KANZHUN LIMITED

Ladies and gentlemen, thank you for standing by and welcome to country and limited first quarter, 2025 financial results conference call. At this time, all participants are in the listen only mode. After the speaker's presentation, there will be a question and answer session. Today's conference is being recorded. At this time, I'd like to turn the conference over to Ms. Wenpei Wang, head of investor relations. Please go ahead, ma'am.

Thank you, operator. Good evening and good morning, everyone. Welcome to our first quarter, 2025 earnings conference call. Joining me today are our founder, chairman, and the CEO, Mr. Jonathan Peng Zhao, and our director and the CFO, Mr. Phil Zhang. Before we start, we would like to remind you that today's discussion may contain forward-looking statements, which are based on management's current expectations and observations that involve known and unknown risk, uncertainties, and other factors not under the company's control, which may cause actual results, performance, or achievements of the company to be materially different. The company caution you not to place undue reliance on forward-looking statements and do not undertake any obligation to update this forward-looking information, except as required by law. During today's call, management will also discuss certain non-gap financial measures for comparison purpose only. For definition of non-gap financial measures and the reconciliation of gap to non-gap financial results, please see the earnings release issued earlier today. In addition, a webcast replay of this conference call will be available on our website at .gping.com. Now I will turn the call to Jonathan, our founder, chairman, and the CEO.

Hello, everyone. Welcome to our company's 2025 first quarter conference call. I would like to extend our sincere thanks to the CEO and CEO of the company to our investors in the first quarter of 2025. for their continued support and support

Hello, everyone. Thank you for joining our company's first 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. In response to key investor concerns, I would like to report on a few main topics. First, we have remained focused on driving profitability with encouraging results. Second, regarding the ongoing tariff war, which is a concern for many, my observation is that its impact on our business has not intensified. Third, we have continued to make solid progress on the AI front. Let me start with an overview of our financial performance. In the first quarter, the company achieved a gap revenue of RMB 1.92 billion at 13% -on-year. Our net income is $1.2 billion. The current revenue is RMB 510 million, reflecting a 112% year-on

-year growth.

Based on this, last year, we clearly proposed guaranteeing profits.

In the first quarter, the company achieved a gap revenue of RMB 6.9 billion. The current revenue is RMB 36%. Last year, the company achieved a gap revenue of 23%. The current revenue is 13%. Overall, this result shows the company's ability to achieve its goals and the excellent management leverage.

In the first quarter, the company achieved a gap revenue of RMB 6.9 billion. The current revenue is RMB 6.9 billion. The current revenue is RMB 6.9 billion. The current revenue is RMB 6.9 billion. The current revenue is RMB 6.9 billion. The current revenue is RMB 6.9 billion. The current revenue is RMB 6.9 billion.

The current revenue is RMB 6.9 billion.

Increasing profitability involves both cost control and revenue growth. With respect to cost, there are two things worth mentioning. First is the decrease of SBC expenses. Our share-based compensation expenses this quarter were down by 10% -on-quarter. As a proportion of revenue, this represents a narrowing of nearly 40% of the total revenue. We have previously predicted that the longer time passes since the IPO as well as the growth of our revenue, the impact of SBC expenses on profits will decline in both absolute value and percentage. This trend will continue.

The current revenue is RMB 57.56 million. The current revenue is RMB 24. In March, the monthly usage of the app is nearly 65 million. The number of single users is increasing in the same amount as the military.

Second is the improvement of marketing efficiency. From January to April this year, the company added over 15 million verified new users. In the first quarter, the average verified monthly active users on the Boss Jiping app reached 57.56 million, up 24% young year. Post-Chinese New Year, monthly active users in March approached 65 million. The average number of achievements per user continues to increase both -on-quarter and -on-year. We maintain robust user growth despite the decrease in marketing expenses benefiting from the two-sided network effects of our model and our continued focus on improving user satisfaction. Our core revenue growth drivers are still the growth of users and the increase in penetration rate. Therefore, revenue growth and user growth showed a highly correlated structural change.

