KANZHUN LIMITED

Ladies and gentlemen, thank you for standing by and welcome to Qantuan Limited Second Quarter 2026 Financial Results Conference Call. At this time, all participants are in listen-only mode. After the speaker's presentation, question and answer session. Today's conference is being recorded. At this time, I'd like to turn the conference over to Ms. Laura Chan, Senior Manager of Investor Relations.

Please go ahead, ma'am.

Thank you, Officer. Good evening and good morning, everyone. Welcome to our second quarter of 2026 Earnings Conference Call. Joining me today are our founder, chairman, and CEO, Ms. Johnson Kong Zhao, and our deputy CFO, Ms. Wenbei Wang. Before we start, we would like to remind you that today's discussion will contain forward-looking statements, which have raised the management's current expectations and observation that involves known and unknown beliefs, identities, and other factors not under the company's control, which may cause actual results, performance, or a treatment of the company to be materially different. The company portion did not display undue reliance on forward-looking statements and did not undertake any of the actions to update the forward-looking information, except as required by law. Hello, everyone.

Welcome to the company's second quarter 2026 annual conference. On behalf of all our employees, management and board of directors, I would like to express our sincere gratitude to our users and investors.

Today, we will mainly report on three aspects.

The performance of the second quarter, the change in the growth strategy of the company, and the stock return.

Let's talk about the performance of the second quarter.

The company made 24 billion yuan in revenue in the second quarter, which is 14% of the growth. In terms of profits, after the second quarter cut out of the stock market, the business profit has been adjusted to 10.5 billion yuan, which has increased by 19%. The business profit rate has been adjusted to 43.8%, which has increased by 1.9%.

In second quarter, the company generated revenue of RMB 24 billion, up 14% year-on-year. In terms of profitability, adjusted income from operations, excluding share-based compensation expenses, was RMB 1.05 billion, up 19% year-on-year. Our adjusted operating margin was 43.8%, up 1.98% year-on-year.

As of June 13th, the total paid enterprise customers showing back 12 months reached 7.3 million, up 11% a year on year. 多个核心经营指标本季度创下历史新高 二季度多次制品APP端 The average user size of Yue Huo Yue has exceeded 70 million in the second quarter. The average number of large-scale risk-care job seekers includes both Liyang media and Kodan reporters. Once again, in an 113-day group, these are outcomes of the recruit. Next, I would like to explain how the companies will study users from higher tier to lower tier cities.

This year's second quarter is the fifth year of company IPO.

Investors who are familiar with us will remember that the company has been insisting for the past five years that the core driving force of company growth is user growth.

The second quarter of this year marks the first anniversary of the company's IPO. It matters for the many of us to remember that throughout the past five years, we have constantly maintained that the core value of the company's growth is user-awareness.

This is determined by market space. China has a nearly 500 million active business population with more than 40 million active businesses. BOSS JAPAN HAS SERVED ABOUT 300 MILLION PEOPLE IN ITS URBAN WORKFORCE AND MORE THAN 14 MILLION ACTIVE BUSINESSES. BASED FUNDING, BOSS JAPAN HAS CUMULATIVELY SERVED APPROXIMATELY 300 MILLION PEOPLE

AND FRUSTRATED 22 MILLION EMPLOYEES. EVEN FROM WHERE WE STAND TODAY, THERE IS STILL CONSIDERABLE ROOM TO GROW.

Secondly, this is decided by our model. BOSS only creates movement, recommendation, and treatment. Its priority is to greatly reduce the communication cost of recruiters and applicants.

Second, this is determined by our model. Both teams pioneered the mobile recommendations and direction model. I recall, this model substantially lowered the cost of communication between recruiters and job seekers.

This low-cost model has inspired tens of millions of Chinese companies to move from traditional recruitment to mobile recruitment.

This low cost model enables tens of millions of companies to shift from traditional recruitment to mobile internet recruitment, thereby visualizing and mobilizing recruitment on a large scale. For the vast majority of our enterprise users, the first time they used our services was also the first time they used online recruitment.

