Webinar Held on the Theme: "Are You Identifying the 'Root Causes Leading to Results' Beyond Mere Correlation?"

Details and Participation Application Here

Decision-making Becomes Increasingly Complex with Accelerated Digitalization With the advancement of digitalization, the amount of data that companies can acquire and utilize continues to grow year by year.

Customer touchpoints span online and offline, and measures are diversifying. Data utilization has become a prerequisite in all areas, including marketing, sales, and product improvement.

Furthermore, the emergence of generative AI has dramatically improved the speed of analysis and reporting. The environment is becoming ready where "data is available" and "analysis can be done."

Identifying the 'Root Causes Leading to Results' from Complex Intertwined Factors However, while many companies utilize data, few can explain "why results were achieved" or "what needs to be changed to increase results."

For example, in a resort hotel, one might think that "customer service" or "hospitality" should be strengthened to increase customer satisfaction and repeat intention. In reality, factors that drive results may be hidden among multiple intertwined factors such as meals, rooms, prices, and stay experience.

Relying solely on superficial scores and correlations can lead to misjudging the points that truly require focus, and measures that have consumed time and cost may not yield the expected results.

A Reproducible Decision-Making Process to Verify Hypotheses Through "Experiments" Even if you identify the "factors that are truly effective" which were not visible through correlation alone, you cannot know if the measures derived from them will actually lead to results without verification.

This webinar will introduce a decision-making process to scientifically confirm the effectiveness of measures through causal analysis and experiments, and to continuously select "winning measures" with reproducibility.

Based on actual analysis cases, we will concretely explain how to proceed from identifying the root causes leading to results, to hypothesis design, verification, and implementation into the next actions.

Causal AI "causal analysis" as a Mechanism to Support Decision-Making Hootfolio Inc., with its mission "Scientific decision-making for everyone," was spun off from NEC Corporation (NEC) in 2025.

Through its causal AI "causal analysis®︎ (Causal Analysis)," developed in NEC's research laboratories, it identifies "factors that drive results" from data without requiring specialized knowledge. It provides a seamless process from measure planning to verification and improvement through experiments.

It supports the practice of reproducible, scientific decision-making required in the generative AI era.

Recommended For: - Those who struggle to identify effective messages and measures. - Those who have data but cannot fully leverage it for decision-making. - Those who want to break away from judgments based on experience or intuition. - Those who want to build reproducible marketing and business strategies.

Organizer/Co-organizer HOOTFOLIO Inc. ■ Cooperation Majisemi Inc.

Details and Participation Application Here

Majisemi will continue to hold webinars that are "useful for participants." Past seminar presentation materials and other ongoing seminars can be viewed here ▶.

Majisemi Inc.

3-12 Kioicho, Chiyoda-ku, Tokyo 102-0094 Inquiries: https://majisemi.com/service/contact/ Keywords: