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Date

Tuesday, Nov. 18, 2025 at 7 a.m. ET

Call participants

  • Chief Executive Officer — Jonathan Zhang
  • Chief Financial Officer — Phil Yu Zhang
  • Operator
  • Board of Directors’ Representative — Wenbei Wang

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Takeaways

  • Total Revenue -- RMB 2,160,000,000 reported, representing a 13.2% increase year over year, with growth acceleration compared to the previous quarter.
  • GAAP Net Profit -- RMB 2,718,000,000, up 67.2% year over year; net profit margin was 35.8%.
  • Adjusted Operating Profit -- Grew 949.3% year over year, excluding share-based compensation expenses and other income.
  • Share-Based Compensation Expense -- RMB 216,000,000, reflecting a 21% decrease year over year and sequential declines for three consecutive quarters.
  • Paid Enterprise Customers -- 6.8 million for the last twelve months, up 13% year over year as of September 30.
  • Newly Verified Users -- Over 40,000,000 added from January to October; average verified monthly active users reached 63.82 million in the third quarter.
  • Enterprise User Activity -- Growth in average daily active enterprise users outpaced job seekers sequentially for the first time in three years.
  • New Job Positions -- 25% year-over-year growth in newly posted job positions during the quarter.
  • Blue-Collar Segment -- Blue-collar revenue contribution hit a record high; manufacturing sector led revenue growth for five consecutive quarters.
  • Revenue from Small and Medium Accounts -- Contribution rose by 2.2 percentage points in the quarter; overall ARPPU remained stable.
  • Gross Margin -- 85.8%, up 2.2 percentage points year over year and 0.4 percentage points quarter on quarter.
  • Total Operating Costs and Expenses -- RMB 1,500,000,000, down 7% year over year.
  • Sales and Marketing Expense -- RMB 394,000,000, a 25% year-over-year decrease; adjusted for sponsorships, decline was 15%.
  • Interest and Investment Income -- RMB 228,000,000, up 43% year over year, driven by partial equity investment disposal and increased income from the July Hong Kong share offering.
  • Adjusted Net Income -- RMB 992,000,000, up 34% year over year; adjusted net margin reached 45.8%, up 77.2 percentage points.
  • Net Cash from Operations -- RMB 1,200,000,000, a 45% year-over-year increase.
  • Cash Position -- RMB 19,200,000,000 as of September 30.
  • Dividend Payment -- Annual dividend of approximately $18,000,000 distributed in October.
  • AI Product Rollout -- Full deployment of AI job search assistant completed; significant quarter-on-quarter rise in user interactions and improvements in job seeker completion rates for AI-mock interviews.
  • AI-Driven Recruiter Services -- AI communication assistance feature integration boosted product mutual achievement conversion ratio by 7%.
  • Revenue Guidance -- Management forecasted Q4 total revenue between RMB 2,050,000,000 and RMB 2,070,000,000, implying 12.4%-13.5% year-over-year growth.

Summary

The company reported accelerated revenue and profit growth supported by a rebound in enterprise recruitment demand and robust user activity, punctuated by record gains in both blue-collar and manufacturing segments. Intensified penetration in Tier 3 and below cities contributed to expanding the enterprise customer base, while ongoing efficiency gains were attributed to AI integration within both operational and client-facing processes. Management highlighted sequential and annual improvements in contract renewal rates and net dollar retention, identifying these as indicators of a shifting trend. Dividend distributions and a strengthened cash position were achieved alongside cost reductions across most overhead categories, except for a one-off general and administrative expense due to intangible asset impairment.

  • CEO Zhang stated, "the paying ratio among quarterly active users increased both year on year and quarter on quarter."
  • CEO Zhang confirmed, "blue-collar revenue growth continued to lead, with its revenue contribution reaching a record high in the third quarter."
  • Management introduced new AI recruiting features to both job seekers and recruiters, with measured improvements in conversion and engagement metrics.
  • Management acknowledged, for the first time in the past two years, the company-level net dollar retention rate started to bottom up. This signals a potential turning point.
  • Greater small and medium-sized enterprise participation in the white-collar industry, along with a significant increase in newly added white-collar job postings, stabilized per-customer revenues.
  • CEO Zhang noted that, "the majority of our main pay-based customers are developed on our own rather than gaining shares from our peers," and cited significant untapped market potential within Chinese SMEs.

