Journal

　On Tuesday, June 15th, Kyoko YANO chief director and three other staff members, Promotion Sales and Marketing Division of Fuji Inc., and Masahiko AKAO chief director and two other staff members, Information Services Promotion Division of Seki Inc., came to our school. Also, with ZOOM, Mr. KARASUDANI Deputy Director of True Data Analytics Solutions, Inc., Fumikazu ONISHI Executive Director of Fuji Inc., Hirotaka SEKI President of Seki Corporation, and Mr. SHIRAISHI, a graduate of our school and student of Tokyo University, participated in this meeting online.

　Today's lecture was given by Mr. KARASUDABU, Deputy Director of True Data Analytics Solutions, Inc., on measures to improve sales based on purchase data.  The contents of this lecture were ①Key Performance Indicator settings, ②Sales analysis tree, ③Considering customer-contact points at 5W1H, ④Steps for action,　⑤Keywords for product appeal, and ⑥·Examples of AI-based comments for applications

　We were given an example and he explained to us the sales analysis tree, the steps for action, the categories of trend loading, and keywords for product-appeal.  Then we created a sales analysis tree based on the customer profile we created so far, and thought about why, what, when, where, and how (to have customers purchase) as action steps to increase the number of purchases.

　From now on, we will further discuss "Sales Analysis Tree", "Steps for Action in 5W1H" and "Appealing Keywords" based on the purchase data of each customer type.  And we will analyze what day of the week, what time zone of the day, and what kind of policy to customers is better to increase the number of customer-visits and purchases based on the contents of the previous lectures on promotional activities. Finally, we will consider target and product department that each section has been in charge of.

　Next time, we will hold an exchange meeting with three companies where students can discuss questions while considering measures.

　I was surprised that I could read a lot of things from the purchase data, and it could be schematically represented as an analysis tree.  I would like to take advantage of what I was taught in the lecture and think about measures.   (202　Ryoya IKEDA)