The introduction of the MA tool “aimstar” improved the efficiency of personalized coupon policies, and a 20% increase in sales was achieved by implementing the PDCA cycle for scenario improvement.

【 Summary 】

　Enigmo Inc. operates BUYMA, a social shopping site with a mission of “changing the world, a new trend” and more than 9 million members in 166 countries around the world.
　When BUYMA first started, the majority of its members were women in their 20s and 30s, and implementing measures mainly targeting these women would have covered the needs of users to some extent, but this was no longer sufficient as the number of male members increased and the age range of members became broader. Therefore, it became necessary to provide personalized customer experience value to each user in order to speed up scenario development and improvement without relying on engineering resources. To achieve this, it was necessary to speed up the cycle of scenario development and improvement. To this end, they decided to implement the MA tool “aimstar” so that they could develop and improve scenarios simply by setting up the tool, even without engineering resources. The aimstar is an MA tool among the 15 companies they compared when selecting an MA tool, aimstar was superior in terms of scalability, range of functions, and business feasibility.
　After introducing aimstar, the company has seen particular benefits from its coupon policy, which allows personalization of coupon amounts and minimum spending amounts for each user, etc. Before introducing aimstar, coupon codes had to be manually issued from the management screen of the core system, but after introducing aimstar, coupon codes can be automatically linked to the core system by utilizing aimstar’s coupon After the introduction of aimstar, it is now possible to use the automatic linkage function of aimstar to link with the core system, automatically generate coupon codes, and issue different coupon amounts for each user. They feel that the use of aimstar to provide individual coupons to users who meet specific conditions is a highly effective measure that has a wide range of uses.
　In addition, AB testing was conducted for each scenario, and a group was set up for users who met the conditions to receive e-mail and push notifications, and another group was set up for users who did not receive push notifications. By analyzing the sales increase rate and coupon usage rate for each group and implementing PDCA to improve the scenario, they were able to increase sales by 20%.