I need feedback from B2B SaaS experts on the problem statement that I have picked
I would like to know if the below is a real pain point from people that have worked in the B2B SaaS Industry
Situation:
Clients of large SaaS companies need custom data for internal analysis. This data is not available via SaaS companies dashboard as they are custom in nature. The client raises tickets to SaaS company.
Pain Points:
It takes 3-4 days if not more to close the tickets
Data analyst bandwidth is choked with multiple internal & external projects
Customer success fire fighting disgruntled customers
Solution:
thereliable.ai allows you to create configurable expirable links using which your client can fetch the data that they want using natural language. All they need to do is open the link, ask their question in natural language, and download the data. All this can be done in less than 30 seconds.
The problem is a good problem to solve but the real challenge would to to find those exact B2B customers which could eventually take several months. I am in Micro SaaS ecosystem for sometime. I am not sure if this is your first product. If so, I would suggest you to pick a simpler one.
the idea seems good but getting the b2b customer is going to be a challenging task for this problem.
I think you need to drill down more and be less generic
If you talk about really big SaaS they would have a custom reporting/query module (possibly in higher tier packages)
Small - mid ones might not
Custom per customer reporting from a SaaS company would be only for the top 1% of customers
I think you need to be more specific about the SaaS company you are describing and it's clients
The reason custom reports for client usually take a while is because the either the data is conveluted, not pre process to what is requested yet or basically is a revenue generator honestly and than the human factor might be pricing and negotiating like then you buy targeted/research lists
There are/were many interfaces trying so simplify queries for non tech savvy customers and sure AI might help a bit, but usually the gaps are many, between biz terminology that isn't the data terminology, the technical flow, and basically the user's not wanting to be tech people or learn too much to do that part which isn't theirs, some learn the tools, IDK who you'd be targeting...
I agree with this. It's great to keep the code generalized so that you can move into other verticals rapidly, but you should have a narrow initial target customer profile that you can really speak to and solve problems for.
Thanks for the reply. I am thinking of solving this for big SaaS companies in the transportation sector. The point about convoluted data is interesting and I think my tool may not be able to solve for it. I need to drill down deeper into why it takes a lot of time. The gap between biz terminology to data terminology is solvable though.
I think the terminology sounds simple on the surface as a dictionary, but than you find the same exact acronyms and even words just don't mean the same between parts of the org... I don't say it's not solvable but it's not a technical problem, it's a soft skills problem, maybe a customer machine learning can solve that but judging by gpt4 as a current best generic option, it's gonna be pretty bad at it, at least to create a generic product out of it
IDK the transportation sector, but do consider the time to solve also for its sales value, sometimes there is a reverse incentive to solve something and as a technical person it's an easy trap to fall into