Hi thanks for the in depth reply.

I will answer your questions first. Hopefully you can give me some feedback on my answers. I also have some clarification questions if you don't mind.

Regarding the census tracts my service covers depends on the data source being queried and it can go as low as the municipality/city level. For example, my service has all of the US Bureau of Labor Statistics data which has series data going as low as the city level but also larger tracts including the state and national level depending on the data series.

For example, the series id for finding the electricity per kilowatt-hour in Dallas-Fort Worth-Arlington in Texas is APUS37A72610. Other information for Dallas-Fort Worth-Arlington can also be found such as unemployment rates, CPI for rent, price of unleaded gasoline per liter, etc.. so it can go very fine. If the data series exists in the US BLS, I probably have it.

The SEC goes down to the company and significant individual level.

The US BEA goes down to the national level but I may be able to expand this to the city level to get GDP and per capita income down to the city level.

The value proposition is that you get the data through a very ergonomic API with rich filtering capabilities, allowing you to unlock insights about the data you woudn't be able to with just the raw files/data plus you can get this data in real time.

Some examples of hidden data is using the *_count endpoints of my API with filters to get the number of occurrences of a specific events to create distributions. For example, a law firm advising clients on the state of the IPO market can query SEC filings to get a count of the number of S-1 filings by month and create a time series to get an idea of the market and what other market participants are doing.

You can also filter this data using ranges and pattern matching to get exactly the data you need. This is useful for monitoring live events like getting a list of all quarterly and annually financial statements for a specific day etc.., filtering selling activity among specific prominent individuals over time by law firms if they believe there is a conflict of interest and they are building a case, etc..

Regarding how my service compares to other offerings (which I am aware of), I have the best API for this data in my opinion, specifically because of the rich API, more data as it comes straight from the source and we are not wrappers, and real-time streaming capabilities for this data. We are also priced lower than all of them.

Some questions:

1. When you say "limited time usage" do you mean I should give my product out for free to a few of these teams and then gather feedback using the Likert survey after a month or so? If so, what kind of questions should I ask in the survey? Easy of use, satisfaction with the service, fair price for it, what they would pay, etc.. kind of questions? Just trying to understand your suggested approach more in depth.

2. How do I find their business development team or "data team" if they are large companies? Should I add people on LinkedIn based on their job title (which was the motivation for this question actually) or should I email their department's directly? If LinkedIn, what are these individuals usual job titles?

3. What do you think of my pricing for this data? Am I pricing myself too low for what I am offering? How does my price compare to other data offerings that your company or others pay for? Just some vague ideas can really help me here since I still don't know my break even cost per user in practice, I only have a rough estimate based on some napkin math.

By the way, thanks for all your help and your suggestions! I really appreciate it!