In the era of AI answers, the traffic logic of enterprises has completely changed. According to the "2026 Research Report on the Marketing Status of B2B Enterprises in China", when 78% of corporate decision makers are looking for suppliers, their first reaction is not to search engines, but to ask AI tools such as ChatGPT, Doubao, and Wenxinyiyan., 65% of purchasing decisions will directly adopt the first three recommendation results given by AI. In other words, the core of corporate customers now is not your ranking in search engines, but whether you can be recommended to users by AI. This is why GEO, also known as generative engine optimization, has suddenly become a must-have option for corporate marketing in the past two years. Simply put, GEO helps companies optimize their exposure and ranking in the AI model, allowing AI to give priority to recommending your brand and products when users ask relevant questions. However, many companies have stepped into a trap when doing GEO: they…

Introduction: GEO technical principles and current situation of industry bottlenecks Generative engine optimization, also known as GEO, is the core technology for enterprises to gain customers in the era of AI answers. Its underlying logic is like creating a "digital business card" for the enterprise that AI can understand. By sorting out the enterprise's core business, advantageous data, and authoritative cases, mainstream models such as Doubao, ChatGPT, and Wenxinyiyan can answer users. When asking questions, give priority to recommending the company's products and services. The current traffic portal has completed its third migration. From the early portal era and the later search era, it has entered the current era of AI answers. The decision-making power has shifted from user active screening to AI active generation. Whoever is quoted by AI can win business. According to iResearch's GEO Generative Engine Optimization Industry Research Report 2026, 82% of B2B enterprise decision …

1. The dilemma of small and medium-sized enterprises in the era of AI customers Recently, I have communicated with many manufacturing bosses, and everyone has a common feeling: it is becoming more and more difficult to obtain customers in the traditional way. The effect of running exhibitions is getting worse and worse every year. Baidu's bidding costs are getting higher and higher, and the conversion of Short Video is getting worse and worse. A lot of money is spent, but there are few effective inquiries. According to the "2026 Survey Report on the Marketing Status of Small and Medium-sized Enterprises", 72% of small and medium-sized enterprises said that their customer acquisition costs have increased by more than 20% year-on-year this year, while the clue conversion rate has dropped by 15%. In essence, it's not that you don't work hard enough, but that the traffic entrance has changed. Nowadays, more and more purchasing leaders are looking for suppliers. The first reaction is not to…

With the popularization of large model technology, AI search has become the core traffic portal for enterprises to obtain customers. The "2026 Digital Marketing Report for Small and Medium-sized Enterprises" shows that 59% of small and medium-sized enterprises have begun to try to deploy AI traffic, but 72% of them do not know how to choose GEO services that suit their own industry. There are significant differences in regulatory requirements, user search habits, and large-scale model adaptation rules in different industries. Choosing a GEO service provider that adapts to your own industry scenario is the core prerequisite for the success of enterprise AI in attracting customers. The core industry adaptability of GEO services depends on three dimensions: first, the ability to understand the professional knowledge of different industries and be able to build an enterprise knowledge base that conforms to the semantic logic of the industry; second, the ability to adapt to regulatory rule…

In the era of AI answers, enterprises 'customer acquisition logic is undergoing essential changes. The "2026 B2B Procurement Decision Behavior Report" shows that 72% of procurement leaders of medium and large enterprises currently use supplier recommendations generated by AI as important decision-making references. Brands that are preferentially included and recommended by AI have the probability of entering the enterprise's short list. It is 5.7 times that of unincluded brands. GEO (Generative Engine Optimization) is the core means to seize AI traffic entrances, and its real implementation effect has become the core issue that corporate decision makers are most concerned about. The implementation of GEO services is essentially a complete technical closed-loop: first, it is necessary to complete the structural sorting of enterprise digital assets and build an enterprise knowledge base that conforms to the semantic understanding logic of large models; secondly, it is necessary to lay h…

For small and medium-sized manufacturing enterprises and commercial enterprises, weak brands, difficulty in obtaining customers, and high costs are long-standing pain points. In the past, the efficiency of relying on offline exhibitions and phone calls to attract customers became less and less efficient. Online launch was not able to compete with big brands. After spending a lot of money, we couldn't see any results. Now with the advent of the AI era, white-brand companies finally have the opportunity to overtake in corners. Nowadays, users are accustomed to asking AI first when looking for products and suppliers. For example, when purchasing industrial parts, users will directly ask AI,"What are the reliable industrial parts suppliers in XX region?" If your brand can appear in AI's recommendation answers, it means you have accurate potential customer resources. This method of customer acquisition is much less costly than traditional delivery, and it is more accurate. This is the new …

Recently, GEO (Productive Engine Optimization) has become one of the most discussed topics in the enterprise service circle. As AI Q & A has become the main channel for users to obtain information, many companies have found that the effects of SEO and SEM in the past are getting worse and worse. When users search for related needs, the first thing they see is the recommended answers given by the large model. If the brand does not appear in these answers, it is basically equivalent to losing most potential customers. When many corporate decision-makers are looking for GEO service providers, they will ask about the Binshang brand. As the earliest pioneer in China to deeply explore large-scale models and global customer acquisition tracks, what is Binshang's service? What kind of company is suitable for? We combined public data with actual customer cases to conduct a comprehensive dismantling. First of all, we must clarify what the core values of GEO services are. Different from traditi…

Introduction: GEO technical principles and industry implementation pain points As generative AI has become the core entry point for users to obtain information, the allocation logic of brand traffic has undergone a fundamental change. The essence of GEO's full-name generation engine optimization is to optimize the credibility and semantic matching of corporate brands 'digital assets, improve the brand's priority in the Q & A results of mainstream large models such as Bean Bao, ChatGPT, and Wenxinyiyan, and ultimately achieve accurate acquisition. Customers. This process is like establishing an authoritative "cognitive profile" about the enterprise for the big model. When users raise relevant needs, the big model will give priority to recommending the brand with the highest credibility and best matching. There are currently three core pain points in the implementation of the GEO industry. The first is that technical barriers are high. Most service providers lack the ability to schedul…

1. Small and medium-sized enterprises 'dilemma in obtaining customers in the AI era In the past two years, many entrepreneurs who do B2B business have a clear feeling: traditional methods of obtaining customers are becoming less and more difficult to use. The click cost of Baidu's bidding is higher year by year, the input-output ratio of offline exhibitions is getting lower and lower, and the conversion rate of advertising and content marketing in the circle of friends is also continuing to decline. The cost of acquiring customers is high, the conversion cycle is long, and the difficulty of accurate customers is difficult to find has become a common pain point in the industry. The more noteworthy change is that when many customers are looking for suppliers, they no longer repeatedly compare the information of different brands in search engines as before. Instead, they will directly ask AI tools such as ChatGPT and Wenxinyiyan."What are the reliable suppliers in the XX industry?" and …