First,

blue-collar new users accounted for over 45% of our total new users in the first quarter, driving their shares of revenue up to more than 39%. Second, alongside with the higher growth rate of new users among tier 3 and lower tier cities, the revenue contribution from tier 3 and below goes up by 3 percentage points to over 23%. Third, revenue from enterprises with fewer than 100 employees hit a record high contribution for the period due to the higher growth rate of the

smaller size companies.

Many people are concerned about the impact of the tariff war. We also take it seriously. So far, our overall conclusion is, with regard to the drop seeking and recruitment supply and demand relationship, no severe impact of the war has been observed so far.

In

general, we observed the growth of the new users in the first quarter of the year. The growth of the new users in the first quarter of the year is the same as the growth of the new users in the second quarter. The growth of the new users in the second quarter of the year is the same as the growth of the new users in the third quarter of the year. The growth of the new users in the third quarter of the year is the same as the growth of the new users in the fourth quarter of the year.

In general, we observed that hiring demand from enterprises has continued to show recovery trends since Chinese New Year. From January to April, average new job postings grew by 17% -on-year, while the paying ratio improved sequentially, posting total paid enterprise customers in the 12 months ended March 31 to 6.38 million, up 12% -on-year.

From the perspective of industry, which represents the sales of the retail industry, has been returning to the same level since April. The manufacturing demand has shown its resilience under the influence of tariffs. The new number of jobs increased since April, and the same growth.

The new retail has been continuously and steadily rebounding since April. Manufacturing requirements have demonstrated resilience despite the impact of tariffs, with the number of new job postings maintaining -on-year growth in April. Meanwhile, recruitment demand for white collar has also stabilized and begun to recover, with industries such as advertising, professional services, internet, finance and automotive leading in -on-year growth rate.

In terms of products and services, we continue to develop and enhance AI applications, and expand the scope and scope of AI users. Let me briefly explain this. In three aspects, AI2C, to job seekers, AI2B, recruiters, and AI2 management.

In terms of products and services, we continue to deepen application of AI technology, and expand the scale and penetration rate of AI testing users. Now allow me to expand on our AI development. We'll break it down into three key aspects. AI2C to job seekers, AI2B to recruiters, and AI2 management.

The first thing is that in the last meeting, we talked about a screening experiment. After the user searches, we not only give a search result, but also give some explanations about the result. This explanation is produced by AI. Why is this result? The overall result of the experiment is positive. So, we have already opened this feature to all users.

First, AI2C. The first item is the gray scale testing, also known as phased rollout, we mentioned in our last earnings call, which is after a user contacts a search, we do not only need to give the result, but also provide an explanation by AI why the result is what it is. Initial outcomes showed promising results, and we have now rolled out to all users. The second thing of AI2C, which we also mentioned during our last call, is our AI-powered interview robot designed to help users practice interview skills. Our experiments have shown that it can meaningfully enhance the recommendation system's understanding of individual user behaviors, and the outcome is quite significant. Now we have officially launched it for all students and young people with up to three years of work experience. Moving on to AI2Recruiters, one is the application of AI technology, which has to some extent supported our exploration in closed-loop services. The result is, in the first quarter, the number of enterprises we provide placement-alike services grew by about 30% -over-quarter. We are now starting to see some questions. The other one is an agent, which can interact with users. The agent can guide enterprise users convey their personalized recruitment demand and proactively search for suitable candidates across the platform. The agent is still evolving, but we have witnessed that this agent can effectively improve the matching accuracy. Enterprise users who have used the agent are seeing a 25% increase in achieving their efficiency in match recruitment results. That said, we remain extremely cautious about broadly expanding the robot's role of allowing it to somehow, even somehow, partially replace human recruiters. Our current strategy is as follows. First, we place no limits on building the recruitment boss capabilities. Second, we are extremely prudent about when and how widely we deploy the robot.

