This relates to the ongoing discussion about how to allocate the recruitment budget. Ultimately, the most
desirable outcome is for Recruit to receive payment, regardless of whether it's through advertising or
placement fees.
The same applies to the candidate pool. The resumes, or profiles, are the same. Matching based on the same
information is the most efficient. Doing this together rather than separately increases that efficiency. The AI
agent video also illustrates this. We provide an app to candidates, but we don't directly charge them for it.
However, the data we gather is enormous. If that leads to better matching, then it pays off for us in terms of
cost. That's the underlying philosophy, in the long run.
Yamamura: So, whether it's advertising or placement doesn't matter? What's your vision for what happens
when placement and automation compete?
Arai: Ultimately, even if we look at the current situation, there are people who pay for advertising and people
who pay for placement, and many customers use both. So, it's not necessary for them to become one single
thing. It's just a matter of how money is spent and how hiring is done. I think those two categories, or
methods, will remain regardless of whether or not automation happens.
However, even in our placement business, we are advancing automation. Therefore, compared to those who
operate solely with human staff, our efficiency will naturally be better, our running costs will be lower, and our
profit margin will increase.
Furthermore, because we will be conducting transactions 24 hours a day, we will naturally be able to handle a
large volume. That's where our winning strategy lies. However, even if you create such a mechanical or
automated system, it becomes useless if there are no actual matches.
Because we possess matching capabilities, it makes sense for us to pursue automation. But even if someone
just creates a mechanically valuable tool, as Deko mentioned, what makes it profitable or valuable for us is
that we have job data and data related to our customers' hiring needs. He said that this is essential, and I
agree.
The remaining question is how well human-driven operations can be made more efficient, and how we can
overcome that bottleneck.
For example, if candidates answer questions the mechanical agents ask, then perhaps our human career
advisors, who can currently handle 30 candidates at a time, could handle 60 if some of their tasks are
automated. I think there’s probably a balance between the upside of one career advisor being able to take
care of 60 people to drive revenue, and the cost-savings of focusing only on 30 people, maybe requiring only
a 0.5 employee. So, if we’re prioritizing revenue growth for now, I think it makes sense to use machines to
help increase the number of people each advisor can take care of. That's the kind of world we're entering.
As that gradually saturates, the next step will be to increase efficiency. Either can come first, but I think
interesting developments will emerge as this progresses.
When expanding in the US, as Deko also mentioned, we will focus on areas where we can offer new and
better solutions.
I think there's a huge difference between having and not having a business rooted in human interaction. I
hope that those who are successfully running such businesses will leverage them, grow them, and transform
them into new businesses – that's where the dream lies.
Zhai: I haven't been covering your company for very long, so I'm not sure if my understanding is correct. You
mentioned earlier that the European business is a bit behind the US, so there's still room for monetization
there. Does this mean that there are monetization methods already implemented in the US that haven't been
introduced in Europe yet, and introducing them will increase the unit price?
This transcript is provided for the convenience of investors only and this is a translated version of the Japanese call.
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