Industry glossary

  • ARPPU: Average Revenue Per Paying User; measures revenue generated per paying customer over a specific period.
  • Net Dollar Retention: A percentage indicating revenue change from existing customers over a defined period, factoring in expansions, contractions, and churn.
  • DAU to MAU Ratio: Ratio of daily active users to monthly active users, reflecting engagement and activity on digital platforms.
  • Mutual Achievement Conversion Ratio: Platform-specific term describing the rate at which recruiter and job seeker interactions convert into agreed-upon outcomes, such as interviews or hires, after introduction of value-added services.

Full Conference Call Transcript

Jonathan Zhang: Hello, everyone. Thank you for joining our company's third quarter 2025 earnings conference call. On behalf of the company's employees, management team, and board of directors, I would like to extend our sincere gratitude to our users, investors, and friends who have continuously believed in and supported us. I will briefly walk through our key operational results and business progress this quarter, focusing on three areas. First, recovery in demand through a priority growth in our third quarter performance. Second, the evolving characteristics of recruitment demands across different dimensions. Third, progress in integrating AI into our products, technology, and overall business operations. Let's start with the financial performance.

In the third quarter, we generated a total revenue of RMB 2,160,000,000, up 13.2% year on year, with growth accelerating from the previous quarter. Excluding share-based compensation expenses and other income, such as investment gains, our adjusted operating profit grew 949.3% year on year. Our GAAP net profit was RMB 2,718,000,000, up 67.2% year on year, with a net profit margin of 35.8%. Part of this improvement was attributable to a decrease in share-based compensation expenses, which was only RMB 220,000,000 this quarter, marking the third consecutive quarter of sequential declines and a year-on-year drop of 21%. The growth in the third quarter was driven by two key factors.

The first and most important driver was continued user growth, supported by our increasing penetration and expanding market share. From January to October, we acquired over 40,000,000 newly verified users. In the third quarter, the average verified monthly active users, which is amazing on the bus ticketing app, reached 63.82 million. User activity is also strong. According to such data, our DAU to MAU ratio has been maintained at a high industry-leading level. The second driver was the rebound in enterprise-side demand, which also helped improve data on the monetization side.

In the third quarter, the newly posted job positions increased 25% year on year, while both the number of recruiters posting new jobs and the average number of posts per recruiter grew steadily compared to the previous quarter and the same period last year. From July to September, the average number of daily active enterprise users grew at a faster pace sequentially than job seekers, marking the first time this has happened in three years. The supply-demand balance on our platform, meaning the ratio of enterprise users to job seekers, continued to improve. By September 30, the number of paid enterprise customers in the twelve months grew 13.3% year on year to 8.68 million.

Throughout the quarter, the paying ratio among quarterly active users increased both year on year and quarter on quarter. The second agenda item focuses on a service entry point for current demand this quarter from multiple perspectives. From an industry perspective, blue-collar revenue growth continued to lead, with its revenue contribution reaching a record high in the third quarter. Manufacturing industries remain the most robust sector, topping the industry's revenue growth for five consecutive quarters. Taking this opportunity, I would like to do a brief review. Three years ago, the company's strategy for serving manufacturing job seekers and recruiters divided into three stages in terms of priority.

The first stage is to improve the online job search environment for blue-collar workers. Between the passage of a solution for the same managed ticket or managed first and profit board second, we chose the second path. The second stage is to develop a user scale for that user base on the platform. And the third stage is to pursue commercial benefits on a reasonable scale. In 2022, we launched the Cont project to purify the job search environment for blue-collar workers, pursuing the authenticity of recruiters, job positions, and compensation, combating false information, and increasing their trust. Over the past three years, the process has been extremely challenging, and the results have gradually emerged.