第三,這是由我們的優勢和需求決定的。 雙邊網絡效應給了公司強大的生命力。 雙邊用戶數量越大,種類越豐富,用戶所表達的越多, 用戶的互動行為越多,我們就可以更好的服務用戶。

Third, this is determined by our strength and user needs. Double-sided network feedback keeps the company strong and fatality. The larger the user base on both sides, the greater the variety of users, the more users express themselves, and the more users interact, the better we can serve them.

The process of promoting user growth is the process of continuously producing digital oil to promote the engine.

The process of driving the growth is also the process of continuously producing digital audio for the recognition engine.

Over the past several years, we have consistently seen that as marketing activities on both sides have increased, user outcomes currently have also improved. With the engine supported by AI, we saw not only that AI increased the engine's efficiency, but also that the engine helped AI quickly establish its data flywheel. Over the next five years, we will adopt different strategies for tier 3, 4, and tier 5 cities, and for tier 1 and tier 2 cities.

In Tier 3, Tier 4, and Tier 5 cities, the core driver of growth will continue to be user growth, and our most important objective will remain user penetration.

In Tier 1 and Tier 2 cities, while continuing to grow our user base, we'll add regional price increases as a growth factor. Regarding our service price, let's first look at the actual situation of Q2.

With regard to 20 of our services, let me first take a look at the actual situation in the second quarter.

This Q2 income is 24 billion. This number has 10 digits. Not bad. However, in Beijing, many jobs release a monthly price, which is the price of buying two cups of coffee.

Revenue in the second quarter was RMB 2.4 billion. That is a 10 billion number. It looks good. But here in Beijing, for many jobs, the price of a one-bump job post is just the price of two cups of coffee.

而每个月所发生的许许多多的达成, 它的单价只够买一瓶矿泉水。

And the value of many many neutral matches happens in every bond combined is only enough to buy one bottle of mineral water.

What do we mean by neutral match? For those who are less familiar with us, let me explain again. One of the achievements on our platform is equivalent to the fact that on other recruitment platforms, the applicant has issued a request to the specific recruiter, and the recruiter has confirmed and accepted the request. Such a double confirmation is what we call an achievement.

A neutral match on our platform is equivalent to a job seeker submitting an application to a specific recruiter on another recruitment platform, and that recruiter also confirming the acceptance of the application. That's why we call it a neutral match.

这样一个达成在北京,上海,深圳,广州,杭州,成都, In many cases, you can only buy a bottle of mineral water at 7-11.

It is a team study combination in Beijing, in Shanghai, in Shenzhen, in Guangzhou, in Hangzhou, in Chengdu, in Mexico. One such match, it was only one bottle of mineral water as added every time.

In order to make it easier for you to understand, I will give you the data of a mature market, a certain head recruitment platform. According to the public information, the click of the platform is about $25 to $1, and the transfer to a basic position is about $5 to $10.

To make this easier to understand, let us start data from the leading recruitment platform in a mature market. According to the publicly available information, one click on that platform costs approximately 0.25 to 1 USD, while generating one application for a basic stroke costs approximately 5 to 10 USD.

For such a basic position, how many candidates can achieve it? I don't have other internal data. I assume that the efficiency is relatively high. Every five candidates, the recruiter is willing to accept one. The price of an achievement is $25 to $50 per candidate.

I do not have data on how many applications with special dates rolling down in one-meter match. If I assume based on a high-efficiency case that it will prove its willingness to accept one out of every five applications, that will translate into $25 to $50 per-meter match.

So, friends, we can feel two things directly.

These, my friends, give you an intuitive sense of choosing. First, compared with developed countries, as the importance placed on talent increases, the human resources services industry grows. There is considerable room for Chinese companies to increase what they pay with such resources.

Of course, it takes time. Time is very important. For example, today in Beijing, a good software developer's salary is similar to that of a shareholder.

Of course, this will take time. Time is a powerful tool. One example is that today, the value of a valuable software engineer in China is roughly at the same value as the sitcom value.

Second, in Beijing, compared to other companies, I have seen that many companies have achieved a single price. It's about one tenth of a barrel of water.

