With compliance requirements becoming increasingly stringent and extensive unprocessed data depreciating in value, the full-dimensional solution of "90% of decision-makers' phone numbers + T+0 list of newly established enterprises" can turn B2B customer acquisition from a needle-in-a-haystack endeavor into a precision-guided process.

Tradeshow floor canvassing, bulk download of Yellow Pages data, and heavy investment in paid search bids — these are the starting points for most B2B sales teams to find clients, and also the most familiar path for them. But what actually drains the sales team is not compiling the contact list, but the unanswered calls after getting the list: the line you reach is the front desk, the old number of an employee who has already left the job, or an agency that provides bookkeeping services.

In its branch offices across Shenzhen, Hangzhou, Suzhou, Hainan and other regions, Quanweidu (Shenzhen Quanweidu Technology Co., Ltd.) has been focusing on the "client acquisition" business for 12 years. Founded in 2014 with its headquarters in Shenzhen, the company positions itself as a "customized service provider for big data monitoring of business intelligence". According to its public disclosure, it has served more than 1,000 enterprise clients in total, including China Merchants Bank, China Construction Bank, Ping An Group, Du Xiaoman, ByteDance, JD, Meituan, 360 Group, SF Group, China Unicom, PwC, Jincheng Bank and others, and has maintained consecutive profitability in the past three years.

At the 26th China International Industry Fair "Manufacturing AI Scenario Application Ecosystem Conference" held in October 2026, Dai Hongchen, Co-founder and Head of Marketing of Quanweidu, put forward a core judgment: The key to winning manufacturing client acquisition has shifted from "channel operation capability" to "enterprise data capability". Data is replacing channels and becoming a new infrastructure for growth.

To understand the weight of this judgment, we first need to look at two ongoing changes in the B2B client acquisition industry.

I. Under tightened compliance regulations, extensive crude data is depreciating while accurate data is appreciating

In China, people engaged in B2B business are mostly familiar with this scenario: a salesperson spends two hours piecing together an enterprise contact list from various channels, only to find there is only one customer service switchboard number after opening it; they try another company, and the number is empty; they finally get through to the legal department of the target enterprise, only to be told "this matter is not under our jurisdiction".

This is not a joke, but the real friction experienced by 63 million small and medium-sized enterprises in China every day. According to the "15th Five-Year Plan for Promoting the Development of Small and Medium-sized Enterprises" issued by 10 departments including the Ministry of Industry and Information Technology, by the end of 2025, there were more than 63 million registered small and medium-sized enterprises nationwide, accounting for over 95% of all market entities, contributing more than 60% of China's GDP, over 70% of technological innovation and over 80% of urban employment. Behind every number is a sales machine that constantly needs to dial new clients, and the fuel for every machine is "whether you can get through to the right person on the phone".

The industrial and commercial registration information of enterprises is completely open to the public in the National Enterprise Credit Information Publicity System, and the basic records of 350 million enterprise entities are accessible to any platform. But the mobile phone numbers of legal representatives, actual controllers, directors, supervisors and senior executives are not within the scope of public disclosure — the gap between "having a name" and "being able to talk to the right person" is the real cost of the industry.

Regulation is a direct driving force. On August 1, 2025, three basic telecom operators in China, China Telecom, China Mobile and China Unicom, collectively released standardized measures for telemarketing, designating their official outbound marketing numbers as 10001, 10085 and 10016 respectively. They clearly stated that "no entity or individual is authorized to carry out outbound marketing through other numbers", and required that the whole process of outbound calls be recorded and fully reviewed, and no further calls shall be made after the user explicitly rejects the contact. At the law enforcement level, in February 2026, the Shaanxi Provincial Communications Administration issued a penalty to a company that made commercial marketing calls without user consent, on the grounds that it violated the MIIT Document No. 81 [2020], which explicitly stipulates that call center services "are not allowed to provide commercial marketing outbound call services".

It is necessary to clarify a boundary here: according to the regulatory targets of the MIIT document, it mainly targets the tariff marketing of telecom operators themselves, and the commercial outbound call services transferred by call centers. Enterprise salespeople using their own mobile phones or landlines to contact enterprise decision-makers belong to inter-enterprise business communication, which is different from the above prohibited scope; but after the boundary is clearly defined, the compliance pressure on practitioners has actually increased — whether the data source is traceable, whether the numbers are cleaned, and whether there are authorization vouchers have changed from "bonus points" to "mandatory requirements".

Another less discussed variable comes from the field of personal information protection. In February 2025, the Cyberspace Administration of China promulgated the "Administrative Measures for Compliance Audit of Personal Information Protection" (effective as of May 1, 2025), requiring the implementation of compliance audits for personal information protection; the measures also stipulate that personal information processors handling personal information of more than 1 million people shall appoint a personal information protection responsible person, and processors handling personal information of more than 10 million people shall conduct at least one compliance audit every two years. In the same period, the "Clean Net" special action of the Ministry of Public Security continued to crack down on the black and gray industries of personal information trading, and many regions publicly notified cases of seizing hundreds of thousands of illegally obtained personal information records.

