Guangyun Technology: On the Eve of Large Model Commercialization, E-commerce Drives Practical AI Applications
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Today's e-commerce market is less about fierce competition and more about finally 'returning to the real world.'
As the structural boom brought by live-streaming e-commerce gradually loses momentum, the peak of traffic dividends is no longer a problem but a recurring cycle of technology and economic phases.
Static challenges test the ability to enter and exit the market, while dynamic cyclical contradictions test operational strategies.
In the e-commerce industry, where 'capturing a city is easier than holding it,' retaining consumers sustainably always holds more bargaining power than attracting new ones.
Undoubtedly, membership marketing is currently one of the most direct and effective methods.
Today, consumption stickiness indicators such as repurchase rates are gaining more attention from brands. Therefore, membership marketing is not just about creating an attractive membership system, but also about implementing a series of growth incentive strategies based on companion services. This involves not only cross-departmental collaboration in areas like user inquiries, order tracking, supply chain support, and after-sales service but also requires data segmentation of users to develop more refined user service operation strategies, maximizing the ROI of customer service resources.
This shows that while supply chains and emerging media channels, once the battlegrounds for e-commerce, still hold strong trump cards in the global cross-border market, they have already reached a highly competitive state in the domestic market, making it difficult to achieve further differentiation. Instead, the customer service sector, which had lower investment costs and poor integration during the野蛮 growth period, is now directly influencing consumer decisions and brand loyalty in the era of refined operations. Factors such as response speed and quality, the衔接 between AI and human agents, the ability to渗透 brand knowledge bases to users, and the implementation of分层 operation strategies are all playing critical roles.
It can be said that customer service capability is the true 'muscle' in the current deep-water stage of e-commerce.
This is evident from the product ecosystem布局 of leading e-commerce SaaS provider Guangyun Technology this year, which has allocated more R&D capabilities and resources to its intelligent customer service product 'Kuaimai Xiaozhi.'
The current state and trend in 2023 is that industries across the board are transitioning towards consulting services and striving to find ways to communicate directly with users. This is also why the role of customer service is becoming increasingly important, yet as a traditional position with relatively low barriers, it struggles to support operational strategies. Based on this, the capabilities of customer service are gradually being generalized. As the front-end component, it has not only been among the first to implement AI applications but also sees systems and solutions built around customer service continuously extending towards mid- and back-end strategic areas.
Take Kuaimai Xiaozhi as an example. Its capabilities not only cover basic AI chatbots, user demand process design, and cross-department collaboration but also include functions like intelligent user tagging, user segmentation, and intelligent quality inspection. During the e-commerce traffic boom, merchants and platforms could hardly imagine that merely perfecting products and channels was far from enough—they would need to focus so much on a position "that could be replaced by robots." In other words, since the current consumer market competition is already about the front-end, those who can integrate more market technologies will be better at executing member marketing strategies.
"The application of AI must be based on clear business processes."
As early as three years ago, Guangyun Technology had already begun its AI transformation, leading to the rapid enhancement of Kuaimai Xiaozhi's underlying AI capabilities today.
Wang Yi, CTO of Guangyun Technology, stated that e-commerce's demand for AI emerged earlier than in other industries and wasn't solely driven by the recent popularity of large models. Ironically, the overwhelming attention on large models has made many forget that AI encompasses more than just generative AI. AI capabilities can be deconstructed and integrated into various business processes, with intelligent automation currently primarily valued for cost reduction and efficiency improvement by replacing repetitive human labor.
For instance, widely recognized applications like customer service bots and design automation tools have existed in e-commerce for years, continuously optimizing to achieve operational efficiencies. Regarding large model applications, constrained by computing power and costs, Guangyun Technology is currently pursuing dual strategies: continuing technological development while awaiting maturation of consumer-facing applications, while simultaneously utilizing large models for training and building enterprise knowledge bases to enhance customer service capabilities with brand and product expertise.
Rather than chasing technological trends superficially, Wang Yi advises merchants to adopt a comprehensive approach - integrating appropriate AI capabilities into standardized mid-platform operational frameworks through careful consideration.
This AI-oriented approach aligns with Guangyun Technology's long-term 'Major Merchant Strategy'. Large merchants possess greater potential for workforce optimization through collaboration, along with more segmented membership marketing strategies and data dimensions, making them more receptive to AI adoption. Currently, some of Guangyun's large model-based technological explorations have begun co-creation and implementation with leading e-commerce brands.
This has positioned Kuaimai Xiaozhi as a key factor in Guangyun Technology's comprehensive product ecosystem, thanks to its dual strengths in customer service and intelligent capabilities.