Let me talk about AI to Management. There are two things we can talk about. The first is some reforms we have made to the weekly newspaper. Now, after a person has finished writing the weekly newspaper, we have a self-taught AI that will help you summarize it. The third is

AI

to Management. There are two things to talk about. First, the AI to Management. The second is the reformation of weekly reports. Now, after one finishes their weekly report, we have our proprietary AI system to help create a concise summary version, which can still be revised by you. That way, you have two reports sent to your higher-up. One is a summative AI plus modified. The other one is your original version. Until now, the supervisor's behavior is trying to check the concise version first, then move on to the longer one.

If there are more than one person in the weekly newspaper, and the content is always more empty, and the words are more general, then AI will be a reminder. I understand that this is actually going to be valuable.

So that's some basic applications for today. The value, how to realize the value is, the AI will study your historical weekly reports, and also read across the weekly reports from related departments. If there are too many projects that are not closed loop, or the content is empty, or there are too many big words, the AI will remind you. This is a supplement to human capabilities. The second thing on AI-2 management is the use case for talent evaluation. When we merely rely on humans for performance appraisal, even so-called 360 degrees, there might be interference from two noisy sources. The first thing is for gaffer-ness. For example, a person's previous contributions will be downplayed, and recent performance will be more important. It's quite human natural, but this might not be appropriate as a long-term evaluation.

The second is that our intelligence is not very good.

The second thing is also quite according to human nature. So a homo sapiens will see what others want you to see. But

AI is objective. Under the pretext of protecting the privacy and dignity of an employee, AI can see the change in the performance and data of a longer-term objective. AI will not like a person because of his personality, nor will it like a person because of his personality. So from this perspective, AI will be a better chance for human natural management.

However,

AI is objective. Under the pretext of protecting an employee's privacy and dignity, AI can see the objective changes in past performance data. AI will not like an employee because it likes his character, or will not like his personality. So AI is neutral and impartial in terms of human resource application.

In conclusion, the three attempts and discoveries of AI in 2C, 2B, and 2M, are equally important in my mind. Overall, the first quarter of 2025 is not bad. The overall prediction is good. We will

continue to work hard. That concludes my part of the call. I will now turn it over to our CFO Phil for the interview, for the review of our financial. Thank you.

Thanks Jonathan. Hello everyone. Thank you, Phil. Now let me walk through the details of our financial results of the first quarter of 2025. We are delighted to record a solid start to the year, characterized by continuous expansion in our user base and engagement and sustainable revenue growth. In this quarter, our revenues reached RMB 1.9 billion, representing a 13% -on-year growth. We experienced a decent spring recruitment season with continuous improvement in enterprise hiring demand, evidenced by the growth of our cash collections, which has bottomed out from the last quarter. Revenues from key accounts and small sized accounts both contributed higher growth rates in the quarter. Our paid enterprise customers grew by 12% -on-year, to 6.4 million in the twilling 12 months, ended March 31st, primarily driven by the growth of enterprise users. Paying ratio among active enterprise users increased on a sequential basis, as the -to-demand situation of the labor market improved from previous quarter. ARPPU increased by 5% -on-year, mainly due to the expansion of paying amounts from key accounts. Moving to the cost side, total operating costs and expenses decreased by 8% -on-year, to RMB 1.5 billion in the first quarter. Share-based compensation expenses dropped by 13% -on-year, and 10% -over-quarter to RMB 252 million, shrinking for the third consecutive quarters. Excluding share-based compensation expenses, adjusted operating costs and expenses decreased by 6% -on-year, to RMB 1.2 billion. And our adjusted operating margins reached 36%, up by 13% points -on-year, a showcase of our disciplined cost control and a high operating leverage, despite Q1 normally having the lowest margin within the full year, due to seasonality. Cost of revenues increased by 5% -on-year, to RMB 311 million this quarter. Gross margin went up by .1% to 83.8%, compared to the same period of last year, as a testimony of our AI application to improve our operating efficiency. Sales and marketing expenses decreased by 15% -on-year, to RMB 491 million during this quarter, primarily due to decreases in advertising and marketing expenses and employee-related expenses. However, our strong brand recognition enhanced marketing efficiency and superior user engagement guaranteed that we can still maintain robust user growth momentum. Our R&D expenses decreased by 9% -on-year, to RMB 424 million in this quarter, and was relatively stable sequentially. This decrease was primarily driven by lower employee-related expenses and reduced public cloud expenses related to AI. Our G&A expenses were RMB 266 million in this quarter, remaining relatively stable both -on-year and -over-quarter. Our net income reached RMB 512 million in this quarter,

