The challenges and next steps seen from a new perspective

[ishanijerin1]

The system and functionality have been successfully revamped and the brand has been renewed, and although the focus is still on app data, over the past year we have come to the point where we are recognized as a customer data analysis platform.

However, as is the case with most modern advanced tools, adding new features can easily lead to situations where the user has to work harder than they should, or where key features of office 365 database the tool becomes difficult to use.

Up until now it has been important to add functions that were lacking, but from now on we need to start working on how to make it as easy to use as possible without hassle.



In fact, the segment function, which is a core feature of FANSHIP, experienced slow usage rates when it was first released.

Although using it can result in very effective marketing, it tends to get stuck at the initial setup and goal setting stage, and time passes without any real results being seen.

So we strengthened our customer success team and started an onboarding program, and as our customers began to see the benefits, usage rates gradually increased.

I think we need to look towards automation in the future.




Presentation at Japan IT Week Kansai in January this year
Where can we be number one? Creating a world where even small companies can be data-driven
If we make providing a customer data analysis platform our goal, we won't be number one, so we go back to the question of what we should aim for.When we thought about it within the big picture, the answer we came up with was to build a business model that boasts an overwhelming number of adoptions, but does not make money from usage fees.

Once we have made FANSHIP something that anyone can use with a certain amount of study, we would like to provide advanced analysis functions free of charge.

We need to create a detailed revenue plan before we can officially decide on this as a company, but we are imagining a model where we monetize elsewhere by utilizing the data obtained through free provision and trade-offs.