Ryan Imaizumi: Welcome everyone to the Location Insights Podcast.
Ryan Imaizumi: I am Ryan Imaizumi, in charge of global marketing at unerry.
Ryan Imaizumi: Today, I would like to talk about marketing utilizing location data.
Ryan Imaizumi: Our guest today is Mr.
Ryan Imaizumi: Takeshi Yamamoto, the founder of Macagua.
Ryan Imaizumi: Mr.
Ryan Imaizumi: Yamamoto, thank you for being here today.
Takeshi Yamamoto: I am Takeshi Yamamoto from Macagua.
Takeshi Yamamoto: Thank you for having me.
Ryan Imaizumi: Well then, first, Mr.
Ryan Imaizumi: Yamamoto.
Ryan Imaizumi: Could you please tell us what kind of company Macagua is, as well as your own background?
Takeshi Yamamoto: Yes, certainly.
Takeshi Yamamoto: Macagua is still a very new company, only one year old.
Takeshi Yamamoto: It's a company that has finally reached its first anniversary.
Takeshi Yamamoto: To introduce the company, I'll need to talk a bit about my background and the flow of events, so I'd like to guide you through that first
Takeshi Yamamoto: Regarding Macagua, the services we primarily handle are foot traffic data and marketing solutions that utilize foot traffic data
Takeshi Yamamoto: Back in 2019, there was a company using this foot traffic data, and at the time, that company operated under the name Near.
Takeshi Yamamoto: I joined them as the person responsible for opening up the Japanese market and market development.
Takeshi Yamamoto: Over time, that company, Near, changed its name
Takeshi Yamamoto: From near to near intelligence and from near intelligence to azira.
Takeshi Yamamoto: The names changed in this way
Takeshi Yamamoto: Among those, the final company, Azira, is currently headquartered in the United States, and I was representing their Japanese operations.
Takeshi Yamamoto: Azira decided to stop its operations in Japan to concentrate on America and other countries.
Takeshi Yamamoto: So, last year my contract ended.
Takeshi Yamamoto: But in order to continue supporting the Japanese market and to further grow the Japanese market, I started the company Macagua and took over the sales rights for Azira in Japan.
Takeshi Yamamoto: Therefore, although Macagua is a recently established company, we mainly deal with foot traffic data.
Takeshi Yamamoto: Since around 2000, I have been involved in marketing solutions in the internet sphere
Takeshi Yamamoto: At that time I was mainly doing affiliate marketing, but since then, search engines like SEM and SEO, and what we now call word-of-mouth or buzz marketing
Takeshi Yamamoto: I have incorporated and supported various marketing methods.
Takeshi Yamamoto: Because I can support customers in the area of digital marketing by combining these, I have made that the scope of business for Macagwa.
Ryan Imaizumi: Thank you very much.
Ryan Imaizumi: That was very clear.
Ryan Imaizumi: I understand that Macagua develops services such as location marketing, utilizing foot traffic data.
Ryan Imaizumi: For example, how are companies utilizing or using location marketing?
Ryan Imaizumi: And what kind of merits are there for the companies?
Takeshi Yamamoto: Yes, let's see.
Takeshi Yamamoto: What we primarily handle is what is called foot traffic data, or some people say human movement data.
Takeshi Yamamoto: What is human movement data?
Takeshi Yamamoto: Well, it means that because people are moving, it actually means that everyone is walking around with a smartphone these days.
Takeshi Yamamoto: We collect movement data from smartphones all over the world.
Takeshi Yamamoto: We stock, classify, and organize a vast amount of data to make it usable.
Takeshi Yamamoto: To imagine what can be done with this
Takeshi Yamamoto: For example, let's say you are running a shop yourself.
Takeshi Yamamoto: You know the faces of the people who come to your shop well, but from where, what distance, and via what route did they reach your shop?
Takeshi Yamamoto: Or they come to your shop often and are a good customer.
Takeshi Yamamoto: But are they also a good customer of the shop across the street?
Takeshi Yamamoto: If you only look at what's right in front of you, you don't really know.
Takeshi Yamamoto: If you observe customers' movement, this isn't very useful if it's just a single ramen shop.
Takeshi Yamamoto: But if you're running a chain with nationwide expansion, or if you hold multiple real estate properties, when you try to do those things to strengthen your business, you naturally want to know and analyze
Takeshi Yamamoto: What kind of people are currently coming to my shop or tenant?