Second, compared with one aspect of the enterprise plant in Beijing, I've seen that many enterprises have achieved a limit plant, which is about one tenth of a mineral water.

The total monthly employment cost of Junior Human Resources personnel could buy 1,000 neutral machines.

Therefore, we can say that, compared with Beijing, the service line in our field also has some potential to be improved. Put differently, if we do not reform this, the human resources service industry is destined not to be valued by companies. It is destined not to receive high quality resources and invite restraint.

Therefore, at the beginning of the second five years of IPO, the company's growth strategy changed to For the mature market, i.e. the first-tier market and part of the second-tier market, while improving user experience, gradually increase the customer's paid amount, including the reasonable increase in the paid rate and the reasonable increase in the single price.

Therefore, at the beginning of the second five years, the company's growth strategy has changed, which is based on the first-tier market and some second-tier cities to improve the user experience while gradually increasing the amount of passive payments in mature markets, including a regional increase in payment rates.

This process has actually been going on for a while. In fact, some of the growth we see now is the result of this process.

In fact, this is also one of the reasons why we predicted that the growth of the second quarter and the growth of the profit would be better in the previous quarter. In fact, it's also that in the last quarter, they would predict that growth and profit growth in the second quarter would be better. That's part of the reason.

This is the right time, right place to change the growth model, and everyone that patient has

played a critical role which mainly reflected in three elements.

First, the large-scale application of AI increased the platform's efficiency. Second, we have a lot of customers who are interested in our service, such as white-collar customers and blue-collar customers. We are very happy to have a comprehensive solution for AI interview, AI-assisted resume screening, and so on.

Secondly, some big customers in the white-collar or blue-collar factories agree very much that they believe that the AI-collared interview AI assistive, resume, filtering, and other competitive solutions are also helpful to them.

Third, the combination of AI and our platform business is actually consistent with the pursuit of recruiters and recruiters on the platform. In other words, the goal is not to achieve success, but to get a job.

The combination with our platform is actually consistent with the persistence of our speakers on the platform and within the router. That is to achieve not the goal to view the equipment, but to view the platform higher. This actually also talks about our closed loop business.

The closer to the entry of the service, The closer you are to the fee according to the entry fee, the closer you are to the service mode and the commercial mode. The company will continue to invest in this part of exploration. In the second quarter, the business related to A.I. negative energy and avoidance has achieved rapid growth.

This brings us to our closed loop segment. The closer our services get to the actual hiring stage and the closer we get to charging back on the process, Let me discuss shareholder returns.

Today, the Board of Directors has passed a resolution that this company will distribute $2.3 billion of annual shares. Since this year, the company has accumulated a return of about $3 billion, accounting for more than 4.7% of the total shares.

The board today passed a resolution approving the distribution of the annual dividend of $230 million. Since the beginning of this year, the company has repurchased approximately $300 million worth of shares, representing more than 4.7% of its total share capital.

In the year of 2026, the total amount of 5.3 billion RMB returned by the shareholders of Huaiyuan and Fenhong has exceeded 100% of the net profit that was adjusted last year and exceeded 50% of the net profit that we mentioned before.

In 2020, the company's total shareholder returns through share researches and visits amounted to $530 million exceeding 100% of last year's adjusted net income and also exceeding the 50% we previously committed to.

We share the benefits of the company's growth with shareholders. That concludes my remarks.

Next, our Deputy CFO, Wenbei Wang, will walk you through the financial details.

