When AI can not only respond to your "what to buy", but also prompt you to make payment directly, a quiet revolution in shopping habits and e-commerce landscape has begun.
How new features are reshaping the shopping process
In the past, after users received product recommendations during a conversation, they still had to manually jump to the e-commerce platform to search, compare prices, and then place an order. Nowadays, in the conversation interface, after artificial intelligence gives text suggestions, it will directly attach the most relevant product cards. This saves users the trouble of switching between different applications.
When users click on the product card, they can see the specific sales page and price of this product on platforms such as Etsy. The entire process of discovering products is greatly compressed. From generating ideas to viewing product details, it can be completed almost seamlessly in one conversation. The efficiency gains are clearly visible.
Equal opportunities for all merchants
This feature emphasizes that product recommendations are naturally sorted solely based on relevance to the content described by the user, and do not involve advertising bidding. This shows that whether it is a large brand or an independent craftsman, as long as the product meets the user's needs, they all have the same opportunity to be displayed. This can be regarded as bringing new exposure channels to small and medium-sized businesses.
However, whether the merchant has enabled the instant checkout function will not affect the display of its products here. The system will display products that support instant checkout while displaying products that need to be redirected to the merchant's official website. This ensures the diversity and completeness of recommended results, and does not use payment convenience as a pre-filter. As a result, recommendation results are guaranteed to be diverse and complete, without payment convenience being used as a pre-filter.
The final opening of the payment closed loop
Previously, even if users saw the recommended products, they still had to leave the application and go to the merchant's website to complete the payment operation. The upgrade that plays a key role now is that users can directly use mainstream methods such as credit cards and Apple Pay to pay within the app without the need to jump. Plus users and Pro users can also use pre-saved address information to achieve one-click quick checkout.
For merchants, there is the support of the ACP protocol, which simplifies the process for merchants to connect various payment methods. For platform-level merchants like Etsy, no additional operations are required as the system has already been integrated. In this way, the “last mile” of the shopping experience is cleared.
Potential impact on Amazon’s business model
The core lies in Amazon's business model. It has become the default search engine and then the end point for users' shopping. Users are accustomed to going to Amazon to search, traffic gathers here, and transactions form a closed loop here. If users develop the habit of describing their needs to AI first and then making purchases directly under its recommendations, the status of Amazon's traffic entrance will be weakened.
This shows that the starting point for shopping may change from Amazon’s search box to an AI dialogue window. AI acts as a shopping guide and price comparison tool. It will no longer direct traffic to a centralized platform, but directly connect users to specific merchants based on demand, which to a certain extent "avoids" traditional central hubs like Amazon.
An industry trend that is not an isolated case
In fact, it is not the only one trying to use AI to break into the shopping scene. Since last year, technology giants such as Microsoft have also launched similar AI shopping functions. Their common purpose is to use the understanding and recommendation capabilities of artificial intelligence to redistribute shopping traffic and challenge the role of "gatekeepers" in the existing public e-commerce landscape.
This trend shows that the "intent shopping" model with dialogue and recommendation as the core is being regarded as a potential form of the next generation of e-commerce. It no longer relies on users to actively enter keywords for search, but relies on understanding the user's natural language needs to proactively present solutions. This has brought changes to the basic logic and principles of human-computer interaction.
Will history repeat itself?
In the field of e-commerce, when AI companies began to get involved, many people were skeptical and felt that they were unable to shake the well-established e-commerce giants. However, disruption in the business development process often starts from those marginal innovations that are not very eye-catching. For example, at first it was just a small company engaged in mailing DVDs. Later, it took advantage of the widespread popularity of broadband to transform into a streaming media company, and eventually reshaped the entire film and television industry.
Today, AI assistants are moving from "recommendation" to "transactions." On the surface, it looks like a crossover, but in fact it is a closed loop at the end of user needs. Whether it can succeed depends on whether users are willing to accept this increasingly convenient shopping model. The prelude to this change has already begun, and its impact will gradually become apparent in the next few years.
After reading this article, do you think you will be more inclined to use AI assistants to tell your needs when shopping in the future, or will you still search on traditional e-commerce platforms? You are welcome to share your views in the comment area. If you find it inspiring, please give it a like and support.