Takeshi Yamamoto: Where are they coming from?
Takeshi Yamamoto: What other places are they visiting?
Takeshi Yamamoto: Based on that analysis, you build and execute a strategy for the next move
Takeshi Yamamoto: The clues for that, or perhaps the foothold, is human movement data.
Takeshi Yamamoto: Since it's only movement data, we don't know what they bought or how much they spent
Takeshi Yamamoto: However, by looking at that movement, you can gradually understand that person.
Takeshi Yamamoto: That's how it's often utilized.
Takeshi Yamamoto: Once you understand this, for example, let's say there is someone who goes to Starbucks often
Takeshi Yamamoto: There is also a coffee chain in Japan called Tully's Coffee.
Takeshi Yamamoto: For example, if I were a marketer for a certain Tully's coffee, I'd think.
Takeshi Yamamoto: Man, Starbucks is great.
Takeshi Yamamoto: It's so nice they have so many people coming.
Takeshi Yamamoto: If even 10% of them came to us, our sales would go up significantly
Takeshi Yamamoto: So, you'd want to run ads or promotions targeting people who visit Starbucks to lure them to your shop.
Takeshi Yamamoto: However, you can't just watch the front of the store all day and you can't keep handing out flyers forever.
Takeshi Yamamoto: In such cases, while looking at human movement data, you can see how many such people there are, what percentage of them come to us, and see people's foot traffic
Takeshi Yamamoto: Moreover, because we are looking at customer movement on a mobile phone basis, it's recently become possible to run ads on those smartphones.
Takeshi Yamamoto: So you could try running ads, and by doing so, entice people to come here.
Takeshi Yamamoto: What I just mentioned at the end is the general gist of it.
Takeshi Yamamoto: You think of the next move after performing an analysis.
Takeshi Yamamoto: Among those moves, there are various options, like handing out flyers or putting up signs.
Takeshi Yamamoto: But since everyone has a smartphone in hand now, you run ads inside the smartphone to encourage behavior change.
Takeshi Yamamoto: That is how it can be utilized.
Takeshi Yamamoto: Sorry, that got a bit long.
Ryan Imaizumi: Thank you.
Ryan Imaizumi: I see.
Ryan Imaizumi: So from traditional paper flyers, you are now already looking at customer movement, deciding on a target
Ryan Imaizumi: and delivering ads to targeted people within their mobile phones and smartphones.
Ryan Imaizumi: In that sense, it means you can perform specialized targeting and marketing towards people who are interested in your business.
Ryan Imaizumi: So there are merits like the accuracy becoming very high and efficiency also improving, right?
Takeshi Yamamoto: That is exactly right.
Takeshi Yamamoto: Yes.
Ryan Imaizumi: Thank you.
Ryan Imaizumi: I see.
Ryan Imaizumi: So this target marketing, this location marketing, probably started earlier globally compared to Japan.
Ryan Imaizumi: For example, you mentioned the American company you were previously at.
Ryan Imaizumi: Near became a zero.
Ryan Imaizumi: When you were working at Near, for example, where there are representative cases of global utilization, you've done marketing utilizing foot traffic data in various forms.
Ryan Imaizumi: But among those, are there any particularly impressive cases you could share with our listeners?
Takeshi Yamamoto: Yes.
Takeshi Yamamoto: Roughly speaking, within marketing solutions, there is the ad delivery business.
Takeshi Yamamoto: On the other hand, if we have the ad delivery solution in the right hand, in the left hand, we have the foot traffic data analysis solution.
Takeshi Yamamoto: The order is to analyze human movement and then deliver ads to the optimal target at the optimal location.
Takeshi Yamamoto: For example,
Takeshi Yamamoto: Considering just the ad delivery business, we have a database of what kind of buildings or shops are at various locations based on past visit points.
Takeshi Yamamoto: We track customer movement continuously, and by combining those visit points and movement trends, combining location data with human movement data, we perform so-called user profiling
Takeshi Yamamoto: Near and Azra, currently Azira, do not hold any personal information at all.
Takeshi Yamamoto: However, while looking at the history of how smartphone location information visits and moves
Takeshi Yamamoto: We look at the visit points, what kind of brand shops are there, whether it's for men or women, and what age group the shop targets.
Takeshi Yamamoto: We have that as separate information and have AI and machine learning analyzing that data.