Thanks, Jonathan. Hello, everyone. Now, let me walk through the details of financial results of the second quarter of 2026. We continue to deliver a high-quality set of financial results this quarter, MARKED BY SOLID REVENUE GROWTH AND FURTHER IMPROVED PROFITABILITY. OUR REVENUE ACHIEVED ACCELERATED TREND, REACHING RMB 2.4 BILLION, REPRESENTING 14% YEAR-ON-YEAR GROWTH. RECRUITMENT DEMAND IN THE SECOND QUARTER REMAINED BROADLY STABLE. WE DROVE REVENUE AND PROFIT GROWTH THROUGH USER-BASED EXPANSION AND IMPROVED MONETIZATION FROM HIGHER VALUE SERVICES. The number of paid enterprise customers increased by 11% year-on-year to 7.2 million over the 12 months ended June 30, 2026. Importantly, the paying ratio among active enterprise users improved for the fourth consecutive quarters, reflecting our sustained progress in monetization. AR PPU output for the quarter increased 7% year-on-year, driven by more efficient and valuable services. including an expanded suite of AI-powered features which encouraged higher customer spending. Revenue growth was broadly balanced across different account sizes this quarter with both key accounts and small size accounts showing healthy momentum. Moving to the cost side, our total operating costs and expenses increased by 6% year-on-year to RMB 1.5 billion this quarter. Total share-based compensation expenses dropped by 19% year-on-year to RMB 186 million. As percentage of revenue, share-based compensation expenses continue this downward trend to 7.8% this quarter, down 3.1 percentage points year-on-year. We expect share-based compensation expenses as a percentage of revenue to remain at a high single-digit level for the full year of 2026. In the second quarter, we sponsored the FIFA World Cup and increased our investment in AI-related cloud services. Meanwhile, our headcount grew sequentially, driven by stable growth in recruitment demand. Despite these investments, our profitability continued to improve. Excluding share-based compensation expenses, our adjusted operating margin expanded by 1.9 percentage points year-on-year to a record high of 43.8%. This was primarily driven by our strong operating averages, disciplined execution, and ongoing efforts to enhance operating efficiencies through AI applications. Looking into each segment, cost of revenues increased by 2% beyond year to RMB 312 million this quarter. This increase was mainly due to higher survey and bandwidth cost partially offset by lower app store commission fees and improved operating efficiency as we widely leverage AI in our daily operations, verification, and customer services. As a result, our gross margin went up by 1.6 percentage points year-on-year to 87%. Sales and marketing expenses increased by 38% year-on-year to only $581 million this quarter. many due to the marketing campaign of 2026 FIFA World Cup, as well as an increase in sales employee rate expenses related to higher cash revenues. Our R&D expenses were RMB 431 million this quarter, up 3% year-on-year. Excluding share-based compensation expenses, our adjusted R&D expenses increased by 7% year-on-year to RMB 361 million. many due to higher cloud service fees and server depreciation expenses related to AI infrastructure investment. Our GM day expenses decreased by 30% year-on-year to RMB 219 million this quarter, many due to lower employee rate expenses. Interest and investment income reached RMB 1.6 billion this quarter, compared to RMB 157 million for the same quarter last year. This increase was mainly driven by investment income of around RMB 1.5 billion arising from the fair value changes of one of our invested companies which went public in January 2026. Income tax expenses were RMB 515 million this quarter compared to RMB 97 million the same quarter last year. This increase was also mainly due to RMB 367 million tax impact from the aforementioned investment income, withholding tax of RMB 20 million, as well as the RMB 10 million provision for the top-up tax under the OECD Pillar 2 rules and higher income from operations. Our net income reached RMB 1.9 billion this quarter, up 173% year-on-year, Excluding share-based compensation and net guidance from the aforementioned investments, our adjusted net income increased by 9% to RMB 1.03 billion. Net cash provided by operating activities was RMB 945 million this quarter, down 10% year-on-year. This decrease was mainly due to higher advertising and marketing expenditures and tax payment. as well as lower interest and investment income received, partially offset by increased cash collection from customers. As of June 30, 2026, our cash position, including cash, cash equivalents, short-term term deposits, and short-term investments, but excluding investments in securities, stood at RMB 18.8 billion. Our strong cash position and cash generating capability enabled us to sustainably deliver our shareholder return commitments. As Jonathan just mentioned, the board declared an annual cash dividend of approximately US$230 million, combined with over US$300 million in share repurchase. We have completed year-to-date, which represents roughly 4.6% of our total outstanding shares. Our total shareholder returns so far this year exceed US$530 million, representing an over 100% shareholder return ratio compared to the adjusted net income last year. Cumulatively, we have now brought back over 10% of our total shares outstanding. And now for our business outlook. For the third quarter of 2026, We expect our total revenues to be between RMB 2.41 billion and RMB 2.5 billion, a year-on-year increase of 11.4% to 15.6%. That concludes our prepared remarks. Now we would like to take questions. Operator, please go ahead. Thank you.