Meanwhile, transportation, logistics, warehousing, and the service industries also delivered solid overall performance. Among the white-collar sectors, industries such as artificial intelligence, Internet service, lifestyle service, new retail, and gaming are experiencing leading growth. One thing worth mentioning among the white-collar segment is that we have noticed a notable increase in participation from small and medium-sized enterprises in the white-collar industry, with paying user numbers growing quickly, while the average spending per customer remains stable, which is an offset to the trend of previous patterns. This, to a certain level, reflects the arrival of the white-collar entrepreneur ecosystem.

From the perspective of compute-side demand, in Tier 1 cities is rebounding, Tier 2 cities remain stable, and the revenue contribution from Tier 3 and below cities continues to rise. Among enterprises of different sizes, medium-large enterprises, which means employers with between 500 to 999 employees, are growing the fastest, followed by small and micro enterprises, and then very large enterprises. The third agenda item reviews the progress we made since AI was integrated into the company's business from a product and technology perspective. On the Dosynchron service side, there are two things worth mentioning. First, after a period of continuous iteration, an AI job search assistant has been fully launched for all job seekers.

Currently, it can recommend positions for users, answer questions, and also provide suggestions on how to optimize their resumes. In the third quarter, not only was the full rollout of this product achieved, but the number of interactions per user with this AI job search assistant also showed a significant quarter-on-quarter increase. We have also been continuously optimizing the AI interview coaching feature. In the third quarter, the number of job seekers who completed the mock interviews showed further improvement, and their activity level and conversion rate continued to improve compared to the previous quarter. On the recruiter service side, multiple AI products have been gradually launched to provide services. There are four aspects to mention.

The AI communication assistance feature is being gradually integrated into existing commercial value-added products. As a result, the average mutual achievement conversion ratio of these products has increased by 7%. A product called AI Quick Hiring, after continuous optimization, is currently under phased rollout. Experiments show that this product not only helps the platform better understand recruiters' intentions but also allows for comparison among all job seekers on the platform, thereby improving matching accuracy. Currently, the reading rate among recruiters participating in the phased rollout campaign is steadily increasing. Third, we have extended the AI interview feature to a number of well-known customers from the contract recruitment side.

For example, the AI interview can support multiple rounds of questions and customize interviewer profiles. This product has very strong appeal to students, leading to a high volume of applications in the short term, which is increasing significant pressure for recruiters during campus recruiting activities. The development of AI services has alleviated this pressure. Fourth, we are cautiously exploring AI-hosted recruitment services and AI-powered bulk placement solutions in diverse recruitment scenarios such as high-end white-collar and gold-collar positions, and blue-collar roles in the patroning and manufacturing industry. These initiatives are gradually generating benefits.

Among all those enterprise-side AI services, we have been quite cautious to ensure we allow the job seekers to know whenever they are communicating with an AI service. They have the option to close the service. They have the button, and sometimes, someone might choose to close, but someone chooses to continue the communication, and we are continuously collecting related examples. We provide the option for job seekers whether they can communicate with AI or not to guarantee their interest. But, also, we are continuously observing with the intervention of AI what kind of impact it will have on mutual matching, not only on individual topics on a cultural perspective but also from a scalable double-side situation.

We are continuing to update and track data. In the third quarter, we delivered high-quality growth with solid progress across user growth, commercialization, and AI technology implementation. In October, the company completed an annual dividend payment of approximately $18,000,000. Looking ahead, we will continue to focus on strengthening our core business ability. We will actively fulfill our commitment to shareholders. That concludes my part of the call. I will now turn it over to our CFO, Phil, for the review of our financials. Thank you.

Phil Yu Zhang: Thanks, Jonathan. Hello, everyone. Now let me walk through the details of our financial results for 2025. In this quarter, we delivered high-quality and sustainable top-line and bottom-line growth. Our revenue reached RMB 2,200,000,000 this quarter, with growth accelerating to 13% year on year. The faster revenue growth this quarter was primarily driven by higher enterprise user growth as well as improved monetization levels due to the recovering hiring demand. Our commercialization strategy, grounded in ecological balance, enabled us to effectively and sustainably improve user payment ratios within a relatively better hiring environment. The growth in paid enterprise customers, which grew by 13% to 6,800,000 for the twelve months ended September 30, demonstrates our capability and potential to enhance monetization.

