Kanzhun Limited (BZ) Earnings Call Transcript & Summary

Ladies and gentlemen, thank you for standing by, and welcome to Kanzhun Limited Second Quarter 2026 Financial Results Conference Call. At [Operator Instructions] 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, operator. Good evening, and good morning, everyone. Welcome to our Second Quarter 2026 Earnings Conference Call. Joining me today are our Founder, Chairman and CEO, Mr. Jonathan Peng Zhao; and our Deputy CFO, Ms. Wenbei Wang. 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 risks, 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 cautions you not to place undue reliance on forward-looking statements and do not undertake any obligation to update these forward-looking information, except as required by law. During today's call, management will also discuss certain non-GAAP financial measures for comparison purpose only. For a definition of non-GAAP financial measures and a reconciliation of GAAP to non-GAAP 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 ir.zhipin.com. With that, I will now turn the call to Jonathan, our Founder, Chairman and CEO.

[Interpreted] Hello, everyone, and welcome to the company's second quarter 2026 earnings call. On behalf of all our employees, management and Board of Directors, I would like to extend our sincere gratitude to our users and our investors. Today, I will report [indiscernible] second quarter results, change in the company's growth strategy and shareholder return. In second quarter, the company generated revenue of RMB [indiscernible] 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%, 1.9 percentage points year-on-year. As of June 30, the total [indiscernible] reached record highs in this quarter. Average monthly active users or [indiscernible] exceeded 20 million in the second quarter. [indiscernible] Next, I would like to [indiscernible] how the company's growth strategy [indiscernible]. The second quarter of this year marks the anniversary of the company's IPO. [indiscernible] quarter, we have constantly maintained that [indiscernible]. China has nearly 500 million [indiscernible] with more than 40 active [indiscernible] and approximately [indiscernible] considerable room to grow. Second, this is the [indiscernible] mobile recommendation and direct [indiscernible] substantially lowered the cost of communication between recruiters and [indiscernible]. This low cost model enables tens of millions of companies to shift from [indiscernible] rationalizing and mobilizing improvement on a large scale. For the last [indiscernible], the first [indiscernible] our services was also the first time [indiscernible] online improvement. This is determined by our needs effect the company hospitality. The larger user base on both sides, the greater variety of users, the more users themselves and the more user interact, the better we can serve them. Over the last several years [indiscernible] on both sides have increased [indiscernible] has also improved. [indiscernible] Over the next first 5 years, [indiscernible] for Tier 3, 4 and Tier 5 cities and of course Tier 1 and Tier 2 cities. In Tier 3, Tier 4 and Tier 5 cities the core driver of growth will continue to be [indiscernible]. With regard to the [indiscernible], let me first take a look at the actual situation in the second quarter. [indiscernible] for those who are less familiar with us, let me explain again. [indiscernible] platform equivalent to [indiscernible] and that is also confirming the [indiscernible]. [indiscernible] automation, in Beijing, in Shanghai, in [indiscernible] Guagzhou, [indiscernible] translating to 25 to 30 [indiscernible]. Second, compared with one aspect of the [indiscernible] in Beijing, [indiscernible] the total monthly cost of premier human resources personnel could [indiscernible]. Therefor we can see that compared with Beijing, [indiscernible]. Consequently, even if we did not perform this, the human resources service industry is acting now to be valued [indiscernible]. Therefore, at the beginning of the second half year, the [indiscernible] has changed. [indiscernible] First, the large-scale application of AI increased the platform efficiency. Second, [indiscernible] in the white collar or blue collar factory [indiscernible] but we're very much -- they say that the AI power interview, AI activity, [indiscernible]. The convention with our [indiscernible] will continue to invest in following the area. One point worth mentioning is that the revenue of which [indiscernible] business grew rapidly quarter over quarter [indiscernible]. Let me start with shareholder return. The Board made [indiscernible] resolution improving the distribution of annual dividend [indiscernible], the company has repurchased approximately $300 million worth of shares, representing more than 4.7% of a total share [indiscernible]. The company total shareholder returns through share repurchase and dividend amounted to $530 million, excluding 100% of last year's adjusted net income. And as [indiscernible] we previously committed to. We share the [indiscernible] of the company's growth with shareholders. [indiscernible] 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 our 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 base 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 trailing 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. ARPPU. ARPPU for the quarter increased 7% year-on-year driven by more efficient and valuable services, including an expanding suite of AI-powered features which encourages 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 cost 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 196 million. As a percentage of revenue, share-based compensation expenses continue its 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 head count grew sequentially, driven by stable growth in equipment 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 leverages disciplined execution and ongoing efforts to enhance operating efficiencies through AI applications. Looking into each segment, cost of revenues increased by 2% year-on-year to RMB 312 million this quarter. This increase was mainly due to higher survey and analyst 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 RMB 581 million this quarter, mainly due to the marketing campaign of 2026 FIFA World Cup as well as an increase in sales employee-related 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, mainly due to higher cloud service fees and server depreciation expenses related to AI infrastructure investment. Our G&A expenses decreased by 30% year-on-year to RMB 219 million this quarter, mainly due to lower employee-related 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 in the same quarter last year. This increase was also mainly due to the RMB 367 million tax impact from the aforementioned investment income. Withholding tax of RMB 20 million as well as RMB 10 million provision for the top-up tax under the OECD [indiscernible] and higher income from operations. Our net income was RMB 1.9 million 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 payments 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 time deposits and short-term investments but excluding investments in securities, stood at RMB 18.8 billion. Our strong cash position and cash generating capability enable us to sustainably deliver our shareholder return commitments. As Jonathan just mentioned, the Board declared an annual cash dividend of approximately USD 230 million combined with over USD 300 million in share repurchase. We have completed year-to-date, which represents roughly 4.6% of our total outstanding issuance. Our total shareholder return so far this year exceed USD 530 million, representing over 100% shareholder return ratio compared to the adjusted net income last year. Cumulatively, we have now bought back over 10% of our total shares outstanding. And now for our business outlook. For the third quarter of 2026, we expect our total revenue to be between RMB 2.41 billion to 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.