up

112% -on-year, while adjusted net income increased by 44% to RMB 764 million. Net margin improved to .6% up 12% -on-year, while our adjusted net margin increased to .7% up .6% -on-year. Net cash provided by operating activities reached RMB 1.0 billion in this quarter, up 11% -on-year. Our cash position totaled RMB 14.8 billion as of March 31, 2025. Our strong cash generation and robust cash position provide financial flexibility to execute growth initiatives and enhance shareholder returns. And now for our business outlook. For the second quarter of 2025, we expect our total revenues to be between RMB 2.05 billion and RMB 2.08 billion, with a -on-year increase of .0% to 8.5%. Please note this growth rate will also bottom out this quarter, driven by continued improvement of cash collection growth in the year. That concludes our prepared remarks, and now we would like to answer questions. Operator, please go ahead.

Thank you. We will now begin the question and answer session. To ask a question, please press star 1-1 on your telephone and wait for your name to be announced. To withdraw your question, please press star 1-1 again. We will now take our first question from the line of Eddie Wang from Morgan Stanley. Please ask your question, Eddie.

Thank you, Director Zhao, for answering my question. I have two questions. First, can you share with us how the tariff war has started to ease over the past month? From a macro perspective, have you seen the changes in the recruitment and recruitment requirements of the companies? And how has this change been changing? In addition, have you seen any recent growth in the recruitment and recruitment requirements of the companies? This is the first question. The second question is, if I remember correctly, after May last year, the macro situation has become more and more different. The recruitment and recruitment requirements of the companies have also begun to weaken. In comparison, what is the current trend of the recruitment and recruitment requirements in May this year? What are the changes in the different industries and companies? And this trend will not continue until the graduation of June-July this year. I will translate it myself. Thank you for taking my question. I have two questions. The first one is that, would you please give us a debrief of how the hiring demand evolved over the past month, from the start of the tariff war to the easiest? And have we seen any signs of the recovery in hiring demand recently? And the second question is that, if I remember correctly, after May last year, macro weakness coincided with a graduation season has led to a deterioration of recruitment demand. How does the current recruitment demand trend in April and May, compared with the same period last year? And have we seen different trends among different industries and different sides of the enterprises? Will the trend continue into the graduation season in June and July? Thank

you. Everyone

is concerned about this relationship. I will answer your first question. We mainly focus on the relationship between the recruitment of employees and the recruitment of employees. This is the most influential relationship for our platform. So, first of all, the overall trend of the recruitment of employees has been constantly changing this year. There is no doubt

about this trend. Thank you for your question. About the first one, which is tariff war everybody is concerned about, we are still looking from the supply and demand perspective of drop seekers posting job expectations and recruiters posting job postings. So this is the most important, most has the most high importance to our platform. In general speaking, the improvement, recovery of recruitment trend, continued recruitment trend is still the case. That is undoubtedly.

And then just now in the report, we talked about a general point of view. This is also a very serious point of view. The impact of the tariff war on the supply and demand relationship on my platform. My conclusion is that this impact has not expanded.

Objectively speaking, we have a quite diversified industry and location distribution. So the export relationship is still quite limited.

The data shows that the increase in the number of new employees in April and May and the number of new employees in the online world have maintained a good growth. There is no significant decline

compared to March. In April and May, the total number of new drop postings and active drop postings have kept a good growth rate. We haven't seen any significant fallback compared to March.

For industries which

affected bigger by the tariffs such as export related jobs, we saw some The second question regarding the overall equipment market. The overall supply and demand relationship has continued to improve in this year. Let's take a detailed look at the days after May compared to the same days after the Spring Festival. This year we saw a better growth trend compared to last year after May, especially after Labor Day holiday and after Spring Festival. Let's look at some detailed numbers. Since April till today, the number of newly posted jobs and the number of recruiters who posted jobs, the sequential trend is better compared to last year. Among which the blue collar sector, especially urban service blue collar sector, the young year growth rates continue to enlarge from March to May.