Revenue from middle-sized and small-sized accounts showed continued growth momentum, with revenue contribution in this quarter up by 2.2 percentage points, while key accounts growth remained stable. As a result of the structural mix shifting, the overall ARPPU maintained stability. Moving to the cost side, total operating costs and expenses decreased by 7% year on year to RMB 1,500,000,000 in this quarter. Share-based compensation expenses dropped by 21% year on year and 6% quarter on quarter to RMB 216,000,000, shrinking for the third consecutive quarters in both absolute amount and percentage of revenue.

Excluding share-based compensation expenses, adjusted income from operations grew by 49% to RMB 9,004,000,000, and our adjusted operating margin reached 41.8%, up by 10.1 percentage points year on year and relatively flat quarter on quarter. Cost of revenues decreased by 2% year on year to RMB 308,000,000 in this quarter, mainly due to the decrease in operational employee-related expenses as a result of improved operational efficiency as we continue to engage AI in our daily operations. Gross margin went up by 2.2 percentage points year on year and 0.4 percentage points quarter on quarter to 85.8%. Sales and marketing expenses decreased by 25% year on year to RMB 394,000,000 during this quarter.

As we do not have sports events or marketing campaigns this year, even if we exclude the sports sponsorship costs, our adjusted sales and marketing expenses in this quarter decreased 15% year on year, while we still maintain robust user growth. This double confirms our sustainable increase in marketing efficiency due to our strong brand recognition and network effect. Our R&D expenses decreased by 12% year on year to RMB 408,000,000 in this quarter. Excluding share-based compensation expenses, our adjusted R&D expenses decreased by 8% year on year to RMB 331,000,000 in this quarter and have stayed relatively flat sequentially.

Our G&A expenses increased by 28% to RMB 367,000,000 in this quarter, primarily due to a one-off impairment of intangible assets partially offset by a decrease in employee-related expenses. Excluding the impairment, our G&A expenses decreased both year on year and sequentially. Our interest and investment income in the quarter increased by 43% year on year to RMB 228,000,000, primarily due to partial disposal of an equity investment and the increased income from the Hong Kong dollar 2,200,000,000 Hong Kong share offering processed in early July. Our net income increased by 67% to RMB 775,000,000 in this quarter, with adjusted net income increased by 34% to RMB 992,000,000.

Net margin improved by 11.6 percentage points year on year to 35.8%, while adjusted net margin reached 45.8%, up 77.2 percentage points year on year. Both of them have maintained sustainable improvement over the past six consecutive quarters. Net cash provided by operating activities reached RMB 1,200,000,000 in this quarter, up 45% year on year. As of September 30, 2025, we continue to maintain a strong cash position of RMB 19,200,000,000. Now for our business follow-up, for 2025, we expect our total revenue to continue the growth momentum and reach between RMB 2,050,000,000 and RMB 2,070,000,000, with a year-on-year increase of 12.4% to 13.5%. With that, concludes our prepared remarks. And now we would like to answer questions.

Operator, please go ahead with the call.

Operator: Thank you. We will now begin the question and answer session. Please press 11 on your telephone keypad to ask a question. Please wait for your name to be announced. To withdraw your question, please press 11 again. We will now take our first question from the line of Eddy Wong from Morgan Stanley. Please go ahead, Eddy.

Eddy Wong: Thank you, management, for taking my question. I have two questions. First, what is the overall recruitment demand recently? We noticed that the unemployment rate in September and October is improving. Do you think this is mainly due to seasonal factors, or is the improving trend a leading indicator of macro recovery? What are the driving factors behind the accelerating growth in the third quarter? My second question is that as we are approaching the end of the year, what is your perception of the key account renewal willingness right now? Are there any noticeable trends in customer renewal rates or the renewal amount? Thank you.