[Operator Instructions] We will now proceed to take our first question, and the question comes from the line of Timothy Zhao from Goldman Sachs.

My first question is regarding your amortization. Could management share more color on the latest progress of your AI products? 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 impact on the matching efficiency? And is there any quantity of metric that you can share, that would be great. Secondly is on your, Nanbeige, large language model. Recently -- I noticed that you recently launched Nanbeige4.2-3B model. Just wondering what is the improvement versus the last generation? And how do you compare the latest model versus the top launch of the next model in the market? And what is your [indiscernible]?

[Interpreted] Okay. Thank you for your question. And about AI talent sourcing that we are currently using, there is something slightly different. It is well known that when some of our customers started to use our compensation system, and we begin to know them, we use some of the search function to help themselves. But the search function, as we all know, the problem is the query is relatively short. And the large language model give us possibilities that you can use a very long query and also you can use multiple round 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 have so a very long [indiscernible] 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 uses a better traditional recognition search model to [indiscernible]. So that does bring our search capability to our next level. So based on that fundamentally we just discussed about, it's quite easy to understand the new value AI sourcing has bring to us which we have already served cumulatively more than 300 million users, but our monthly active users last month is just 17 million and with as we further penetrate to new users, the 17 million month 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 some of the interesting parties who are the customers who would like to -- who have the most need to contact this kind of silent customers. So these kind of customers or this kind of job [indiscernible] 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, that's part of the rhythm we are applying this function to our -- both our own and third-party headhunter workstream. So this is more and more about getting close to like our pursuant of close loop service. So my understanding of the close loop service more like just one stage to another stage, the process of interacting. So like we are using AI to help our customer [indiscernible] we are using AI function to help them [indiscernible]. Our AI interview functions are now working on more than 10,000 interviews every day. So this 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 [indiscernible]. So for Nanbeige4.2-3B is quite coincident that early this -- today, a very well-known testing institution -- so a well-known testing institution artificial analysis, they combine with Liquid AI to do a joint testing on small-sized model on both iPhone 17 Pro and Samsung Galaxy S26. So Nanbeige4.2-3B has achieved just #1 in 5 areas, including following the 2 transforming orders, scientific elution, scientific interference and mathematic theoretical areas. So Nanbeige has actually #1 in all those 4 areas. Actually, our previous model, 4.1-3B also achieved quite nice results. So this model has been quite good in inference writing a fundamental advanced [indiscernible]. And on the contrary, 4.2-3B small-sized model better to handle more complicated agent to functions, including coding intelligence entity and maybe office working [indiscernible]. So we believe on the road to pursue AGI, that's one way mega-sized models super consuming of electronical powers investing a lot of money that a lot of big companies are doing. That's another way that maybe a smaller sized model can help solving some specific problems and also create value. For example, the application in smartphone, in mobile vehicles, intelligent robots, et cetera, in those areas, those smaller size model, we are in a leading position and have [indiscernible]. And that's our answer to the first 2 questions. Operator, let's proceed to next one.

And our next question comes from the line of Eddy Wang of Morgan Stanley.