To ask a question, please press star 11 on your telephone and wait for your name to be announced. To withdraw your question, please press star 1-1 again. Please stand by while we compile the Q&A roster. We will now proceed to take our first question. And the question comes from the line of Timothy Zhao of GomezX. Please go ahead, Timothy. Your line is open.

Zhao Zong, Wenbei, good evening. Thank you for accepting my question. My question is about AI. First of all, can you please share further about the recent progress of our current AI products? What is the overall size of the closed service that we just talked about? We saw an improvement in the efficiency of AI for PPP. Can you share some of the measured indicators, including the feedback of users? The second question is about our large model NEMECO. We saw that the latest large model NEMECO 4.23B also achieved a very good result. Please share with us, compared to the previous model, which model do you want to solve the problem with? Compared to some of our target models, what are the differences in our focus points? I will quickly translate it. Thank you, Benjamin, for taking my question. My first question is regarding your AI monetization. Could Benjamin share more color on the latest progress of your AI product? For the closed-loop services that you just mentioned, could you share any color on the overall revenue scale? And how do you think about the overall AI impact on the matching efficiency? And is there any quantitative metric that you can share that would be great? Secondly, it's on your Nanbei Ge large-language model. I noticed that you recently launched Nanbei Ge 4.23b model. Just wondering what is the improvement versus the last generation, and how do you compare the latest model versus the top large-language model in the market, and what is your different position? Thank you.

In terms of AI search, it's not the same as our previous search process. In the end, some users just used our recommendation system. We don't know this user very well. He will use some searches to help himself. But the previous search, as we all know, its query is very short. And this large-scale model actually gives us a possibility. In fact, you can actually use a very, very long query. Of course, Tanghuan can use the method of multi-round conversation to physically see that your query has become longer. In fact, the system is gradually closing in on what you want to do. This is the ability of these large-scale models. So, long queries, long postings, and multiple communications form memory and storage. Indeed, it can help us to serve better with higher requirements. Using traditional recommendations and searches can't serve well.

Okay, thank you for your question. And about AI talent sourcing that we can't use, there is something slightly different. It is well known that when some of our customers started to use our recommendation system and we began to know them, he used some of the search functions to help himself. But the search functions, as we all know, the problem is the query is relatively short. And the large language model just gave us a possibility that you can use a very long query. And also, you can use multiple round of conversations to make it look like long. But actually, the system is just coming back to understanding what you really want. So that's the fundamental capability that large language model has. So a very long text and multiple rounds of communication that which can come out to understanding of our customer demand and better to serve some clients who have high requirement, who have the requirement for high professionalism and which use a better traditional recommendation search model cannot serve. So that just brings our service capability to our next level.

And then on this basis, it is easier to understand the new value that AI sourcing can give us. As we all know, we have served more than 300 million Chinese users. In fact, last month, there were only 70 million active users. As the penetration rate of our covered users is getting higher and higher, in fact, the number of 70 million to 3 billion may become 1 billion to 4 billion. In fact, there are many users that are in some form sinking beyond the number of active users. At this time, the value of AI sourcing becomes more prominent.

So based on that fundamental we just discussed about, it's quite easy to understand the new value AI sourcing has brought to us, which we have already served more accumulatively, more than 300 million users, but our monthly active users last month is just 17 million, and we further penetrate to new users, The 17 million monthly active users versus 300 million total users might turn into like 100 million versus 400 million. So this creates a capability that we can expand our service to a lot of new users that are not within the monthly active users scope.

So who needs to be the most in touch with this, what we call, the bottomless pit? In this process, this is one of the reasons why we can use AI to supplement the work of a headhunter.

So the interesting part is who has the most need to contact this kind of silent customers. So this kind of customers or this kind of job seekers actually is more senior, more professional, and more likely to be liked by the headhunters. So the headhunters always try to contact them. So in this process, This is part of the reason we are applying this function to both our own and third-party headhunters' workstreams.

