You have come this far by implementing various measures such as raising the paid job ads ratio, expanding
premium services, and introducing minimum budgets. What stage are you currently at, and in the next year or
in the mid- to long-term, where is the most significant upside remaining? We believe in your resilience against
macroeconomic factors to a certain extent, so could you please comment on the sustainability of your
monetization strategy?
Deko: Thank you for the wonderful question. First and foremost, what we are considering as a fundamental
premise is that, until now, we have inevitably focused on acquiring a large number of applicants. However,
especially when the economy worsens, the number of applicants naturally increases. Therefore, by using
things like AI, we can selectively send higher quality applicants – those who are a good fit for the job and the
type of person the company wants to hire – thereby reducing the burden on companies.
For example, we have many major clients who receive as many as 3 to 4 million applications per year. They
have a very strong desire, and we hear many requests from them, to see if we can narrow that down to just
one-tenth of truly suitable candidates.
So, regarding the premium services you mentioned, currently, these are mainly targeted at small and
medium-sized enterprises. For example, if they only want to hire people with specific qualifications, we apply
several matching criteria on our end and charge these clients more for this service.
Looking ahead, there is still a lot we can do and are currently testing using AI, such as AI-powered screening
and AI-powered interviews. We need to consider how to monetize these advancements. Furthermore, we
have been operating what is called a demand-side auction, where companies looking to hire people for
specific jobs compete on price in an auction format.
In the mid- to long-term, this relates to concepts that are often discussed not just by us but also things like
optimized CPC (OCPC) and outcome-based models. What this means is, for example, and this isn't just
limited to us, when ten people click on an advertisement, how do we allocate budget and charge differently to
those who are highly likely to make a purchase versus those who are less likely? There are also
advancements in advertising technology in this area.
In other words, as demand and supply become more scientifically understood, we can achieve slightly more
scientific pricing by determining how to allocate and charge based on who is truly a very good applicant for a
particular company.
In other words, once we understand not just how many people want to hire, but also how many applicants are
likely to be qualified for a specific job in a specific area, then, for example – just to give a clear example –
that's how it works. So, I believe this kind of evolution will continue to progress.
The most important thing is that the value for client companies and users is genuinely enhanced. We believe
this can be achieved through the evolution of AI technology. When it comes to monetizing this, it's crucial not
to be too hasty. By proceeding while confirming that it's beneficial, I believe we can receive payment in many
ways beyond just premium services, in a way that everyone is satisfied with. That's what we are thinking. I
apologize for the lengthy answer, but we believe we are just getting started.
Shen: Thank you. Are there any other questions?
Kitagawa: Thank you. I am Kitagawa from NewsPicks. Nice to meet you.
Since the HR Technology business is doing extremely well, I would like to ask about the other business areas
instead.
This transcript is provided for the convenience of investors only and this is a translated version of the Japanese call.
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