Takeshi Yamamoto: By doing so, because a single user ID has a certain visit tendency, we can identify, for example, a company employee or someone who often goes to shops for young people and regularly visits to a college.
Takeshi Yamamoto: So they are likely a student.
Takeshi Yamamoto: Based on the brands of shops visited, they often go to places for men, so they are likely a male student.
Takeshi Yamamoto: We do such profiling
Takeshi Yamamoto: Based on this, we run targeted ads, which is what Near and AZIRA have been doing for a long time.
Takeshi Yamamoto: While profiling and targeting are common in the world of advertising,
Takeshi Yamamoto: The characteristic part is looking at foot traffic and seeing visit tendencies, looking at behavior in the real world, which is very useful.
Takeshi Yamamoto: Based on such data, for example, what is happening now is that when companies perform marketing, they usually look at behavioral logs left on digital platforms or what content is frequently read when running targeted ads.
Takeshi Yamamoto: They perform so-called contextual targeting while seeing what content is frequently engaged with.
Takeshi Yamamoto: That refers to digital footprints when running targeting ads
Takeshi Yamamoto: In the case of Near and AZiRA, we look at the foot traffic of where customers visit in their real lives, not on digital platforms, and perform so-called real behavioral targeting
Takeshi Yamamoto: By combining these two types of data, it becomes possible to run high-precision, accurate targeting.
Takeshi Yamamoto: This kind of thing, for example
Takeshi Yamamoto: Companies know data for people who came to their shop, people who came to a physical shop, or people who visited an e-commerce shop, and they know the data of people who bought things or registered as members.
Takeshi Yamamoto: There is a database called CRM for maintaining relationships with customers.
Takeshi Yamamoto: By looking at purchase data and such, they have data for those who came or bought things.
Takeshi Yamamoto: However, they have no way to capture those who came to the shop but left without buying anything.
Takeshi Yamamoto: Online, if it's e-commerce, you know someone clicked an ad and entered.
Takeshi Yamamoto: But you don't know the person who left without buying.
Takeshi Yamamoto: At physical shops like department stores, people who came but left without buying anything don't stay in the database.
Takeshi Yamamoto: You don't know them well.
Takeshi Yamamoto: And people who came to your shop surely go to competing stores as well.
Takeshi Yamamoto: If you wonder where they go, you say welcome and thank you to people who come to your shop.
Takeshi Yamamoto: But you don't even know if they turned right, turned left, or entered the competing department store across the street afterward
Takeshi Yamamoto: By combining real-world data and digital data in these areas, you can better understand what kind of customers came to your shop and how to reach such customers.
Takeshi Yamamoto: By combining data, you can refine your customer image.
Takeshi Yamamoto: We've been providing services to extend CRM data using data near holds for over five years overseas
Takeshi Yamamoto: We do so-called first-party data extension.
Takeshi Yamamoto: However, in Japan, it's been difficult to get this accepted.
Takeshi Yamamoto: That's been a challenge in my five years of activity.
Takeshi Yamamoto: However, something similar to this, running campaigns by combining online and offline data, has been proven to yield very high performance overseas, and we've done a few trials in Japan as well
Takeshi Yamamoto: Since it results in quite high conversions and high click-through rates, marketing that combines the real world and the digital world must be done in a more targeted way.
Takeshi Yamamoto: And I think it will increase
Takeshi Yamamoto: There is room to grow it.
Takeshi Yamamoto: So this would be a good case of starting overseas first and then seeing how it went when trying it in Japan.
Ryan Imaizumi: Yes, thank you.
Ryan Imaizumi: Especially combining real and online, I can really imagine how customer understanding deepens and targeting precision improves.
Ryan Imaizumi: Specifically, for example, in America, it's probably a service or movement that particularly started there.
Ryan Imaizumi: But based on your experience, what are some other markets where this is being utilized?
Takeshi Yamamoto: Yes.
Takeshi Yamamoto: Regarding the first-party data extension I just mentioned, it's actually being done quite actively in Australia.
Takeshi Yamamoto: Major publishers have been doing this with us for a long time.
Takeshi Yamamoto: It's highly effective, and for publishers, in Japan, they are exhausting themselves by undercutting each other on media fees, but in Australia, it's the opposite
Takeshi Yamamoto: The media performance improves because it leads to an understanding of the customer image.
Takeshi Yamamoto: They can make great proposals to clients.