My feeling is that June and July will be good, because they will be

here soon. About our prediction for June and July, the graduation season, it's hard to say we can predict precisely, but according to my personal feeling it could be okay, since it's coming. That's my answer to your question, Eddie. Operator, let's move on to the next one. Thank you.

Our next question comes from the line of Timothy Zhao from Goldman Sachs. Please go ahead, Timothy.

I'm not sure when we can officially launch the AI currency tool and how we can measure its increase in revenue. The second question is about our revenue, especially considering the latest Hong Kong's impact and some changes in user growth and currency exchange rate. Will the expectation of the non-GAG operating profit of 300 million be changed? What measures will we take to ensure the implementation of the profit in the second half of the year? If we see a longer term, what will the company's future profit margin and how will it be considered? Can you share with us some of our capital allocation plans? I will quickly translate. Thank you, Madrin, for taking my questions. Two questions here from my side. First, we understand that the company has been internally testing the AI features for both enterprises and job seekers. Could Madrin share what is the feedback so far and what is the plan for the company to launch the AI monetization features? Secondly, considering the latest microenvironment as well as the monetization rate as well as user growth, I was wondering how does Madrin see the 3 billion RMB non-GAG profit target for this year? And into the second half, what are our leverage to make sure this 3 billion target is achievable? And what is the longer term market expansion role for the company? And additionally, could Madrin share about our plan for capital allocation? Thank you.

Thank you for your question. I will take the first one regarding AI and our CFO will answer the second question regarding the margin. So about AI, it's good to summarize that our series of phased out AI product testing has quite positive feedbacks. We have just mentioned. And this is based on that we have continued to be very cautious in terms of using AI. And I think analysts and investors who are familiar with us know our views. I have just mentioned that some of our testing products have already opened to all of our users. It's a gradual process.

But you asked me about this because it has something to do with money. When did you start a currency exchange with me? I can actually say a little bit. It's not money, but it has money in it. You can smell the money. I want to give you two data.

And regarding the monetization, I would like to share two data with

you. The first one is that when we use the AI recruitment function, the recruiters still have to work under the same amount of labor. We are not completely the same. Its achievement efficiency has actually increased by one-fourth. The

AI communication assistant has accumulatively served over 9 million conversations.

I think from the principle, it has improved efficiency, improved feelings, and saved time and labor. We can smell the money in this. But I would say that we are more cautious in terms of AI. I would see it as a slow-moving, but very efficient way to do things.

In principle, the AI product can improve efficiency, increase your user experience, and save you some time. But in reality, we are still quite cautious. My view is that we might be relatively gradually and slowly on the AI adoption of monetization,

but it must be some real money.

And then, Liwen, please. We have to start with the first quarter. We have to start with the first quarter. We have to start with the first quarter. We have to start with the first quarter. We have to start with the first quarter. We have to start with the first quarter. We have to start with the first quarter. We have to start with the first quarter. We have to start with the first quarter. We have to start with the first quarter. We have to start with the first quarter. We have started with the first quarter. We have started with the first quarter, but we still achieved satisfactory new user growth. We had a higher revenue, but our sales sky, number of our sales dropped. Our headcounts for RND, administrative cost and operation functions kept stable. So our internal AI tools keep the in for the platform's operation and verification jobs, which leads to improvement of our gross margin. You should know that our margin in the first quarter is the lowest due to the seasonality. With all the measures mentioned above, there's still room to improve in the second quarter, second half of the year. So we are confident with our 3 billion RMB non-GAAP operating profit target for the full year. This is the comment for the profitability and margin. Regarding the shareholder return topic, the company currently has more than 2 billion US dollar cash and equivalent on hand. We consider shareholder returns a very important topic and we like to do whatever fits us. Currently our share repurchase program is still ongoing and we definitely will continue. At the same time, we are studying and doing some assessments for other measures to increase our shareholder return. So please stay tuned. We would like to do it step by step.