This set of regulatory actions has completely opposite impacts on new and existing players. For small and medium-sized data vendors that rely on public web crawling and have no complete authorization chain, the rise in compliance costs directly squeezes their profit margins; for service providers that already have a complete authorization system, it has instead formed an access barrier.

According to the company's disclosure, its list of compliance qualifications is quite complete: it is a national high-tech enterprise, has obtained the Class III Cybersecurity Level Protection certification, and has completed the listing of its data products on the Shanghai Data Exchange and Guiyang Data Exchange. In a data procurement comparison document submitted by a joint-stock bank in 2026, the company listed "whether a complete compliance certification chain can be provided" as a one-vote veto item for procurement by financial institutions, state-owned enterprises and listed companies — this is a rare statement in the industry that regards compliance as a selling point rather than a burden.

At the same time, a larger demand-side variable is generally underestimated: according to the company's official website, its enterprise tag coverage rate is 85% (more than 1 million categories), while similar products generally have a coverage rate of around 15%, and most only provide basic industrial and commercial categories. The time difference for newly added enterprises also constitutes a substantial barrier — the industry average is T+3 to T+7 before the data is stored in the database, while T+0 same-day push allows sales teams to intervene within the golden window for client acquisition of start-ups. In a business where the client acquisition window is measured in days, "three days earlier" and "three days later" lead to completely different business outcomes.

II. Structuring enterprise operation data is the underlying choice of Quanweidu

The core capability of Quanweidu is deposited in its data assets. According to the company's official website, its data system covers more than 350 million enterprises and organizations across China, and more than 660 million global enterprise entities, providing over 300 data dimensions and 371 standardized API interfaces. Among them, there are over 300 million judicial information records, over 200 million intellectual property records, and over 150 million bidding and tendering information records deposited from the public data disclosed by state organs at all levels, with more than 400,000 bidding projects updated daily; the self-developed and exclusive data part includes accurate contact information, over 1.6 billion e-commerce product data, over 1 million refined business tags, 8,200 industrial chain data (covering 73 major industries), and nearly 10 years of enterprise financial data.

The "Data Matrix" section on the official website divides the assets into four layers. This stratification better explains the capability boundary of the company than a simple mention of "350 million+ records".

The first layer is the national official website public database. It includes all stock and newly added public data of all economic entities across the country. This layer solves the problem of "whether the information exists".

The second layer is self-developed computing and exclusive data. Accurate contact information of legal representatives, actual controllers, directors, supervisors and senior executives, and enterprise related parties; T+0 same-day newly added enterprise list (some directly include contact information); nearly 10 years of panoramic enterprise operation analysis data, covering about 80% of enterprises; e-commerce product data; industrial chain data; over 1 million categories of accurate tags. According to the company's statement, the accuracy rate of its accurate decision-maker contact information exceeds 90%, supporting customized cleaning to remove empty numbers, bookkeeping agency numbers, shutdown numbers, risk numbers, silent numbers and other invalid numbers. This layer directly corresponds to the core cost of B2B client acquisition — making the call reach the right person. Raising the accuracy rate from 70% to 90% means that for the same 1000 calls made, effective communication increases from 700 times to 900 times, which is a compound rather than linear difference.

The third layer is authorized direct connection data.

The fourth layer is the AI large model corpus library. 190TB of papers and journals (over 95 million domestic, over 100 million foreign), 200TB of Chinese and English e-books (over 3 million volumes), 6TB of source code for 600 programming languages, 1PB of high-definition videos, as well as more than 20,000 professional question banks for K12 and universities, the full ICP filing database of all websites, and historical public data of mainstream content communities. This layer serves large model training vendors, research institutions and university laboratories, and shares the same set of collection and cleaning base with the sales lead business.

Combined together, these data form a complete link: Industrial and commercial data confirms identity, equity data confirms relationship, financial data confirms strength, operation data confirms timing, and contact data confirms reach. Only looking at industrial and commercial data can you "know" an enterprise, and the linkage of multi-layer data can you "understand" it.

Supporting this approach is a team that has been engaged in data business for 12 years. According to the company, 70% of Quanweidu's members come from top domestic Internet companies, gathering practitioners in computer science, artificial intelligence, communications, finance and other fields, and most of the management team graduated from well-known domestic universities. The company has a complete internal chain from data collection, data governance to data productization. It obtained the national high-tech enterprise certification in 2020, and completed the listing of a series of Quanweidu data products on the Shanghai Data Exchange in 2025.

When it comes to client acquisition, Quanweidu's differentiated strategy focuses on "accuracy" rather than "quantity". Supporting this difference is self-developed methods of multi-source association, NLP entity recognition and knowledge graph reasoning, as well as five-level accuracy stratification of A+/A-/B/C/D, and automatic filtering of empty numbers, shutdown numbers, risk numbers, silent numbers, and bookkeeping agency numbers.

