ZOZO Inc

TSE:3092

Earnings Call Analysis

ZOZO's Strong Financial Performance

In the second quarter of FY 2024, ZOZO exhibited solid financial results, with the Gross Merchandise Value (GMV) recording a year-on-year increase of 7.9%, totaling JPY 279.1 billion. When adjusting for other GMV, this core GMV also rose by 7.9% to JPY 260.8 billion. ZOZO's Operating Profit (OP) climbed to JPY 30.4 billion, reflecting a growth of 5.3% from the previous year, though the OP margin slightly decreased by 0.3 percentage points to 11.7%. This growth is significant, achieving approximately 45.6% of their planned GMV and 47.5% of the OP target for the fiscal year.

Seasonal Challenges and Adapting Strategies

Despite the overall positive growth, the company faced challenges due to unusually hot summer weather that subdued the launch of fall/winter products. Notably, the performance during summer sales in July and August was strong, but September's sales slowed down due to these climatic conditions. ZOZO is actively managing these challenges by adjusting their approach, with a focus on promoting items suited to the ongoing weather patterns through personalized recommendations on their platform.

Key Growth Drivers

The increase in OP can be attributed to several factors: a rise in GMV from ZOZOTOWN and LINE Yahoo Commerce contributed an additional JPY 5.15 billion, while enhancements in advertising revenues added JPY 0.98 billion. Furthermore, modifications in the shipping policy, which improved gross profit, accounted for an increase of JPY 2.13 billion. However, this was partly offset by rising costs resulting from an increase in fixed expenses such as employee wages and logistics overheads, which overall led to an increase in variable costs of JPY 2.76 billion.

Operating Margin Improvement

The OP margin improved slightly by 0.4 points year-on-year to reach 11.4%, largely driven by higher gross profits from robust sales in the advertising sector. ZOZO's latest shipping policy not only contributed to enhanced gross profits but also helped in surpassing the cost implications that arose from new logistical setups and the economic landscape. Moving forward, this improved margin shows the company's ability to adapt its operational strategies effectively.

User Growth and Engagement Metrics

In the second quarter, ZOZO expanded its user base significantly; the total number of buyers increased to 11.87 million, with active members growing by 110,000 to reach 11.02 million. However, an interesting point is that the number of guest buyers decreased by 30,000 indicating a shift towards more engaged purchasing. This highlights ZOZO's focus on building a loyal customer base, essential for sustainable growth in the competitive ecommerce landscape.

Future Strategic Directions with AI

CEO Kotaro Sawada emphasized the use of AI technologies in enhancing user experience and operational efficiency. Strategies include personalizing shopping experiences to improve customer retention and adapting product recommendations based on real-time weather data. These initiatives aim to further engage customers, particularly as seasons change. The company is also working on more advanced AI applications, including improved customer service support and data analytics, to better understand consumer behavior.

No Changes in Earnings Guidance

In its earnings forecasts, ZOZO has maintained its guidance, indicating confidence in its operational tactics and market positioning despite external challenges. The unchanged forecasts suggest a stable outlook for the remainder of the fiscal year, which may reassure investors of ZOZO's foundational strength amidst fluctuating market conditions.

Earnings Call Transcript 2025-Q2

[Operator]

It is time. So we would like to begin ZOZO's FY 2024 second quarter earnings briefing. The briefing will be live streamed only. And also, the session will last until 5:35. And after that, from 5:50 on a different Zoom channel, we will have a Q&A session for institutional investors. We introduce the presenters of today's session. President and CEO, Kotaro Sawada; and Executive Vice President and CFO, Koji Yanagisawa. Thank you. So we have two presenters today. Now Yanagisawa will take you through the earnings results.

[Koji Yanagisawa, executive]

Good afternoon. I will take you through the FY 2024 second quarter earnings results. The presentation material can be found on our IR site, so please take a look. I would like to jump right in and share with you our quarterly results. In FY 2024 second quarter, the GMV increased by 7.9% year-on-year to JPY 279.1 billion. GMV, excluding other GMV increased by 7.9% year-on-year to JPY 260.8 billion. OP increased by 5.3% year-on-year to JPY 30.4 billion, and OP margin was 11.7%, decreasing by 0.3 points year-on-year. Those are our results.