Okay, that's our answer to those two questions and I'll bring it on to the next one.

Thank

you. Next

question comes from Wei Xiong from UBS. Please ask your question, Wei.

Okay, good evening, Mr. Zhao and Mr. Yu. Thank you for answering my question. I have two questions. First, I would like to ask about AI. We have seen that the human resources industry has also started to use AI extensively. Have you seen any changes in the competition pattern or potential changes? Can we use AI to further expand our service content? The second question is something we have been discussing in the past. We have also introduced the progress in the blue collar and summer market. I would like to ask the management to update us on the KPI in the blue collar. What are the progress in the new business we are dealing with? I will also translate it for myself. Thank you, Mr. Zhao, for taking my question. First, with the wider adoption of AI in the human resources industry, are we seeing any changes or expecting any potential changes in the competitive landscape? Can we leverage AI to further expand our service offerings? Secondly, could management share more updates regarding our blue collar recruiting business? What are the key KPIs for this year and how is our progress in the new business such as placement services? Thank you.

In the first question of how AI will impact the competitive landscape, my view is relatively conservative. My assessment is for this generation of AI technology and all the AI application we can observe from the market, we haven't seen any revolutionary or disruptive changes. So the competitive landscape is relatively stable.

But I also have a prediction. If the new generation of AI technology comes out in the human resources and recruitment industry, I believe the biggest driving force behind it is the new technology capabilities. And there is a possibility that the 1.5 or 2 generations of AI technology will be more likely

to come out. But I also have some predictions that if globally among the human resource industries there is a new generation of AI products can change the overall landscape, then there must be pushed by the new generation of AI technology, which may be like the 1.5 or 2.0 generation.

But we will still put a lot of resources in the AI field. For example, we bought more than 100 million chips last year, which allows us to create resources and

test-based push services in small areas.

AI is very high in the importance of AI and AI-rated investment. For example, last year, actually since 2023, we have bought more than 1 billion of chips, which is enough for us to conduct self-development research and small-scale inference. In terms of AI science, we still maintain a small-scale lab for us to be able to conduct pre-training of our own model and replicate all those open source models.

In

fact, we are actually quite confident that in terms of using AI science for AI application, our business scenario is actually quite suitable to to to advocate the power of AI. So,

in this process, we have seen the chat GPT, and we are still very curious about it. Today, we are more confident that this generation of large-scale models can already help us with our work. So, I think this work has become more realistic.

Compared to the first emergence of chat GPT, when we felt a little bit panic or curious at that time, now we have more certainty on the AI technology can actually help with our business and with

more real feelings.

And a more topic of view to share that a lot of online recruitment platform have long been pursuing the close-loop or placement service. Now, with the help of AI technology, we have more certainty to confirm that whether we can achieve close-loop service

in a big scale or not.

And with blue collar sector, new user contribution more than 45%, very new contribution more than 30%, we are very confident that we can achieve close-loop service.

I would like to use a word to describe our feelings when we are serving blue collar and low-tier services. This word will simplify things. Whether it is blue collar or low-tier services, the use of our software is very important.

And if we want one word to summarize our future efforts to serve the blue collar and low-tier users, our service and products will be more simple and

clear. I think the key point of blue collar is that we are spending resources and time on it. Now, I think the essence of blue collar is the reliability of efficiency and results. If so, then the AI technology will be more clear. I am also willing to do so because of the help that AI has brought to us. I am also willing to do so because of the help that AI has brought to us. We are still continuing to

invest. And in terms of placement business, especially on the blue collar placement, we have been spending a lot of resources and time. The key point is to guarantee the efficiency and reliability of your results. So if AI application can really help with those two aspects, then we do feel some confidence in this perspective. And that's why we want to further invest in this area. And that's my answer to your question. Operator, I think that's the last one due to the time constraint.

Thank you. Yes. Due to time constraint, that concludes today's question and answer session. So at this time, I'll turn the conference back to Wenbei for any additional or closing remarks.

Thank you, operator, and thank you everyone for joining our call today. And if you have any further questions, please contact our AI team directly or TPG in that relation. Thank you.

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