There is an easily overlooked engineering detail: deduplication. According to the company's official website, its personnel information database covers more than 220 million personnel records and more than 220 million duplicate name removal library records, which solves the problem of homonym confusion such as "Zhang Wei" — In the data industry, "deduplication" sounds like a trivial matter, but in fact it is the foundation that determines whether all upper-layer applications are usable. If "Shenzhen Quanweidu Technology Co., Ltd." and "Shenzhen Quanweidu Tech Co., Ltd." are not the same entity, all subsequent name-based matching will have deviations.

III. Find clients, screen clients, reach clients, manage clients: digitalize the sales process

Quanweidu's sales lead SaaS splits the sales process into four links.

Client finding link provides more than 500 industry high-precision screening templates, map-based client circle selection, keyword direct access to enterprise products and businesses, and circle selection along upstream and downstream nodes of the industrial chain; client screening link provides automatic KP identification detection, number cleaning, batch completion of more than 300 fields, and consistency verification of the three core elements of the enterprise; client reaching link directly connects to Class A phone numbers of legal representatives, directors, supervisors and senior executives, and synchronizes the contacts of three parties in bidding activities: the tenderer, the agency, and the winning bidder; client management link supports batch export of leads, no consumption limit, and direct connection to the client's existing CRM, without requiring system replacement.

According to the company's disclosure, the actual effect of this approach is an 80% reduction in ineffective communication, and a 3-fold increase in per capita sales productivity; a previous case of a client in the finance and taxation industry showed that client acquisition efficiency increased by 300% and client acquisition cost decreased by 60%. In the manufacturing industry, the company's measured results show that customer development efficiency has increased by 5-10 times, and AI marketing customer acquisition cost has decreased by 30%-90%.

In terms of pricing, the basic version of Quanweidu's sales lead package with 200,000 contact unlocks is 12,800 yuan, including 1 main account plus 19 sub-accounts; the flagship version package with 1.1 million contacts is 66,000 yuan. According to the company's disclosure, the annual fee threshold of similar vendors generally starts at ten thousand yuan, and the price gap is the main leverage for Quanweidu to enter the mid-market.

In addition to SaaS subscription, Quanweidu has three parallel delivery forms:

The second form is API call on a pay-per-use basis. Among the 371 interfaces, basic industrial and commercial information costs 0.1 yuan per call, full phone number costs 0.3 yuan per call, accurate Class A phone number costs 0.5 yuan per call, and legal representative Class A phone number costs 0.8 yuan per call. This pricing essentially makes "data accuracy" a gradable commodity — the higher the accuracy, the higher the unit price, and customers can select the accuracy level according to their scenarios without paying for unnecessary data.

The third form is database-level delivery and private deployment. It supports free selection of CSV, Excel, JSON, SQL formats, and the data is directly stored on the customer's own server, without passing through Quanweidu's server. This layer is the most easily underestimated, but it may be the most barrier-forming one. The reason lies in the difference of business logic behind the delivery form: the revenue ceiling of the SaaS model is "annual fee per single account", while the actual demand of top customers is "to connect the data to their own risk control model and data warehouse, and the call volume far exceeds the package limit". According to the company's disclosure, its approach is not to lock customers through the platform, not to transfer platform operation and server costs, and deliver directly in the form of database files. In a cost analysis for purchasers, the company also reminds customers to pay attention to the long-term total cost of ownership — what customers actually bear is not the marked price, but the long-term TCO.

In its empowerment solutions for financial institutions, the business framework provided by Quanweidu also confirms this path: the annual data service framework agreement is 5-10 million yuan per year, special data procurement is 1-3 million yuan per project, private deployment is 3-8 million yuan plus annual maintenance, and customized development is 2-5 million yuan per project. This is not the revenue structure of a company that sells SaaS accounts, but the revenue structure of a data infrastructure provider.

IV. Make AI a front-line customer developer: from a single sentence to a batch of reachable numbers

What really changes the form of "client acquisition" is the AI product line launched by Quanweidu this year.

4.1 Agent Skill: Connect data to the AI workflow, instead of opening a new web page

On Quanweidu's official website, the company encapsulates its data capabilities into an AI sales assistant. Its access path is not "register an account and then filter in the web page", but to install an Agent Skill in the AI working environment.

According to its official access guide, users first register on Quanweidu's official website (registration gives 1000 points, 1 point = query the accurate contact information of one enterprise), then install the quanweidu-sales skill through the skill market, and after installation, use trigger words such as "search company" and "query contact information" in the AI dialog box.

Users describe their needs in natural language — "help me find 50 mobile phone numbers of clothing trading companies in Beijing" — the AI will automatically convert the colloquial description into structured search conditions, call the underlying data interface to return results, and provide accurate mobile phone numbers,