Jonathan Zhang: From our data perspective, the recruitment activities from enterprises indeed recovered in the third quarter. The growth rate of monthly active users on the enterprise side is faster compared to the job seeker side. Pressure from the job seeker side has been alleviated. If we recall back in 2021 and 2022, it was a little bit difficult for fresh graduates to find a job. In the opening, whichever was affecting or not happening as we expected, young people, especially young people, found it really difficult to find a job. This year, take July, for example, the fresh graduates' expression for job-seeking demand compared to the same period of last year declined by double digits.

Meanwhile, from the enterprise side, the companies that have posted job openings for fresh graduates increased by double digits. From the situation on both ends, especially from the fresh graduate as an example, we quite clearly felt that the pressure which has been accumulating for several years was released a lot in the third quarter. In the third quarter, the ratio between job seekers and recruiters among active users improved compared to last year. The newly added user ratio also improved, and the third quarter is better than the third quarter of the previous year, which gives us continued confidence.

So it is quite easy to understand that based on the improving change of supply and demand balance, we treat the recovery of the enterprise side and the improvement of the pay ratio as helping our overall business operation. The first quarter last year was a relatively low base, so from a cautious perspective, we also compared it to 2023 in the same period. It is worth mentioning that the recovery of the white-collar sector, for example, the newly added number of job postings for the white-collar profession in the first quarter, increased significantly compared to the second quarter and the previous three quarters.

Based on all these observations and comparisons, I have the confidence to conclude in my prepared remarks that the improved hiring demand drove our third-quarter revenue growth. That is where my confidence comes from regarding the retention situation that you are concerned about.

Phil Yu Zhang: So, Eddy, you know, companies renew their contracts individually at different points in time, not only at the year-end. Starting from the year, we have witnessed improving contract renewal rates, improving continuously. Particularly in the third quarter, for the first time in the past two years, the company-level net dollar retention rate started to bottom up. This signals a potential turning point from a previous downward trajectory. We believe this is driven primarily by improved company retention rates and higher renewal spending. We observed that this situation is not only at the key account customers but also at the small and medium-sized enterprises. Typically speaking, the company's renewal contract renewal situation improved sequentially and annually.

This once again proved that the higher demand in the economy has been recovering healthily. And that is our answer to your question, Eddy. Operator, please move on to the next.

Operator: Thank you. Our next question comes from Wei Xiong from UBS. Please go ahead.

Wei Xiong: Thank you, management, for taking my question. Firstly, we observed that our company has continued outgrowing peers for the past few years. So if we look at the enterprise recruiting budget allocation, how much more share can we continue to gain over peers, and how do we sustain that above-peers growth going forward? Looking at next year, if the macro situation improves, will we continue to solidify our leadership, or is it possible to see higher competition pressure because the peers may step up investments? And secondly, on the margin side, given the high base this year, how do we think about the trend for our margin next year?

What are the major investment areas, for example, in terms of sales marketing, do we think about the spending plan there? And previously, given the macro uncertainty, we said we want to prioritize profitability. So looking at next year, are we going to continue prioritizing that profitability or leaning towards investing a little bit for growth? Thank you for taking my question.

Jonathan Zhang: I would like to start with our number of paid enterprise customers, which grew by 13.3% to 6,800,000 by the trailing twelve months. In fact, the majority, or maybe over 80% of these paid enterprise customers, are small and micro enterprises, which we use our own business model and go-to-market strategy developed over the years. By mentioning this, I would like to clarify two concepts. First, the majority of our main pay-based customers are developed on our own rather than gaining shares from our peers. The second concept is that there is data about China having over 40,000,000 small and medium-sized enterprises, and our entire enterprise cap number of paid enterprise customers is still a small percentage of that.

That is why even in a relatively tight macro situation, we still have ample room to grow in terms of our market share. The logical conclusion is that when the market recovers and demand improves, we can achieve better revenue and business growth rates. But on a competitive landscape perspective, we need to admit that for the customers both we and our peers are serving, especially under economic pressure situations, clients normally tend to choose service providers who have better ROI and higher service ability, and we do have some advantages over that. Regarding profitability, which you are concerned about, the current profit margin you observed is actually a strategic selection from our company level.