We have achieved 45.6% of our plan with respect to the GMV, excluding other GMV and 47.5% of the OP plan. With summers being hotter than last year, fall winter products started off slow, that's impacting the GMV. However, all of the businesses are, for the most part, on track. OP is also positive in comparison to the plan due to the unused variable costs as a result of the delay in promotion execution and fixed costs such as employee payroll and consignment fees. As of end of the first half, we have reached record high GMV in OP.

On Page 7 of the material. Here are the consolidated quarterly results. During the second quarter, the GMV, excluding other GMV increased by 8.3% year-on-year. September this year was even harder than last year. So the sales of fall-winter may sluggish, but we saw great results in July and August, especially during summer sales. With respect to OP, the GMV increase in the advertising business grew and we changed the shipping policy. This resulted in a higher gross profit which surpassed the increase in cost from the new logistics center and higher shipping costs due to the changes in the economic condition. Thus OP increased 11.6% year-on-year. The OPM was 11.4%, up by 0.4 points year-on-year.

Let me now take you through the business results in detail. Please turn to Page 8. Here is the OP increase/decrease analysis as of the end of the second quarter and year-on-year comparison. From JPY 28.93 billion in FY 2023 second quarter, the OP has increased by JPY 1.54 billion to JPY 30.4 billion. The OP increased due to three factors. First one, increased JPY 5.15 billion due to the increase in GMV of the ZOZOTOWN business and LINE Yahoo Commerce. They also increased JPY 0.98 billion as a result of the growth in the advertising business and JPY 2.13 billion due to an increase in gross profit resulting from the increase in shipping income arising from a change in the shipping policy.

On the other hand, OP decreased due to four factors. It decreased by JPY 2.59 billion due to the rise in fixed cost attributable to an increase in employees and logistics centers, JPY 2.76 billion attributable to increase in variable costs, such as cost increase in correlation to the GMV growth and increase in shipping fees. The OP decreased by JPY 0.81 billion as a result of increase in actual promotion-related expenses for customer acquisition initiatives and promotions using points and JPY 0.56 billion due to the increase in other expenses such as cloud server fees.

Now if you turn to Page 21, I would like to take you through the breakdown of the SG&A expenses. The SG&A GMV ratio was 23.6%, up 0.7 points year-on-year. Here are the reasons why the SG&A expenses have increased. There are three reasons. First, although the AOV has increased year-on-year, Yamato's shipping fee increase came into effect on April 1 this year. Thus, the shipping expenses has increased by 0.4 points. Second, depreciation of material handling equipment for logistic centers also ZOZOBASE Tsukuba 3 has begun, as depreciation has increased by 0.3 points. We also began incurring rent for ZOZOBASE Tsukuba 3 and for [ AOV ] Tsukuba 2. So the rent has increased by 0.2 points.

On the other hand, the SG&A has decreased due to the following two reasons. Automation and logistics centers has enabled us to have fewer people working in the centers, thus the logistic-related payroll expenses has decreased by 0.1 points. Second, the payment collection fee has also decreased by 0.1 point due to changes in the payment option composition.

Now on Page 24. Here are the trends in actual promotion expenses. This quarter, the percentage of actual promotion expenses, which include advertising and promotional spend and point-related expenses against the GMV was 3.9%. From the first quarter, we have pushed back our promotional spend, and we still have surplus budget in the second quarter. This percentage against the GMV has gone up by 0.1% year-on-year because we have spent more on web advertising and ran more free shipping campaigns for purchases over JPY 12,000.

Now if you turn to Page 20. This is the quarterly trend for OP and OPM. This quarter, GMV and advertising business growth as well as the increase in gross profit resulting from exchanges -- resulting from the change in the shipping policy have outpaced the increase in costs from the new logistics centers and shipping expenses due to changes in the economic condition. Therefore, the OPM was 0.4 points higher, landing at 11.4%.

