Ask HN: Startup idea feedback – user-friendly AutoDataScience
ML and more broadly data science are very useful, but even some of the most recent "easy" data science tools (e.g. Google AutoML tables) have too high of a learning curve to be useful to the average consumer.
Normally if you were learning a new tool, you might learn through a combination of study, and trial and error. However, many people don't have a lot of time to sit down and learn something complex in this manner. (They need a bit of an extra push to minimize their error/guide them toward reasonable use cases.) The result is something like this:
1 - get excited to try something easy and get new value out of their data
2 - get frustrated because the tool is not easy enough, or they don't know what questions are answerable with the available algorithms
3 - search the internet for guidance on what the algorithms do, get overwhelmed
4 - abandon tool
Solution:
1 - send us your data (probably a spreadsheet/CSV/Excel file)
2 - we analyze the data, and send you a list of questions that we can answer/insights that we can derive
3 - you select which of the questions you want answered
4 - we run our analyses and send you the results, including an explanation of the algorithms that were used to derive the results
The key here is that the "learning" takes place after value is delivered to the user. Even though a tool may allow you to do things with the click of a button, the hidden complexity still presents a learning curve to the user.
Footnotes:
- I'm not claiming to have a large amount of data to back this up, hence why I said this is a "hypothesis". I'm offering the idea up for feedback and am interested in hearing what people say!
- This certainly does not apply to people who are used to self-directed learning and enjoy a healthy challenge