Last year, we decided that facing all of these uncertainties, we want to make sure that the only certainty is to guarantee profit, and this year, you have seen our very strong implementation capability and realized profit numbers. Essentially, this very strong margin profile actually reflects our effective double-sided network effect, further penetration into user mindset, and very efficient and smooth internal management and operation, all of which result in this high margin profile. As a result, I cannot predict if the profit margin for next year will continue to improve. Actually, we will not sacrifice our branding growth to achieve this profitability.

So for next year, we still want to guarantee us to be with the 35,000,000 newly verified users. Our pursuit in better serving users and achieving higher revenue growth actually has higher priority compared to our pursuit of profitability. Our strategic level view on our profitability, and we hope you and our investors can better understand what profitability means to us. For your reference, and that is our answer to your question. Operator, please move on to the next.

Operator: Thank you. Our next question comes from Timothy Zhao from Goldman Sachs. Please go ahead.

Timothy Zhao: Thank you, management, for taking my question, and congrats on the solid results. Two questions from my side. First, as Jonathan just mentioned, we are going to explore more in the different verticals within the recruitment industry. Could management share more progress and updates on this? And what are the potential impacts on our services and monetization in the longer term? Secondly, on the AI-related question, we noticed that OpenAI recently announced its entry into the recruitment industry. Some other AI startups like Merkur have also been evolving their business models. Could management share your view on the competitive landscape between the traditional recruitment platforms and the general AI companies in the recruitment industry? Thank you.

Jonathan Zhang: When we are trying to combine AI and human activities, we have some very interesting findings under our conjugate experiments. For example, when a customer is quite angry and cannot contain their temper while facing a customer service representative, they could be quite aggressive. But when the customer knows that the counterpart is AI, they normally take some very harsh words. So the beta complaint from the customer trained AI is, "You are very stupid AI." The second example is for our AI interview coaches product. A lot of job seekers who have used this service repeatedly to train their interview skills once and once again.

But we found out that when the job seeker's second scoring is lower than the first one, they will stop this repeat. So you can see the number of interesting findings in our daily experiment. People can control their temper well when facing AI, and also people do not want to bother a real human coach very frequently, but they can do that with AI. All these findings are telling us that when we apply AI technology to a very old, very ancient people and job matching, superior and subordinate matching scenarios, we need to be very cautious while using the new technology.

For more than two years, it is really exciting for a sampling model to be able to generate a killer-level application in our industry. Actually, we are not in a hurry, and it actually gave us more time to find a way to harness all this new development and technology. I just mentioned that in certain placement scenarios, both in blue-collar and white-collar recruitment, such as full-cycle hosting recruitment service or semi-cycle hosted recruitment service, we have been very actively trying out new services, but also quite cautiously. So far, we have some achievements, but still not in a stage to massively roll out this.

We also noticed that some leading technology companies who have been empowered by AI have expressed their interest in entering the recruitment industry. The new technology combined with old and the questions possibly can generate revolution-level industry change. Like the mobile network and recommendation technology combined with the traditional recruitment demand that have generated faster too fast. This new generation of online recruitment model. Up to today, my thinking is that the combination of AI and recruitment service's key bottleneck is actually not computing power. Merkur, who has in the bottom professionals to do the tagging, actually shows the value of high-quality data.

If high-quality data is very critical, then with the foster team, other peers within our industry actually have some certain level advantages. Just to leverage your question, I want to express some observations we noticed from our data operations. And that is all of our answer to your question, Timothy. Thank you.

Operator: Thank you. Due to time constraints, that concludes today's question and answer session. At this time, I will turn the conference back to Wenbei Wang for any additional or closing remarks.

Wenbei Wang: Thank you once again for joining us today. If you have any further questions, please contact us directly. Thank you.

Operator: Thank you for your participation in today's conference. This does conclude the program. You may now disconnect your lines.