Allied Architects Launches 'Kaname.ax Global' to Uncover Insights in International Markets from Customer Voices

Allied Architects, a company committed to driving enterprise growth through AX, has launched 'Kaname.ax Global,' an international expansion of its 'Kaname.ax®' data platform that uses AI to analyze customer feedback and uncover insights that form the starting point of communication.

By leveraging AI to analyze social media posts and e-commerce reviews, the platform identifies the 'Contexts of Entry Points (CEPs)'—the specific triggers and situations that lead local consumers to recall products, services, or brands. This provides end-to-end support, from high-level strategies like target selection and product optimization during international expansion to operational activities like creative optimization.

■ Background
In global marketing, language and cultural barriers make it difficult to grasp deep insights into why local consumers choose specific products. Applying domestic Japanese success experiences directly often fails locally. Without objective data backing, implementing strategies carries the risk of requiring time-consuming corrections and failing to maximize marketing investment effectiveness.

'Kaname.ax®' in the Japanese market has already expanded its successful use cases across various industries, including food, beverages, and cosmetics, receiving high praise for optimizing measures based on customer recall contexts. 'Kaname.ax Global' goes further by capturing differences in language, culture, and business practices unique to global markets, assisting companies in strategic decision-making regarding which products to deliver to whom and in what context.

■ Services Provided
Tailored to a company's data availability and objectives, the platform utilizes diverse data sources—such as SNS post data, e-commerce reviews, surveys, and consumer panels—to support everything from insight identification to strategic planning and design.

1. CEPs Listening® (SNS Data Analysis): Reveals market trends and demands in specific categories from SNS conversations. By using AI to analyze consumer voices and discover brand recall triggers (CEPs), it supports effective marketing strategies.

2. Go To Market Asking (Overseas Panel Surveys): Assists in strategic planning and target selection for new market entries, even when the company lacks its own existing data.

3. Free Text Analysis (Internal Data Utilization): Analyzes existing multilingual reviews or survey data to optimize product selection and marketing messaging.

■ Key Value Propositions
1. Improved Strategic Planning Accuracy: By identifying the contexts and situations (CEPs) in which local consumers recall a brand, the platform complements decision-making for target and product selection with objective data.
2. Survey Design Focused on Actionability: Rather than merely providing reports, surveys are designed to link directly to specific, effective subsequent actions such as influencer collaborations, SNS operations, and advertising.
3. Multidimensional Insight Extraction: Provides reliable, evidence-based data from multiple perspectives by combining 'voices' from SNS with in-depth panel surveys of specific demographics.

■ Analysis Case Study
Using the 'Sunscreen' category as an example, here are partial results from visualizing overseas consumer insights via CEPs Listening®:

Example | Insight Comparison of the 'Sunscreen' Category in 3 Countries
Country A: Benefit-Oriented ('Peace of mind from UV protection')
Country B: Routine-Oriented ('Ease of use in morning skincare')
Country C: Seasonal-Oriented ('Strength of the sun and sense of summer')