Now I would like to talk about the KPIs for ZOZOTOWN starting with Page 25. These KPIs do not include the results of LINE Yahoo Commerce or the BtoB business. First, starting with the total buyers. The total buyers increased by 80,000 from last quarter to 11.87 million. Of that, active members increased by 110,000 from last quarter to 11.02 million. And guest buyers decreased by 30,000 from the previous quarter to 840,000.

In the second quarter, as was the case with GMV, we experienced severe summer heat. Thus, the growth in September was sluggish, but we were able to grow steadily from the third quarter.

Next page 28, the number of shops. As of the end of the second quarter, the number of shops were 1,621 with a net increase of 16 shops from the end of the previous quarter. In the second quarter, we welcomed 34 new shops, including Sweden's fashion brand, Acne Studios as well as Kao Group's “KANEBO” and luxury brand “BYREDO”. So they have joined our fold.

Next, moving on to Page 30. The average retail price was JPY 3,629, up 1.1% year-on-year. The brands continued to raise their prices. However, the launch of fall/winter products in September was sluggish. So the increase in the average retail price remained limited.

On the other hand, on Page 31, the average order value was JPY 8,196, up 3.8% year-on-year. More items were purchased per order, thus AOV increased more rapidly than the average retail price. The reason why the number of items purchased per order increased was because, as I mentioned before, we ran more free shipping campaigns for purchases over JPY 12,000 in comparison to last year, resulting in people buying more items together on the day of these campaigns. And this drove the number of items purchased per order upward.

Lastly, on Page 33, here are the consolidated earnings forecast and dividends. We have not made any changes to these plans. This concludes my explanation. Our President Sawada will take it from here.

[Kotaro Sawada, executive]

Good evening. Thank you. So usually, I talk about the strategy and the progress but in recent years, using AI and technology, we do receive a lot of questions about that. So we want to talk about how we intend to use AI and how we intend to automate our processes. So that's what I'll be covering today. So this is AI technology automation initiatives. So basically, we have -- we are embarking on various initiatives, but basically, we're focusing on these three segments. So we utilize AI to raise immediate sales and also automate our processes.

That's on the short -- you see these initiatives in the short term and also improvement of operational efficiency. So we're utilizing AI and LLM. So I would like to introduce some examples of our technology uses in that respect. And over the long term, as we're thinking about how we can use AI and automate -- automation technology, so I would like to cover that as well today.

So we'll start from short term first, introducing some case examples. First, within ZOZOTOWN, how do we -- how are we using AI? This is just one example. So we have two screens. This is the same top page -- ZOZOTOWN app top page. And this just shows how different it will be for individuals. So of course, we target the masses. So our products are catered to the mass, but of course, these are fashionable products that we handle. So I -- somebody who's in their 50s like me, like a gentleman -- we might have different preferences, I mean if I saw some fashion that were more catered to younger man, I might think that, that's not for me.

So we knew that, that has been a challenge. So we wanted to personalize for each individual. We've been focusing on personalization. And by doing so, we believe that this will improve our retention, that's our strength. So with respect to the logic behind this, we are, of course, making new adjustments every single day. So if you have time, please compare your top pages to see how different they are, it is to others.

Next. In recent years, climate or weather is -- has had significant impact on the fashion industry. In order to alleviate that impact, this is something that we've done. So simply put, depending on where the person is looking at the products from, we automatically show the right products for that weather.

So we're using weather use API. So we actually use a regional information, location data of that person who's looking at our site and we recommend a product that best fits the weather in that area. But in recent years, it's been quite warm. So there hasn't been that much of a regional difference, but it's becoming cooler now. So we hope that we expect that these functions will have bigger impact.

Next, the WEAR front page as well, we are implementing AI here significantly. This spring, we renewed the WEAR service. And on the top page, we will show styling photos that we believe that person will like. This is not just something that is similar. It's not simple technology as that. There's a lot of information that is included in the styling photos and fashion genre is very complicated. So we try to incorporate different information. We can define some style as girly or we define these fashions ourselves.

And based on that definition, and we use the browsing history as well to show images of styles that we believe our users -- individual users would like. So the more the user clicks on images, the smarter the AI will become and will learn. So it will continue to learn the users' preferences. So we hope that you will give this a try and continue to use it.