On the other hand, as the growth红利 of live-streaming e-commerce begins to stabilize, much of the e-commerce SaaS sector remains in the phase of adapting to multi-platform integration. The market lacks a mid-platform product centered on customer service, making Kuaimai Xiaozhi a significant player with substantial market education value and integrative competitiveness, even independent of Guangyun's client ecosystem.
Looking back, Guangyun Technology has focused on service areas ranging from e-commerce ERP to digital product management, digital assets, and intelligent design—all revolving around product management. In other words, during an era when product differentiation significantly drove organic traffic growth, Guangyun accurately anticipated and addressed trending market pain points.
Today, Kuaimai Xiaozhi has clearly stepped beyond the comfort zone of product-centric focus. Guangyun completed its AI transformation during the "Year of Large Models," once again leveraging disruptive technology to help e-commerce brands shift from product differentiation to operational differentiation. This also implies that the business value of e-commerce customer service is increasingly rising, alongside growing demands for low-cost yet highly professional human resources.
From the perspective of global SaaS development history, the strategic and technological directions of leading companies, though perhaps less impactful than the "ignition" effect of media iteration, are irreplaceable for the industry's "painless" transition into a rational and stable growth phase.
Guangyun Technology, by adhering to a top-down strategy focusing on large merchants, has gained a deeper understanding of the structural changes in the e-commerce industry and the differentiated needs across various categories compared to individual merchants. Therefore, exploring solutions with major clients and leading more merchants to "break through" has become one of its ecological responsibilities.
The launch of Kuaimai Xiaozhi represents a clear strategic move: transforming the customer service department, which had been marginalized over the past decade, from a mere process hub into a driving force within the e-commerce workflow. Other business operations have shifted from a linear chain to satellites orbiting around user communication.
It is foreseeable that, in the near future, while the next wave of e-commerce opportunities driven by new platforms or categories remains highly anticipated, for most merchants, seizing fleeting opportunities like live-streaming e-commerce will always be reactive. However, continuously adapting to post-boom steady growth and finding a sustainable niche in a rational and healthy business environment will be the true long-term test of operational strategies.
In the process of 'survival,' the ability to operate across multiple platforms is particularly important, as it helps brands expand channels and thereby diversify risks. This is also a path that small and medium-sized brands excel at for breaking through. At the same time, in the era of refined operations, multi-platform operations have become a much heavier strategy compared to the traffic红利期.
Currently, refined operations based on multiple platforms can no longer return to the years when simply投放 content meant being ahead of the competition. As operators, not only do they need a richer perspective on business processes, but they must also understand platform rules. Additionally, since each e-commerce platform has its own set of data tools, breaking down data silos is also crucial. Therefore, the SaaS solutions chosen by merchants need to have strong ecological interoperability.
From this perspective, Kuai Mai Xiao Zhi not only already has integrated processes designed for different platforms, customer service logic, and one-click deployment of large model tools suitable for multiple platforms, but it also has strong interoperability with ERP products under Guangyun Technology and digital asset management platforms like Shen Hui. In other words, considering the requirements of refined operations for data consistency, the Matthew effect in the e-commerce SaaS field will continue to deepen. The more single-point products, mid-platform solutions, and vertical SaaS are interconnected, the fewer repetitive pain points merchants will face due to全平台渠道.
Guangyun Technology's Integrated Customer Service Solution for Customer Service Middle Platform
"The customer service middle platform eliminates the need for customer service personnel to frequently log into different systems across multiple platforms, as all information is integrated together," said Wang Yi, emphasizing that data integration undoubtedly enhances efficiency.
Reportedly, in July of this year, a leading clothing merchant connected their ERP system through Kuaimai Xiaozhi, enabling intelligent order tracking based on ERP order status and inventory conditions. This resulted in a weekly increase of 200,000 in payment reminders, a 5% improvement in conversion rates, and a reduction of over 100,000 in logistics and express delivery losses.
On the other hand, as a leading manufacturer, Guangyun Technology excels in making its product ecosystem collaborative and fluid, rather than allocating resources through internal competition. This is why Kuaimai Xiaozhi quickly gained the capability to cover all categories and platforms shortly after its launch.
Undoubtedly, before the next e-commerce game-changer, akin to mobile internet or short videos, surfaces, users' expectations for consultative, communicative, and growth-accompanying services from e-commerce brands will not lower any further. For businesses themselves, rather than lamenting the market conditions, it's more productive to focus on adjusting strategies, delving deeper into user needs, and exploring more business scenarios.
As e-commerce service providers, at this stage, they should not solely chase their own valuation and growth. Instead, they should focus on actions that benefit the industry as a whole, exploring the unknowns of transformative technologies for the sector. Technologically, they should keep a long-term perspective, while in product capabilities, they should concentrate on the present.