Shulou(Shulou.com)06/02 Report--

Not long ago, we just released the first episode of the White Cave Enterprise Awakening Plan. In the original intention of formulating this plan, we are eager to be close to the infinitely real and infinitely detailed scenarios of AI industry applications. Especially away from the areas where financial and Internet data are sufficient and more suitable for AI, and then stagger the perspectives of BAT and large factories, which are concerned by more people.

The end result is that what AI needs most to irrigate the roots of industrial applications is more collisions between technology users and technology developers.

Today, we will witness the collision between AI unicorn vision and a small mother-and-child retail chain, starting from the first episode of the White Hole Project, "Intelligent Retail Solutions for exclusive small and Micro businesses".

Root obstacles and bewilderment: why is it difficult for small and micro businesses to apply AI?

In the whole process of communication, our deepest feeling is that the application of AI in small and micro business systems is far more urgent than we thought, but the environmental conditions for the application of AI in small and micro business systems are also far worse than we imagined.

In the case of Mr. Jiabin Shi, as a small retail chain of mother and baby products in Beijing, they are particularly poor in withstanding the impact of smart retail.

Mr. Shi said he saw that many retail stores have adopted new models such as facial scan payment and facial membership system, while his own stores seem to be stuck in a few years ago. What has a more direct impact on efficiency is that many retail enterprises have been able to apply data mining to make selection decisions by accumulating business data and associated data. However, traditional small and micro commercial stores often rely on intuition when carrying out promotional stock preparation.

In Mr. Shi's own words, that is, he can only look at what is popular on other brands and frequently produce online celebrity explosions. But the only thing that can relate to personal consumption trends in their stores is the membership system, but now many consumers no longer accumulate points because they find it troublesome.

Generally speaking, the weak control of sales rhythm, the high cost of cross-store management, the rib of membership system, and the lack of data in sales promotion and selection decisions are several typical problems that need to be solved urgently by using AI technology in small and micro business system.

As a small and micro business system, the poor information conditions and the lack of understanding of the technology itself also increase the decision-making cost of business owners.

In Mr. Shi's case, most of the employees in mother-and-child stores refer to each other's sales ability and whether they know enough about the baby group, which results in their employees having little basic knowledge of the Internet and IT technology, let alone AI. And business owners have no idea what changes to the infrastructure in the store, how much it costs, and how to install subsequent upgrades, and so on.

For small and micro enterprises, the input-output ratio of AI technology application can not be implemented in detail, which leads to numerous puzzles.

Fitness testing: what kind of technical support do small and micro businesses need?

To put it bluntly, not all of these problems faced by small and micro businesses can be perfectly solved by technology enterprises. However, we can dig in the solutions that can be given by Skyvision to see the technical support that small and micro businesses need and what are the characteristics.

To put it simply, we can divide the fit points between smart retail solutions and small and micro businesses into three points.

The first point is to use extensive data mining and association to make up for the data base of small and micro businesses.

We have learned that the biggest shackle of small and micro business systems using AI is the lack of data. If a large enterprise is transforming, it may be possible to collect, clean, label and model data from scratch, or simply buy large amounts of data. But the small and micro business system does not have this kind of energy.

The solution given by Xiangshi is to analyze brand-new data through its own inherent data analysis model, and to extract information that can be used by small and micro businesses.

For example, Xiangshi has a very detailed intelligent video analysis scheme, which can analyze the behavior of users when shopping to find out which products they are more interested in, and can further subdivide highly repetitive users by dressing up. Even if the main consumers in mother and baby stores are women, the smart video analysis program can also analyze their spending power through the image of clothes.

In this way, it is possible to develop a suitable data analysis model while growing together with the business body, and at the same time have a reliable transition plan.

The second point is the zero-threshold application model to eliminate the learning cost and mistrust of small and micro businesses.

Due to the limited cost, the biggest concern for small and micro businesses to access new technologies is "one-shot trading". For example, after purchasing a technology, they find that they need to purchase a large number of supporting services before they can use it; or they cannot connect with their own system after purchasing the technology; no one is responsible for subsequent upgrades, and so on.

Kuangshi suggested that in the case of Mr. Shi, for example, only the snapping equipment for portraits and the AI computing unit for using the original security equipment, the network facilities of basic normal stores can be satisfied. As for system docking, the vast API interface library of ERP partners has been accumulated, and most of the data docking can be completed in as long as two months in a week. As for the subsequent upgrade and so on, basically only need the user to choose "agree", it can be carried out automatically in the background.

Although the goal is far away, the industrial application of AI technology is indeed developing in the direction of "foolishness".

Third, growth technologies that pay for the future.

As owners of small and micro businesses, they share the same confusion as most people-where on earth is the evolution of AI technology? As ordinary people, we are only observing the evolution path of AI technology, but for business owners, especially small and micro business owners who rely heavily on technology suppliers, the evolution path of AI technology is closely related to their own business decisions.

The most direct interest correlation is that if the technology partner they choose currently cannot cope with the future technology growth, it will bring a lot of trouble to the enterprise.

At this point, the advantage of being an AI unicorn is revealed. Ignoring its own ability of computer vision, it has a more comprehensive layout of AI technology, and intelligent retail is one of them. This also means that Xiangshi will continue to innovate in technology, constantly inputting their omni-directional abilities into the details of the scene. Take smart retail as an example, Xiangshi is constantly trying to integrate a variety of technologies, such as using intelligent warehousing robots to solve city-level logistics problems, or using the city brain to help small and micro businesses to improve location efficiency.

From this point of view, in fact, the cost of small and micro businesses applying intelligent retail technology should be divided into long-term costs and short-term costs. The short-term cost includes the cost of purchasing services at that time, the price of supporting hardware, the duration of system docking and the difficulty of getting started. The long-term cost includes the cultivation of its own applicable model, the service quality of technological upgrading and updating, and the supplement of technical capability in the future.

Only by considering the balance of the two kinds of costs can the final decision be made. But there is no doubt that most business owners think like Mr. Shi that AI is a trend-people can only ride the wind or be abandoned by the waves.

Therefore, the brain polar body is fortunate to be a tide watcher above the lighthouse, hoping to do its part to help more AI technology enterprises contact users in the White Hole project and collide with real-world solutions.

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