In today’s competitive landscape, institutional investors are continually seeking innovative ways to gain an edge. At aiQ, we believe that alternative data holds the key to unlocking profound insights and driving strategic decisions. Our dataset, aiQ Geolocation, is a powerful tool designed to provide a deeper understanding of market dynamics in Japan, enabling investors to correlate foot traffic with company KPIs.
What is aiQ Geolocation?
aiQ Geolocation is the most extensive mobile location-based footprint data available for the Japanese market. Unlike traditional data sources, it offers a granular view of human movement, providing invaluable context to consumption and production activities. This dataset is sourced from NTT Docomo, Japan’s largest mobile carrier, ensuring a vast and stable data pool derived from base stations, which offers more consistent and larger amounts of data compared to GPS-based solutions.
Our focus with aiQ Geolocation is on heavy industry manufacturers that own plants and factories across Japan, including car manufacturers, car parts manufacturers, and semiconductor manufacturers. By tracking the foot traffic of workers at these sites, we can provide a measurable indicator of activity levels, allowing us to gauge the operational activity at their sites.
The Power of Correlation: Real-World Examples
We’ve conducted extensive backtests that showcase this potential, providing compelling evidence of its predictive capabilities. In this post, we introduce three examples of high correlation from the industries of Car Parts Suppliers, Car Makers, and Hotels.
Example 1: Car Parts Supplier
TOYOTA BOSHOKU CORPORATION (3116 JT Equity)
For a leading automotive interior system supplier in the Toyota group, we observed a strong correlation between the year-over-year (YoY) change in “geofence_ot” (nighttime foot traffic) at their various factory and regional HQ locations and their consolidated quarterly sales. By shifting the aiQ Geolocation data by +1 month, accounting for potential time lags between production and sales, we achieved a correlation coefficient of 0.895.
Example 2: Automobile Manufacturer
MITSUBISHI MOTORS CORPORATION (7211 JT Equity)
Similarly, for a prominent automobile manufacturer known for its SUVs and PHEVs, our analysis revealed a significant correlation. By analyzing the YoY change in “geofence_ot” at their assembly and component plants, as well as their tech/research centers, and shifting the data by +1 month, we found a correlation coefficient of 0.876 with their consolidated quarterly sales.
Example 3: Hotels
Imperial Hotel, Ltd. (9708 JT Equity)
Beyond manufacturing, aiQ Geolocation also proves highly effective in the service industry. For a long-established hotel representing Japan in Tokyo, we identified a strong correlation between the YoY change in “geofence” (all-day foot traffic) at their various hotel locations and their consolidated quarterly sales. In this case, no time shift was applied, as the time lag between foot traffic and sales is typically relatively slight in the hospitality sector, resulting in a robust correlation coefficient of 0.873.
Unlock Your Investment Potential
These examples highlight the power of aiQ Geolocation data for financial institutions seeking to optimize their investment decisions and gain a predictive edge. By understanding the intricate relationship between human movement and business outcomes, you can make more informed judgments regarding stock analysis, real estate valuations, and identifying early indicators of market shifts. Our dataset is specifically optimized to support sophisticated investment strategies and provide valuable insights for proactive decision-making in the Japanese market.
At aiQ, we are committed to providing the most comprehensive and insightful alternative data solutions for the Japanese market. Our aiQ Geolocation dataset stands as a testament to this commitment, offering unparalleled depth and accuracy.
Please don’t hesitate to contact us if you would like to get a full report or more information about our datasets.
