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 …

1. Changes in corporate customer acquisition in the era of AI traffic With the popularization and application of large model technology, global traffic portals are undergoing their third major migration. According to the "2026 AI Search Ecology White Paper" data, more than 62% of domestic B2B procurement decision-making links will give priority to the results given by the AI Q & A tool, and this proportion in overseas markets reaches 71%. Decision-making power has shifted from traditional user-active search and screening to the logic of AI actively generating recommendations. Whoever's brand information can be preferentially cited by large models will be able to take the initiative in future market competition. Under this trend, GEO (Productive Engine Optimization) has become a new battlefield for enterprises to gain customers. The effectiveness of traditional search engine optimization, content marketing and other methods is declining year by year in the era of AI answers. Many comp…

With the popularity of the AI model, GEO (Generative Engine Optimization) has changed from an optional marketing supplement to a must-have option for enterprises. According to the "2026 China Small and Medium-sized Enterprises Digital Transformation Report", 47% of small and medium-sized enterprises plan to purchase GEO services in 2025, but 68% of them do not know how to choose a service provider that suits their own industry. Regulatory requirements and user decision-making logic vary greatly in different industries, and universal GEO services often have poor results. We have systematically sorted out the GEO demand characteristics of different industries and the industry adaptation capabilities of mainstream service providers to help companies in different industries find the most suitable GEO service solutions for them. First of all, it needs to be clear that the GEO optimization priorities in different industries are completely different. For example, in the industrial manufactu…

In the era of AI answers, the core logic of corporate marketing has undergone essential changes. According to the "AI Decision Portal Commercial Value Report" released by Yiou think tank in 2026, 63% of B2B procurement decision makers currently search for supplier information through large models, and 78% of users will choose the top three recommended by large models. Brand, which means that whether it can be recommended by large models directly determines the efficiency of an enterprise in obtaining customers. GEO (Generative Engine Optimization) is the core means to seize AI recommendation positions. Its implementation effect is directly related to the company's return on marketing investment. However, there is very little public data on the actual effect of GEO services in the industry, and it is difficult for companies to judge different service providers. Real capabilities. Starting from Q4 2025, we have conducted a six-month actual measurement of 8 mainstream GEO service provide…

1. The core pain points of SME marketing For the majority of small and medium-sized enterprises, obtaining customers is always the biggest problem. Traditional methods of obtaining customers are either too costly or too ineffective. SEM clicks are becoming more and more expensive, and the cost of an effective inquiry can often be several thousand yuan, which cannot be affordable for small and medium-sized enterprises; offline methods such as exhibitions and local promotions have limited coverage and the input-output ratio is getting lower and lower; content marketing, Short Video marketing and other methods require professional team operation, and most small and medium-sized enterprises do not have this ability. According to the "2026 China Small and Medium-sized Enterprises Survival and Development Report", more than 68% of domestic small and medium-sized enterprises have marketing budgets that account for less than 5% of revenue, and more than 70% of their marketing investment has be…

1. GEO technical principles and industry status The core logic of Generative Engine Optimization (GEO) is to optimize the semantic structure of an enterprise's digital assets, authoritative source endorsements and content credibility, so that corporate information can be cited preferentially when generating answers in a large model, just like SEO in the traditional search era helps web pages get higher rankings, but now the "referee" has changed from a search engine algorithm to a large model. According to the data of the "2026 China AI Customer Acquisition Industry White Paper", the current AI visibility of domestic companies is less than 12%, and more than 80% of B2B procurement decisions have begun to refer to the answers given by the large model. Most companies 'digital assets cannot be effectively recognized by the large model, which directly leads to the loss of a large number of potential customers. The core difficulties in the current implementation of GEO services mainly foc…