In this regard, we are talking about the process of pursuing a closed loop. I would rather see a closed loop as a process of one loop after another. In fact, AI has already helped the AI sourcing candidates on our platform. In fact, we also use AI to help customers select resumes. In fact, there are more than 10,000 interviews with AI interviewers on our platform every day. So this is more and more about getting close to our pursuant of closed-loop service. So my understanding of the closed-loop service is more like just a

One stage to another stage, the process of interlocking. So we are using AI to help our customers to sort attendance. We are using AI functions to help them to screen resumes. Our AI interview functions are now working on more than 10,000 interviews every day. Stage by stage, we are getting more and more close to our onboarding and AI is just helping us to accelerate in this process and achieving our goal.

Nanbei Ge 4.2 has a 3D model, which is quite a coincidence. This morning, there is a well-known organization. Nanbei Ge, 4.23B is quite a coincidence that early today a very well known testing institution ARTIFICIAL ANALYSIS is a well-known one. It is a collaboration between Liquid AI and iPhone 17 Pro and Samsung Galaxy S26. A very well-known testing institution, artificial analysis, they combined with liquid AI to join the testing on small-sized model

on both iPhone 17 Pro and Samsung Galaxy A26. So Nanbei Go 4.23B has achieved just number one in five areas, including following the two transforming orders, scientific illusion, scientific interference, and the mathematics theoretical areas. So Nanbei Go has achieved number one in all those five areas.

In the previous version, Nanbei Ge 4.1 3B actually had a good result. It was mainly based on better push-and-pull cooperation and the ability to use basic tools. Today, the one that was tested was Nanbei Ge 4.2 3B. Actually our previous model 4.1 3B also achieved quite nice results. So this model has been quite good in inference.

We believe that

On such a long road like AGI, it is a lot of work to burn so much power with such a large model and spend so much money. Besides, using a small model, can also solve specific problems and generate value in the industry. For example, in smartphones, cars, and giant smartphones, it has a lot of value. So far, Nanbei Pavilion has proven many times that we are at the forefront in the field of small-machine.

We believe on the road to pursue AGI, there is one way that mega-sized models super consuming of electronic powers, investing a lot of money, that a lot of big companies are doing. There's another way that maybe a smaller-sized model can help solving some specific and also create its own value. For example, the application in smartphones, on mobile vehicles, on intelligent robots, et cetera. In those areas, those smaller size model, we are in the leading position and have proven our value.

And that's our answers to the first two questions.

I pray that I proceed to the next one. Thank you. We will now proceed to take our next question.

And our next question comes from the line of Eddie Wang of Morgan Stanley. Please go ahead, Eddie. Your line is open.

Thank you for accepting my question. I have two questions. The first one is that Recently, the influence of Hongguan on us, especially in the second half of the year, because in this performance period, the performance of most Internet companies seems to have been affected by the negative influence of Hongguan and consumption. So I would like to ask, if we look at it from the perspective of BOSS, under such a situation of Hongguan, how much influence will we have? And if we can make adjustments to our own operations, to what extent can we eliminate, for example, some negative Hongguan influences? This is the first question. Thank you, management, for taking my question. My first question is related to the macro impact. What's your view on the macro impact on our company, especially for the second half of this year? As most internet companies that have reported second quarter results have mentioned the macro overhands and the weak consumption. To what extent will bots be affected under such a macro backdrop? How much of this micro-driven pressure can be offset through our operation improvement? The second question is related to the AI development. AI service and the product we have launched and probably will launch, do you expect they will have different cost structure and will this affect our overall margin? In addition, do we have plans to materially ramp up the CAPEX? As we have seen with some of the other Internet companies.