Takeshi Yamamoto: This allows them to further increase their value as premium media.
Takeshi Yamamoto: There are various other use cases in other countries
Takeshi Yamamoto: There is the aspect of improving results by using audience profiles, and for an example, from another country, Europe.
Takeshi Yamamoto: Azira has a base in France as well, and what they are doing there is, I think it was Paris.
Takeshi Yamamoto: It seems that distributing paper flyers is already prohibited.
Takeshi Yamamoto: So, what is happening there?
Takeshi Yamamoto: Paper flyers were likely used to say.
Takeshi Yamamoto: Please come to the shop at key points and guide people, but that has been entirely replaced by digital.
Takeshi Yamamoto: Instead of digital flyers, they run audience targeting ads tailored to the location
Takeshi Yamamoto: This eliminates wasted effort and resource drain, and based on past foot traffic, which leads into location marketing, location marketing is becoming more digitalized
Takeshi Yamamoto: It feels like it's operating as a major success case of a transition from paper to digital.
Ryan Imaizumi: Thank you.
Ryan Imaizumi: Yes, from paper to digital, plus the ability to target, I feel there are various possibilities there.
Ryan Imaizumi: You mentioned earlier that there are still various challenges for location marketing in Japan.
Ryan Imaizumi: Specifically, how do you think location marketing will spread in Japan?
Ryan Imaizumi: For example, what kind of companies could utilize location marketing and what kind of merits would those companies have?
Ryan Imaizumi: Please let us know your views.
Takeshi Yamamoto: Yes.
Takeshi Yamamoto: What I've mentioned so far were mostly stories leaning towards marketing campaigns.
Takeshi Yamamoto: Of course, I think there is room for improvement and more utilization on the marketing campaign side, but from a different perspective.
Takeshi Yamamoto: Data on how what kind of people are moving around the globe is the basis of foot traffic data.
Takeshi Yamamoto: It's becoming clear that this can be used in various industries
Takeshi Yamamoto: unerry is also active in this industry, so you know well, but commercial facilities, restaurant chains, and where people are and what routes they use to enter.
Takeshi Yamamoto: Store opening plans, closing plans.
Takeshi Yamamoto: So-called store opening strategies.
Takeshi Yamamoto: When you move large amounts of capital and cannot afford to fail, a lot of preparation is necessary.
Takeshi Yamamoto: You can derive where to open a store more precisely based on human movement.
Takeshi Yamamoto: You can do those things.
Takeshi Yamamoto: Real estate, restaurant chains, and shops inside them.
Takeshi Yamamoto: Retail stores in large shopping malls.
Takeshi Yamamoto: If it's an industry that moves people in the real world, it can be utilized in almost any industry.
Takeshi Yamamoto: This isn't recent, but money flows to where people shop was the main driver of economic activity
Takeshi Yamamoto: While people say it is less expensive in the digital world with e-commerce.
Takeshi Yamamoto: Actually, the Japan Ministry of Economy, Trade and Industry said a few years ago
Takeshi Yamamoto: 90% of the economy consists of the actual movement of people.
Takeshi Yamamoto: In that sense, we have to look at this 90% of the economy properly.
Takeshi Yamamoto: Since almost everything is managed by people moving, if you look around outside, money flows to where people are moving.
Takeshi Yamamoto: I believe it can be utilized in various industries right before our eyes
Takeshi Yamamoto: Dining, real estate, and the retail shops inside.
Takeshi Yamamoto: By performing proper analysis and comparing with competitors and other shops,
Takeshi Yamamoto: We can continue to develop not just existing marketing methods, but marketing methods that utilize such data.
Takeshi Yamamoto: Another interesting trend from the last few years is in the financial industry, what is called alternative data.
Takeshi Yamamoto: Finance combines various data for things like quants.
Takeshi Yamamoto: Previously, they used artificial satellites to look at human movement, trucks.
Takeshi Yamamoto: And the movement of materials entering factories to predict that something will be shipped from the factory months later and lined up in stores.
Takeshi Yamamoto: They looked at how much economic effect there would be when those products sold, but now human movement data is gradually becoming a support material.
Takeshi Yamamoto: Since these things are happening, it's not just visible objects moving.
Takeshi Yamamoto: Even in invisible areas, which might mean money moving, utilization will progress in such industries
Ryan Imaizumi: Thank you.