Next. This is not directly going to impact ourselves. This is a little bit more indirect. But over the last couple of years, we have put a lot of effort into our measurement technology. We started with ZOZOSHOES, ZOZOMAT and ZOZOGLASS. So you may remember our technologies. But over the last 6 months, we -- basically a new technology we've released is ZOZOMAT for kids. So these are recommendation -- with this, we can recommend kids shoes for children.

And what's most different from the traditional ZOZOMAT is that we actually took into account a childs growth trajectory. So we can say these shoes might be slightly bigger -- big now, but the child will be able to wear it for a year, for example, and this is very helpful, convenient to mothers with small children. So we hope that you will give this a try. And of course, we will utilize the data to see how that chart has grown. So we actually statistically analyze that child's data to make more accurate recommendations. So we focus on usage of technologies that contribute to sales or retention. But from here onwards, we want to use -- talk about Gen AI, we have a lot of data we are an Internet company, so we want to organize our data.

So we're utilizing Gen AI behind the scenes as well. So it's not really anything new. It's quite primitive, but we're utilizing Gen AI in all areas. So one example is the item review. We implemented reviews last year, and we need to monitor these reviews as well because sometimes it goes against the rules or our manners. So before we used to check the content of the reviews manually, but we can use Gen AI, and we can automatically patrol the content now. And thankfully, we were able to significantly reduce the time spent on these kind of tasks.

Moving on. This is the automatic categorization. You might not know what this is about. But on fashion, EC products, it's important to have products for and make sure that they go into certain categories because people search for items by selecting categories. As sometimes categories are in the gray and the sales will differ considerably depending on which category you categorize them in. So we can utilize Gen AI to automatically categorize these products out and choose the optimal category. So we implemented an automatic system that will enable us, the brands to do so as well.

And next, this is more about customer support. We use a BI tool that will actually -- we are using LLM to basically -- other companies may do so as well, but we actually look at the comments or the content of the inquiries and feed that into LLM. So the system is a dreamlike tool because we used to do it manually, but now the system will automatically categorize the type of inquiries. So we're using AI in that way. So -- and that was about making our operations more efficient.

From here onwards, we can go to the next page. Over the mid- to long term, we want to use LLMs in these areas. So this is just a direction. So first, we want to utilize it for niaulab. So this is just one physical store that we currently have. So this is a prototype to actually understand what looks best in people, but we want to use Gen AI as well. And we introduce somewhere as well but styling photos as well. We want to make sure that we can take fuzzy images and virtually recommend what the best looks are for individuals. So this might be difficult to understand if I just explain. So we have made this publicly available, but there is a video that -- what explains what we mean by this. So please take a look.

[Presentation]

[Kotaro Sawada, executive]

Thank you for watching. So that's what we have planned for the future. We haven't realized everything yet. But AI agents are going to be -- are right around the corner. So I think -- I also believe that as well as ZOZO, we want to create a fashion AI agent or stylist. So we're trying to do that and the technology and data. Of course, we believe that we have the right technologies and data to do so. So please look forward to what we have planned for the future.

Lastly, this is called REVINAL, so it's a virtual closing shop. So we're working on this as well. So in the PR chat, Metaverse, ZOZO NEXT, we are going to sell these items on ZOZO NEXT. So it's not just real clothes, but we are going to sell virtual clothes. So that's something that we're trying to do as well. So Gen AI -- with the power of Gen AI in the virtual world, we can actually design clothing with great freedom.

And this is something that anyone can do now. But we -- as a technology, we don't have -- in the world, there is no technology that could take the virtual clothing and make it into a real clothing. You need to create 3D models, make sure the sizing is right that drapes on the skirt are right as well. So there's a lot that we -- I mean if you have the time, you can do that, but it's not automated, but in the future, we will be able to connect virtual with physical. So we are actually studying the technology that will enable us to do so. That's it for me. Thank you for watching.

[Operator]

That concludes ZOZO's FY 2024 second quarter earnings briefing. Thank you for watching today.