To help tourism in Japan flourish, Wi2 wanted to turn data from 200,000 Wi-Fi access points into a rich source of insight into visitor preferences. How could it analyze the data at speed and scale?
Wi2 deployed a platform for rapid analytics based on IBM Cloud Data Services technology—enabling it to begin pinpointing trends in visitor tastes and pedestrian flows from vast amounts of mobile data.
Cutsanalytics cycle times from weeks to days
EnablesWi2 to uncover unique tourist preferences
Supportsdata-driven service development to improve visitor experiences
Business challenge story
Offering a warm welcome to every visitor
Whether you’re traveling on vacation or business, nothing makes you feel more at home than a local showing you the best places to eat, drink and relax. What if every visitor could benefit from local expertise to get the most out of their trip? This was the goal for Wi2, a leading provider of public Wi-Fi services in Japan. With thousands of tourists downloading its TRAVEL JAPAN Wi-Fi app and connecting to more than 200,000 access points across the country, the company realized that it was sitting on a gold-mine of data—including everything from visitors’ favorite foods to the most common pedestrian routes around shopping districts in towns and cities. Businesses and local governments across Japan were already using the TRAVEL JAPAN Wi-Fi app to share promotional messages with visitors. Wi2 wanted to take the service to the next level by using behavioral analytics to identify trends in visitor preferences by region, and empower its clients to share highly relevant, compelling and personalized messages. The challenge was the sheer volume and velocity of data flowing from the TRAVEL JAPAN Wi-Fi app. The platform captures information on the way visitors move around an area, the types of articles and messages they read inside the app, and the times when these events take place. Mr. Kenji Soma, CTO at Wi2, explains: “Our aim is to offer tourists the best possible hospitality, and provide them with all the information they need to get the most out of their stay.” “Preparing our mobile app data for analysis was extremely time-consuming; we couldn’t keep up with all the data the platform created,” Mr. Soma adds. “We were storing masses of useful information, but we had no way to work with it.”
Harnessing big data to reveal unique preferences
To achieve its goals, Wi2 decided to create a cloud-based big data analytics platform based on IBM® Cloudant® as a NoSQL database platform, with IBM Db2 Warehouse on Cloud as an in-memory data warehouse for structured data. Both databases run on the IBM Cloud™ platform. Data from the TRAVEL JAPAN Wi-Fi app is first staged in cloud object storage, converted into JSON objects, and then loaded into IBM Cloudant. The IBM solution assigns the optimal schema to each object, and sends it to the IBM Db2 Warehouse on Cloud for rapid analysis. “We had three main reasons for embracing the IBM solution,” recalls Mr. Soma. “Our philosophy is that we should trial any innovative technology that might have the potential to improve the quality of our services—and we were confident that the IBM solution would enable us to accelerate our analytics process substantially. “The second reason is the functionality and performance of IBM Cloudant and IBM Db2 Warehouse on Cloud. IBM Cloudant not only provides a RESTful API, but it is natively capable of handling JSON, full-text and geospatial data. It was also appealing that the schema we applied to data in IBM Cloudant could be automatically converted to structured data in IBM Db2 Warehouse on Cloud, which makes it easy to analyze using traditional business intelligence tools. “The third reason is our partnership with IBM. We knew that the project we were embarking on was the first of its kind in many respects, and that we might encounter unexpected issues along the way. The IBM team was resolute from the start that they would face the challenges with us side-by-side, and they were always available to provide expert guidance when we needed it.” Within just two months, Wi2’s new data aggregation infrastructure was up and running. By selecting a cloud solution, the company’s data scientists can spend less time on time-consuming administration tasks and more time drilling down to discover new trends. Mr Toshiya Fukui, Manager, Corporate Business Division, Wire and Wireless (Wi2), comments: “We can now analyze a huge amount of data in an instant, without having to go through a tedious data-conversion process. Our new way of working is definitely taking the frustration out of analyzing our data.”
Personalized recommendations, perfect experiences
Today, preparing data for analysis takes minutes or seconds rather than days or weeks—enabling the company to accelerate the development of new data-driven services. With big data analytics in the cloud powering its business, Wi2 is taking major steps towards achieving its personalized marketing goals. “In the past, we used to have to extract the data we needed from huge volumes of logs in our cloud object storage environment, and then structure the data manually,” says Mr. Fukui. “Processing the data could take up to a week, and analyzing it could take more than an hour—but today, that has all changed. “It is a breakthrough that our lead time for analysis is now just minutes or seconds. Better still, we can now visualize our data in more intuitive ways—for example, by plotting events on a map based on GPS coordinates from users’ mobile devices. We can concentrate more on analyzing our data, and we feel it is advantageous for us to be able to carry out more types of analysis in a single day.” Rapid analysis is already helping Wi2 to build a better understanding of visitor preferences and honeypot sites, and improve targeting for offers and recommendations. “The more data we collect, the more accurately we will be able to predict what each visitor is likely to want to see and do while they stay in Japan,” explains Mr. Fukui. “Ultimately, we aim to deliver the most useful information at the optimal point in a person’s trip.” By helping its partners in industry and local government get to grips with what tourists want from their stays, Wi2 can help them build more effective strategies for engagement—delivering even better visitor experiences across the board. “Many companies are already analyzing pedestrian patterns from mobile data, and providing product recommendations or coupons for sought-after services,” says Mr. Soma. “As an innovative company, we always try to be the first to implement these kinds of new technologies.” Ultimately, Wi2 aims to develop predictive products that help its partners to understand what visitors are likely to do, based on their current behavior and historical visitor trends. For example, predictive analytics could identify that a group of Asian tourists enjoying some shopping in Yokohama have a high propensity to book an overnight stay in the spa town of Hakone Yumoto. “We want to tackle these kinds of challenges with cognitive technologies for deep learning and artificial intelligence, such as the IBM Watson® solutions available via IBM Bluemix,” says Mr. Fukui. Looking to the future, Wi2 intends to continue its close collaboration with IBM to drive its business growth. Mr. Soma concludes: “At the moment, we are accumulating a wide range of mobile logs in our data aggregation infrastructure. It may become necessary to reorganize our infrastructure into two systems: a database for a long-term analysis of large-scale archive data, and a data mart for real-time pattern detection in streams of data. We see great potential in our IBM Cloudant and IBM Db2 Warehouse on Cloud solutions to realize these objectives.”
Founded in 2007 and headquartered in Tokyo, Japan, Wire and Wireless Co., Ltd. (Wi2) provides wireless broadband infrastructure and services. The company offers a public wireless LAN service with the largest number of hotspots in Japan, serving major train stations, cafes, and fast food shops, accessible via the TRAVEL JAPAN Wi-Fi mobile app.
- Cloudant Local On-Prem
- Db2 Warehouse on Cloud
- IBM Bluemix
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