Ryan Imaizumi: Yes, alternative data, utilizing foot traffic data in the financial industry specifically, is a very interesting initiative, and I can really imagine utilization progressing further and further.
Ryan Imaizumi: Thank you.
Ryan Imaizumi: Another thing I wanted to ask is that AI has been attracting a lot of attention lately.
Ryan Imaizumi: For example, as you mentioned
Ryan Imaizumi: Predicting store openings or signs and predictions of where to open stores are already being used in our location data business.
Ryan Imaizumi: But going forward by combining AI and location data.
Ryan Imaizumi: What kind of new products, services, or markets do you feel or think will be born?
Takeshi Yamamoto: Yes.
Takeshi Yamamoto: We still need to think about what various things it can be used for from now on.
Takeshi Yamamoto: So I haven't reached a specific this is it yet.
Takeshi Yamamoto: But for example, tourism.
Takeshi Yamamoto: Lately, there are many stories about tourism.
Takeshi Yamamoto: In tourism, you can grasp trends from people's movement.
Takeshi Yamamoto: People often worry about what should the next move be, because they could not analyze the situation so they don't know what hand to play next.
Takeshi Yamamoto: There are companies working on using AI to make proposals.
Takeshi Yamamoto: This might just be an example from tourism right now, but it's not just tourism.
Takeshi Yamamoto: It includes store opening plans where you feed past data and analyze it.
Takeshi Yamamoto: Based on those results, you try executing, and successes and failures naturally emerge.
Takeshi Yamamoto: By ruminating on those, I believe more precise proposals and strategic decisions can be made
Takeshi Yamamoto: In terms of AI utilization, I think such things will continue to progress in the future.
Ryan Imaizumi: Thank you.
Ryan Imaizumi: Yes, we often hear that data can be seen, but it's unclear what specifically to do next.
Ryan Imaizumi: So AI being able to propose or suggest specific next actions or what options exist makes it very easy to imagine as a form of utilization.
Ryan Imaizumi: Indeed, this is the last thing, but regarding location marketing.
Ryan Imaizumi: While its utilization progresses globally and in Japan, I'm sure there are various challenges.
Ryan Imaizumi: If there are challenges you see now or things that might become challenges in the future, even if not right now,
Ryan Imaizumi: Could you please share them with our listeners?
Takeshi Yamamoto: Yes.
Takeshi Yamamoto: After all, if you observe movement information continuously, as I said earlier, you become able to do things like profiling.
Takeshi Yamamoto: While you can't strictly identify individuals like their gender, age, or email address, as things progress, you can somehow smoke out things that are really close to that
Takeshi Yamamoto: So I think concerns regarding privacy will continue to rise in the future.
Takeshi Yamamoto: In Azira's case, we tackle service and development with a privacy-first approach.
Takeshi Yamamoto: But depending on the country, Europe is particularly strict with things like GDPR.
Takeshi Yamamoto: Depending on the country, or not just the country, but when everyone's interest in privacy regarding digital data rises further.
Takeshi Yamamoto: We must continue to watch how location information changes and how its handling changes and respond appropriately.
Takeshi Yamamoto: I think that is a future challenge
Takeshi Yamamoto: I believe it is a part where we need to deal with it successfully in advance.
Ryan Imaizumi: Thank you.
Ryan Imaizumi: Yes.
Ryan Imaizumi: In North America, specifically America, rules change or differ by state.
Ryan Imaizumi: And regarding using or acquiring people's location information, rules change frequently in each state.
Ryan Imaizumi: So it's about getting along with that successfully.
Ryan Imaizumi: It might not be that it can't be used or done, but we must follow each rule to acquire and utilize it.
Ryan Imaizumi: So that is a challenge each company must follow properly, right?
Takeshi Yamamoto: Yes, that's exactly right.
Ryan Imaizumi: Thank you.
Ryan Imaizumi: Today we heard from Mr.
Ryan Imaizumi: Takeshi Yamamoto of Macagua about marketing using various location data
Ryan Imaizumi: From global to domestic and how this will be used in the future, including AI and how it will be utilized in location marketing.
Ryan Imaizumi: And finally, we talked about challenges
Ryan Imaizumi: You shared various knowledge and experiences regarding location marketing in many forms.
Ryan Imaizumi: Mr.
Ryan Imaizumi: Yamamoto, thank you very much for your time today.
Takeshi Yamamoto: Thank you.