Hosting Study Group for EC Managers 'Practical Course on EC x AI Analysis' - Grasp the Next Move in EC Operations through Efficiency and Deepening of AI Analysis
Commerce Ship Co., Ltd. will hold a free online study group for EC managers, "Practical Course on EC x AI Analysis," on April 23, 2026. It will cover AI-driven operational efficiency and practical prompt design.
📋 Article Processing Timeline
- 📰 Published: March 31, 2026 at 17:25
- 🔍 Collected: March 31, 2026 at 09:01
- 🤖 AI Analyzed: April 22, 2026 at 21:52 (540h 50m after Collected)
Commerce Ship Co., Ltd. (Headquarters: Kita-ku, Tokyo, President and CEO: Mamoru Ueno) will hold a study group "Practical Course on EC x AI Analysis" for marketers and operators involved in EC on Thursday, April 23, 2026, from 16:00 to 17:00.
## Background of the Event
In EC malls such as Rakuten Ichiba, Yahoo! Shopping, and Amazon, a massive amount of data, including sales data, reviews, and advertising effectiveness, is generated daily. However, we often hear voices from the field saying, "We are too busy compiling data to actually analyze it."
In recent years, due to the rapid evolution of AI tools, not only has the time required for data compilation and report generation—which previously took hours—been significantly reduced, but an environment is also being prepared where deep analyses that traditionally required expert knowledge, such as competitive comparisons, trend forecasting, and customer LTV analysis, can be performed by the EC managers themselves.
This study group was planned as a place to systematically learn such "practical knowledge of EC x AI."
## Target Audience
- Those involved in store operations at malls like Rakuten Ichiba, Yahoo! Shopping, and Amazon.
- EC managers, marketers, MDs, and ad operations staff dealing with data daily.
- Those interested in operational efficiency and advanced analysis using AI but don't know where to start.
- Those who need to handle data themselves because there are no data analysts or engineers in-house.
## What You Will Gain from This Study Group
- The current state of EC x AI
- Specific AI utilization methods to reduce man-hours for data collection and aggregation
- Practical examples of analysis using data from Rakuten, Yahoo!, and Amazon
- Points of prompt design that can be used immediately in the field
## Event Overview
| Item | Details |
|---|---|
| Date & Time | Thursday, April 23, 2026, 16:00-17:00 |
| Application Deadline | Monday, April 20, 2026 |
| Format | Online (Zoom) |
## Background of the Event
In EC malls such as Rakuten Ichiba, Yahoo! Shopping, and Amazon, a massive amount of data, including sales data, reviews, and advertising effectiveness, is generated daily. However, we often hear voices from the field saying, "We are too busy compiling data to actually analyze it."
In recent years, due to the rapid evolution of AI tools, not only has the time required for data compilation and report generation—which previously took hours—been significantly reduced, but an environment is also being prepared where deep analyses that traditionally required expert knowledge, such as competitive comparisons, trend forecasting, and customer LTV analysis, can be performed by the EC managers themselves.
This study group was planned as a place to systematically learn such "practical knowledge of EC x AI."
## Target Audience
- Those involved in store operations at malls like Rakuten Ichiba, Yahoo! Shopping, and Amazon.
- EC managers, marketers, MDs, and ad operations staff dealing with data daily.
- Those interested in operational efficiency and advanced analysis using AI but don't know where to start.
- Those who need to handle data themselves because there are no data analysts or engineers in-house.
## What You Will Gain from This Study Group
- The current state of EC x AI
- Specific AI utilization methods to reduce man-hours for data collection and aggregation
- Practical examples of analysis using data from Rakuten, Yahoo!, and Amazon
- Points of prompt design that can be used immediately in the field
## Event Overview
| Item | Details |
|---|---|
| Date & Time | Thursday, April 23, 2026, 16:00-17:00 |
| Application Deadline | Monday, April 20, 2026 |
| Format | Online (Zoom) |