洛克兄弟集团创始人张新刚：AI定制实现“先卖后产”，重塑骑行品牌增长模式

This article shares practical hands-on AI implementation experience from Zhang Xingang, founder of global cycling brand Rockbros. Key takeaways are as follows:

1. Companies do not need to pursue organization-wide AI adoption. Instead, they should introduce AI tools aligned with their development stage: prioritize cost reduction and efficiency improvement first, then gradually explore new business models, and avoid excessive anxiety around AI.

2. AI has already been deployed across multiple core business processes: In product design, what originally took 1-2 weeks to produce one rendering now allows designers to deliver three distinct design directions per day, a dramatic efficiency gain. In market research, AI can quickly compile demand reports for different regional markets. In marketing, AI can generate localized marketing materials for different regions in bulk, cutting costs and shortening turnaround times.

3. Rockbros is currently piloting an AI-powered made-to-order model that sells before producing. Leveraging its in-house flexible supply chain, the company can fulfill orders within three days. This model meets consumers' personalized demand while cutting inventory and upfront costs, and has already won positive reception from customers.

Rockbros' journey from cross-border seller to global brand, and its practice of AI-powered growth transformation, offers valuable references for peer brands. Key insights are as follows:

1. Brand transformation path: Starting as a trading seller, Rockbros gradually transitioned to its own brand. It first built product competitiveness through in-house design and R&D, then laid out its own supply chain and overseas localization, establishing local subsidiaries and overseas warehouses to address service and trust issues. The company has never engaged in fake reviews or order brushing, instead iterating products based on genuine consumer feedback, resulting in a very healthy current revenue structure.

2. Shifting consumer trends: Young consumers today have growing demand for personalized expression in cycling products. Traditional mass production models cannot meet this demand and are prone to resulting in excess inventory.

3. AI-enabled brand implementation: AI can be applied to product design, market research and marketing content production to cut costs and improve efficiency, and brands can explore the new AI-powered made-to-order model that sells before producing, which relies on in-house flexible supply chains to enable fast delivery.

Rockbros' growth from a small cross-border seller to a renowned global brand offers valuable guidance on growth directions for cross-border sellers. Key takeaways are as follows:

1. Transformation and growth opportunities: Transitioning from a trading seller to an own-brand business is a viable growth path. Rockbros made the shift to its own brand in 2013, and just one year later own products accounted for 60% to 70% of its total sales. It subsequently achieved balanced multi-market growth through supply chain布局 and overseas localization, with North America, Europe, and China each accounting for one quarter of current revenue, forming a very healthy structure.

2. Practical AI implementation path: Companies do not need to overhaul their entire operations with AI. Prioritizing AI application in specific processes such as design, research and content production already delivers significant cost reduction, efficiency gains and lower trial-and-error costs.

3. New business model opportunities: The combination of AI and flexible supply chains enables an AI-powered made-to-order model that sells before production. This model solves the pain points of high customization costs and heavy inventory pressure, while accumulating consumer data to inform product R&D, making it a promising new growth opportunity.

Rockbros' experience offers multiple insights on product transformation and digital upgrade for manufacturing factories. Key takeaways are as follows:

1. Shifting demand for product design and manufacturing: Consumer demand for personalized custom cycling products is becoming increasingly prominent today. Traditional mass production cannot match this demand and is prone to resulting in excess inventory, so factories need to adjust their production models to adapt to new demand.

2. New business opportunities: The core prerequisite for the new AI-powered made-to-order model is a fast-response flexible supply chain, as brands impose very high requirements on factory delivery speed. Rockbros requires factories to complete custom single-unit production and shipment within three days, so factories with flexible production and fast delivery capabilities will secure more cooperation opportunities with brands.

3. Insights for digital transformation: Factories can connect with brands' AI design and consumer data to achieve on-demand production, reducing their own inventory risk. Meanwhile, factories must strengthen quality control: Rockbros keeps its product defect rate below 0.1%, and high quality is the core foundation for long-term cooperation.

Rockbros' practice reveals the demand for AI-related services from global cross-border brands, and points out clear business directions for service providers. Key takeaways are as follows:

1. Industry development trends: A growing number of globalizing brands have moved beyond AI concept exploration to actual implementation. Most brands do not pursue full-enterprise AI transformation; instead, they prefer to use AI to solve practical problems in specific business links, with cost reduction and efficiency improvement as the core current demand.

2. Core pain points of brand clients: Under traditional models, brands face long product design cycles and high costs, low efficiency for multi-regional market research, high input for localized marketing content production across regions, and the pain points of high costs and heavy inventory pressure for personalized customization, all of which require urgent solutions.

3. Business opportunities: Service providers can develop professional tools targeted at segmented links, such as AI product rendering tools, AI-powered multi-regional market research tools, and AI tools for localized marketing material generation. Meanwhile, supply chain service providers with flexible custom production capabilities will also see growing cooperation demand from brand clients.

Rockbros' practice offers many insights for cross-border e-commerce platforms on operations, recruitment and service optimization. Key takeaways are as follows:

1. Core merchant demand for platforms: A large number of brand merchants are currently exploring AI application and new business models, and need platforms to improve listing rules, transaction services and data accumulation functions for personalized custom products, to lower the operational threshold for merchants adopting new models.

2. Platform merchant recruitment priorities: Platforms can prioritize recruiting global brands like Rockbros that grew from cross-border sellers, own independent supply chains, and have mature brand operation capabilities. These brands have strong growth potential, pursue integrated online-offline布局, can enrich platform product offerings, and elevate the overall product quality of the platform.

3. Operations management direction: Personalized customization is a key future consumer trend, so platforms can develop supporting rules tailored to this trend. Meanwhile, platforms should promote genuine reviews and crack down on fake orders and fake reviews, which helps improve overall platform trust and mitigate risks from false marketing.

Rockbros' practice is a vivid case of AI enabling growth for global brands, reflecting new trends in industrial development. Key research insights are as follows:

1. New industrial trends: The cross-border e-commerce industry has shifted from early-stage traffic-driven trade to brand globalization. AI has moved from conceptual discussion to implementation in specific business links, with cost reduction and efficiency improvement as the primary goal for corporate AI adoption. Unlike previous conceptual AI transformation pushes, most enterprises choose to implement AI in phases, prioritizing deployment in core business links.

2. New business model: The combination of AI and flexible supply chains has spawned a new AI-powered made-to-order model that sells before production. This model solves the pain points of high costs and heavy inventory pressure in traditional personalized customization, upgrading the conventional C2M model. It meets the personalized demand of young consumers while reducing operational risk for brands.

3. Directions for further research: The phased AI implementation path adopted by enterprises is particularly suitable for small and medium-sized brand transformation and offers high reference value. The growth path combining localization布局 and integrated online-offline operations for global brands, as well as the supply chain requirements of the made-to-order model, are all new questions worthy of in-depth research.