Thanks! Some competitor did pretty well, the total addressable market should be huge enough, for example Intuit Mint claims to have 10M (free) users, some funded companies benefits a lot from its shutdown.
There are some big parts identified for this case, and because it is dependency of 3rd party service, we can not do much about it.
But more importantly, I think it is the product itself, the market is probably does not appreciate that much of "customization / personalization" as I thought, in other words, we are probably haven't figured out the best path to get the ideal users yet.
In the other side, free users do not have this issue. We do have free tier which counts for 1/3 of all active users.
How do you tell product market fit? we have about ~1K paid users, people constantly send positive praises, but also many people churned away.
I doubt if "bootstrap" is the right way for this type of product/market.
The famous PMF survey (how do you feel if you can no longer use this), %50.8 responds with "very disappointed". And I deeply know this product is pretty unique offering in "finance tracking" market.
But the MRR stays in this level for 6 months now. I feel I do not have ideas to break it through.
Excel/Spreadsheet are best invented software ever.
However, the other side of this double-edge sword is its fragility, when data or logic grow in complexity, it raises more errors than it should. That's when a niche product gets its chance to chime in.
Have you heard of Fina Money? SpreadSheet works, but Fina tries to make it easier to analyze and visualize your finance data from sheets + live banks. It solves the problems you mentioned.
Trusting is a problem, to be honest, mostly for fun. If you want to trustable source, feel free to copy text paragraph and let it parse for you, there is another mode for that.
So it's a pretty simple wrapper of LLM model in use (currently gpt-4o), it does not add much technical stuff in it.
It does not use database for any "random search", but yes, columns.ai is a data analytics tool that allows you to connect supported live data sources like Google Spreadsheet, Airtable, Notion Database to create visual stories.
The analytics engine is home built (https://github.com/varchar-io/nebula) but it is not a database. And I don't use LLM agents, just build logic how to purify data returned by LLM, and fit them into an optimized visualization.
Unless it's very "public common", otherwise, the numbers can be used for trustworthy work. In general, I think this is just for "fun play" most of the time.