Thank you. Regarding the situation of Hongguan, I think I respect your professional observation. I will not go into details. From our point of view, we have seen all the days in the past 12 years of entrepreneurship. We have seen what you have seen. We have seen what you have not seen. Thank you for your question. Regarding the macro situation, I actually respect your professional observation and I won't talk too much about it. But I have been starting our business for more than 12 years.

and we have experienced a lot. Whether you have experienced or not experienced, we have all gone through that. So we have always maintained to be a very stable and maybe trustworthy business and we will continue to maintain this very stable operation. Let me talk about my opportunity.

One of my opportunities is So far, we have served more than 300 million users and 22 million companies. As we all know, the average life span of Chinese companies is relatively short. The average life span of Chinese companies is less than three years. We have a big opportunity here, which is our potential market size. We have served over 300 million customers and more than 22 million customers.

It is well known that the average life cycle according to the Central Bank of China's enterprise is less than three years. So within all those 22 million companies that have served, a lot of them are not active anymore. They have turned into new elements and beginning new companies.

Even if we use 40 million companies to calculate and observe, we still have half the space. Moreover, from the perspective of future development, new companies are born every year, and many of the companies we have served no longer exist, so this space will become larger.

So for ease of observation, even we consider those 40 million enterprises as a fixed situation, we have more than double of our market to grow. And on top of a lot of new companies are emerging every year, so our actual market size is even bigger.

And the second opportunity is in the paying ratio.

The annual number of enterprises is more than 10 million, and over 50% of them are using our service for free. So from that perspective, this is our second driver of second growth opportunities.

I will use a certain first-tier city as an example. Because in this meeting, we have reported to everyone what we might do in the next first-tier cities. I will use a certain first-tier city as an example. If it includes free services, then actually, So I will use the

One first-tier city, as an example, we just reported that we intend to increase monetization for certain first-tier cities. So in this particular city, including both paid and free service, the average cost per mutual match our customers can get for this city, for example, is like X RMB. And if we turn those free customers into our lowest level of paying customers, then those costs will go by at least 15%.

Please rest assured both our investors trying for public

Actually, this is a very minimal changes. I just explained that for a lot of our customers, the average cost to achieve a mutual matching is only the price of one mineral water at 7-Eleven. So either one bottle of mineral water or 1.15 bottle of mineral water is a very minimal cost to every enterprises.

So Ellie, I think just like we I am confident that we are not only surviving, we should and we will be better and better.

All right, thank you.

Thank you. Thank you. Thank you. Thank you. Thank you. follow the advanced big model company's so-called tail light strategy, and then choose our priority on AI applications, and then choose our priority on AI applications, and then choose our priority on AI applications, and then choose our priority on AI applications, and then choose our priority on AI applications, and then choose our priority on AI applications, and then choose our priority on AI applications, We don't have a dynamic cost structure that affects the company's management. We will maintain our current investment. As you know, our profit level is not bad. So our investment in the industry has always been at the level of 20% to 25% revenue. I think we will still be willing to spend money on it. In the second question, thank you, Eddie, for asking me that. So actually, all those large companies who have invested a lot of TAPEX for like

I think they have their ambitions, they have their beliefs, but most importantly, they have that financial capabilities. So for a company like us, when we chose the path of following or the tail light strategy, and we prioritize AI applications in the smaller size companies, that is our approach, our strategy to facing this AI Thank you for your trust, but I believe our investment in AI will not impact our overall cost structure and impact our operation capability and financial margins. So we will maintain current level of investment. And as you see, as you know, we have good profitability. So we will maintain around 20% to 25% of R&D expenses. And we will spend incremental money on AI and to give more support. But I will not sacrifice our safety on our cash flow. I won't do that. Just don't worry. And that's our answer to those two questions. Thank you.

Thank you. We will now proceed to take our next question. And the next question comes from Wei Xiong of UBS. Please go ahead, Wei. Your line is open.

Okay, thank you. Mr. Zhao, Wenbei, Laura, good evening. Thank you for accepting my question.

I also have two questions I would like to ask. First of all, regarding our company's profit and loss rate, it is very healthy. I am curious if it can lighten the help of our internal use of AI to increase the efficiency of our products. Thank you management for taking my questions. First, it's encouraging to see our margins have been maintaining at a very healthy level. So could we quantify the benefits from AI in our internal use to drive better efficiency and lower costs? And how much room of further improvement do we see? Also, after the investment in World Cup, how should we think about the investment plans, the expenses, and the margin trends in the second half? And second, could we please get an update on your overseas business, including the offer today, and how should we think about if there's any plan to expand into other markets? Thank you.

