, blog, page in social networks, know that the creation of unique and attractive product descriptions for each product requires a lot of effort and time. There are hundreds and thousands of goods, and they differ at most by color or size. Product description with the help of neural network greatly simplifies this process and saves time and resources.
Content:
- Advantages of using a neural network
- How to generate a description with AI?
Benefits of using a neural network
Creating product descriptions using neural networks saves time and resources that were previously spent writing each description manually
. Instead, a neural network is able to create a large number of unique descriptions in a short period of time.
In addition, artificial intelligence helps improve the quality and attractiveness of product descriptions. It uses training data and analytics to understand which phrases and words are most effective in attracting the attention of potential buyers. Thus, descriptions created with the help of neural network are optimized for maximum customer engagement.
But we can’t say that generating product card descriptions using artificial intelligence is all pluses, otherwise everyone would have switched to such generation a long time ago. As always, there are pitfalls that are nevertheless immediately noticeable. For example, neural networks can generate descriptions that sound correct, but are not quite meaningful or do not match reality. Therefore, it is important to carefully check and edit the generated texts for product cards. For the information to be meaningful and reliable, you will have to proofread each description yourself. But this is still faster than writing it yourself and certainly not as routine. For example, when thousands of dresses and skirts need to be called something beautiful, at the fifth hundred products fantasy begins to beg for mercy, and that’s where the neural network comes to the rescue. It can come up with not only product descriptions, but also titles and names.
Creating product descriptions using neural networks is an effective tool for online commerce. AI models are capable of generating unique and attractive descriptions, which saves time and resources and improves the quality of the resulting texts. The user sees the product description and based on this, can navigate and compare the lot on one site with detailed text and on another site without it. To create a description of the product, you can also use services that specialize in writing essays online. However, it is important to remember to check and edit the generated descriptions so that those meet the expectations of potential buyers and simply reality.
How to generate a description using AI?
1. First of all, you need to choose the model you will use to create product cards.
2. The right query is the key to success. The neural network must understand what you want it to do. If there are a lot of product cards, it is recommended to create a query template that can be periodically adjusted depending on the type and characteristics of the product.
3. no neural network will produce a perfect result. We have already realized this, so we play the cards that are dealt. We need to reread the resulting descriptions. It’s still faster than writing them from scratch. As a rule, if the AI has correctly understood the query (which should include the amount of description in characters or words, the name of the product, its characteristics), it will need to correct at most punctuation marks, which the neural network sometimes likes to arrange randomly.
If you have correctly formulated queries, you can generate a huge number of descriptions. Usually the resulting text is already unique, so you do not need to check through the anti-plagiarism program. But if you are not sure, you can check. Standard plagiarizers give a good figure, which is accepted by the issuing system. Thus, in a short time with the help of a neural network it will be possible to fill the site with unique descriptions of goods.
Also Read: MIT Neuroscientists Identify AI-Powered Predictive Language Models Resembling Human Brain
