Episode 2 - Interview with Macagua founder 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 Regarding Macagua, the services we primarily handle are foot traffic data and marketing solutions that utilize foot traffic data Back in 2019, there was a company using this foot traffic data, and at the time, that company operated under the name Near. I joined them as the person responsible for opening up the Japanese market and market development.

Over time, that company, Near, changed its name From near to near intelligence and from near intelligence to azira. The names changed in this way Among those, the final company, Azira, is currently headquartered in the United States, and I was representing their Japanese operations. Azira decided to stop its operations in Japan to concentrate on America and other countries. So, last year my contract ended.

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. Therefore, although Macagua is a recently established company, we mainly deal with foot traffic data.

Since around 2000, I have been involved in marketing solutions in the internet sphere 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 I have incorporated and supported various marketing methods. Because I can support customers in the area of digital marketing by combining these, I have made that the scope of business for Macagwa.

To imagine what can be done with this For example, let's say you are running a shop yourself. 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? Or they come to your shop often and are a good customer. But are they also a good customer of the shop across the street? If you only look at what's right in front of you, you don't really know.

If you observe customers' movement, this isn't very useful if it's just a single ramen shop. 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 What kind of people are currently coming to my shop or tenant? Where are they coming from? What other places are they visiting?

Based on that analysis, you build and execute a strategy for the next move The clues for that, or perhaps the foothold, is human movement data. Since it's only movement data, we don't know what they bought or how much they spent However, by looking at that movement, you can gradually understand that person. That's how it's often utilized. Once you understand this, for example, let's say there is someone who goes to Starbucks often There is also a coffee chain in Japan called Tully's Coffee.

For example, if I were a marketer for a certain Tully's coffee, I'd think. Man, Starbucks is great. It's so nice they have so many people coming. If even 10% of them came to us, our sales would go up significantly So, you'd want to run ads or promotions targeting people who visit Starbucks to lure them to your shop. However, you can't just watch the front of the store all day and you can't keep handing out flyers forever.

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 Moreover, because we are looking at customer movement on a mobile phone basis, it's recently become possible to run ads on those smartphones. So you could try running ads, and by doing so, entice people to come here. What I just mentioned at the end is the general gist of it. You think of the next move after performing an analysis.

Among those moves, there are various options, like handing out flyers or putting up signs. But since everyone has a smartphone in hand now, you run ads inside the smartphone to encourage behavior change. That is how it can be utilized. Sorry, that got a bit long.

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 Near and Azra, currently Azira, do not hold any personal information at all. However, while looking at the history of how smartphone location information visits and moves 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.

We have that as separate information and have AI and machine learning analyzing that data. 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. So they are likely a student. Based on the brands of shops visited, they often go to places for men, so they are likely a male student.

We do such profiling Based on this, we run targeted ads, which is what Near and AZIRA have been doing for a long time. While profiling and targeting are common in the world of advertising, The characteristic part is looking at foot traffic and seeing visit tendencies, looking at behavior in the real world, which is very useful.

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. They perform so-called contextual targeting while seeing what content is frequently engaged with.

That refers to digital footprints when running targeting ads 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 By combining these two types of data, it becomes possible to run high-precision, accurate targeting.

This kind of thing, for example 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. There is a database called CRM for maintaining relationships with customers. By looking at purchase data and such, they have data for those who came or bought things.

However, they have no way to capture those who came to the shop but left without buying anything. Online, if it's e-commerce, you know someone clicked an ad and entered. But you don't know the person who left without buying. At physical shops like department stores, people who came but left without buying anything don't stay in the database. You don't know them well. And people who came to your shop surely go to competing stores as well.

If you wonder where they go, you say welcome and thank you to people who come to your shop. But you don't even know if they turned right, turned left, or entered the competing department store across the street afterward 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. By combining data, you can refine your customer image.

We've been providing services to extend CRM data using data near holds for over five years overseas We do so-called first-party data extension. However, in Japan, it's been difficult to get this accepted. That's been a challenge in my five years of activity.

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 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. And I think it will increase There is room to grow it.

So this would be a good case of starting overseas first and then seeing how it went when trying it in Japan.

This allows them to further increase their value as premium media. There are various other use cases in other countries There is the aspect of improving results by using audience profiles, and for an example, from another country, Europe. Azira has a base in France as well, and what they are doing there is, I think it was Paris. It seems that distributing paper flyers is already prohibited. So, what is happening there? Paper flyers were likely used to say.

Please come to the shop at key points and guide people, but that has been entirely replaced by digital. Instead of digital flyers, they run audience targeting ads tailored to the location This eliminates wasted effort and resource drain, and based on past foot traffic, which leads into location marketing, location marketing is becoming more digitalized It feels like it's operating as a major success case of a transition from paper to digital.

It's becoming clear that this can be used in various industries 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. Store opening plans, closing plans. So-called store opening strategies. When you move large amounts of capital and cannot afford to fail, a lot of preparation is necessary. You can derive where to open a store more precisely based on human movement. You can do those things.

Real estate, restaurant chains, and shops inside them. Retail stores in large shopping malls. If it's an industry that moves people in the real world, it can be utilized in almost any industry. This isn't recent, but money flows to where people shop was the main driver of economic activity While people say it is less expensive in the digital world with e-commerce.

Actually, the Japan Ministry of Economy, Trade and Industry said a few years ago 90% of the economy consists of the actual movement of people. In that sense, we have to look at this 90% of the economy properly. Since almost everything is managed by people moving, if you look around outside, money flows to where people are moving. I believe it can be utilized in various industries right before our eyes Dining, real estate, and the retail shops inside.

By performing proper analysis and comparing with competitors and other shops, We can continue to develop not just existing marketing methods, but marketing methods that utilize such data. Another interesting trend from the last few years is in the financial industry, what is called alternative data. Finance combines various data for things like quants. Previously, they used artificial satellites to look at human movement, trucks.

And the movement of materials entering factories to predict that something will be shipped from the factory months later and lined up in stores. 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. Since these things are happening, it's not just visible objects moving. Even in invisible areas, which might mean money moving, utilization will progress in such industries

But going forward by combining AI and location data. What kind of new products, services, or markets do you feel or think will be born?

This might just be an example from tourism right now, but it's not just tourism. It includes store opening plans where you feed past data and analyze it. Based on those results, you try executing, and successes and failures naturally emerge. By ruminating on those, I believe more precise proposals and strategic decisions can be made In terms of AI utilization, I think such things will continue to progress in the future.

If there are challenges you see now or things that might become challenges in the future, even if not right now, Could you please share them with our listeners?

But depending on the country, Europe is particularly strict with things like GDPR. Depending on the country, or not just the country, but when everyone's interest in privacy regarding digital data rises further. We must continue to watch how location information changes and how its handling changes and respond appropriately. I think that is a future challenge I believe it is a part where we need to deal with it successfully in advance.