Thank you. I will take the first question on margin. So actually, we have been leveraging AI in all aspects of our daily operations, including security, notifications, sales, and marketing, and operating, and everything. But to quantify it, it may be more easier in the cost line. So since 2023, we have been witnessing that alongside with our user growth, Our overall headcount of operating employees maintained stable. So as a result, the employee-related cost as a percentage of revenue continued to go down and helped to contribute around two percentage points of our gross margin. So you can see our gross margin now stayed at a very healthy high 80s level, and we believe we still maintain this very high gross margin level. And for our outlook for the second half, yes, we have sponsored the FIFA World Cup, but the cost will be evenly distributed or recognized within second quarter and third quarter. And apart from that, we will maintain our current investment level of the cloud service rental cost for our AI model training. So we are expecting maybe in the third quarter, the margin level should be similar to the second quarter And for the full year, as we expected at the beginning of this year, our overall adjusted operating margin can still slightly increase.

Thank you for your interest in OfferToday. OfferToday, we would like to add another 5 years from now. We hope that OfferToday can bring 1 to 1.5 billion RMB of revenue to the company every year. This is our confidence in the Hong Kong market. At the same time, we think this is a mid-range, not so fast and not so slow. In the next five years, there will be a revenue of about $100 million to $150 million. This is our view on Hong Kong.

Thank you for your concern about offer today. So our current goal for Offer Today is in like maybe five years from today, it can bring the company with 100 to 150 million US dollars of revenue about the market size of Hong Kong. So we call it like maybe a middle dish, not too fast, but not too low.

And then similar to this middle, I think we can still look at some big cities. Offer Today, In a big city, it takes 2-3 years to get used to it, and it takes about 5 years to grow. In the 6th year after 5 years, it can bring a revenue of $100 million to $150 million. We think this is a city worth investing in. These are some of the places that Off Today is going to. I think the places it might be going to, such as Chinese cuisine, may include some developed Asian big cities to avoid the high-risk geopolitical factors. These are the big cities in Asia and Europe that are relatively developed. This is the inspiration offered by OfferToday. Simply put, it is a three-year trial period, a five-year development period, and a revenue of $1 to $1.5 billion as a city market or a city cluster market. This is our standard idea. Let's see how many of these cities there are.

And the lessons we learned from Offer Today is that it took around like two or three years for a new business like Offer Today to enter into the market and then the next additional five years to grow to achieve like 100 to 150 million US dollars of revenue. So we consider this kind of place or this kind of city worth investing. Of course, those cities are in Asia and Europe. Of course, we need to avoid those high geopolitical risk areas. So to sum up, two, three years of adoption and mature five years of development, there are still a lot of cities of this size and worth investing.

In addition, we have some slow food, which is to watch for a long time, about 10 years, 10 years to 15 years. I also hope to have a similar income like just now. Then the picture of such a market is probably that the average age of the people is relatively young. It is a young country. It is a relatively interesting developed country. Their population is close to 100 million, or a little bit smaller. So if you look at it from this perspective, it should be like Vietnam, like Argentina, like Brazil. After 10 to 15 years, we hope that the market will accept more of the model we have created, and at that time, we can bring a good profit to the company. So this is the big topic of OPPORT Day, which is to inspire our overseas business development.

And also we have some markets we call the slow dish, maybe take a longer term, around 10 to 15 years, which also achieve revenue like 100 to 150 million U.S. dollars. So the profile of this kind of market like maybe generally younger in the average age of the citizens in this developing country, but it's developing quite early, A total population is around slightly less than 100 million. So some places like Vietnam, Argentina, or Brazil. So in 10 to 15 years, we are hoping this kind of city can accept new models like we have created and bring about large profit revenue to the company by then. So this topic is about of today and what Thank you once again for joining us today. If you have any further questions,

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