Anmol - you're building an information business. And at scale, IMHO, they're fabulous. Health information seems like a massive market, and this seems like unique data. (Think about financial consumers who care about health data in addition to the pharmas.) I'll assume your app scales so that you get critical mass of input, but once you have that in your sights, here's how we constructed our information business.
In my experience, the best information businesses are founded on a core of primary research - data that you find/generate that no one else has. Once you build that database, you build the products. You might be surprised, but here's what many information products look like - I'm a fan of doing it in this order:
1. A big honking CSV file of the primary data. For customers that have their own models, which your early adopters will likely have. Ours did.
2. A CSV file of derivative analytics (the output of your prediction tools perhaps?). For customers who want your algorithmic take on the underlying data.
3. Reports (manually written). People buy your analysis of the data. We found a majority of the potential market doesn't want Tools or data files (even if they're Wall Street "quants"). They just want answers - and by virtue of having the data, you're an instant expert. Reports have the nice benefit of being A) tangible B) easy to consume and C) subscribe-able (repeat revenue!) They have a bonus of being delicious chum for the media sharks.
4. Reports (automated, for scale). Subscribers get the latest insights each week, month, etc. Best not to automate until you see which of #3 are most popular.
5. Now come the technology Tools. #3 and #4 above will be excellent test beds for your prediction tools. Doing it in this order, you won't have to build any front end applications until you understand what predictions people pay for. One way to build a tools-based product line is to give the tech away for free and have the customer subscribe to the latest data.
You might also find that a great consumer-facing website is powerful for the information business. We don't have those skills in our company, but have found that when we pull it off even a little, institutional buyers begin as personal, individual consumers. A great consumer facing site/app is a perfect way to reach them.
"Stealth Mode" when used properly, is an effective marketing tool that leads to a big launch event. We're building, working with initial customers, and when we launch it'll be huge!
"Stealth Mode" used ignorantly means, "we're unwilling to discuss our idea with anyone for fear they'll steal it."
Rand - It sure seems like you're recruiting sophisticated application engineers, you're not recruiting SEO engineers. That is, this is a recruiting problem (yours) not a perception problem (theirs).
Focus your headline on the sexy work you're recruiting the engineers for, not the market your customers are in. Why mention SEO at all in your recruiting?
Oo turn it on it's head and address the fear in your recruiting efforts. Like, "how can a gig as awesome as this possibly be found in the slimy, shady underworld of search engine optimization? mwahaha."
Maybe I'm biased because I'm an SEOmoz client, but I'd imagine that once they get past the initial hurdle that your firm doesn't fit a preconception about SEO anyway. So get em over that initial bump.
Sure, you can have a "successful" business that grosses $250k / year. If you can do that with no employees and go surf every day, there will be a lot of jealous surfers out there.
But if you're looking to bootstrap a startup into a sustainable enterprise that "solves the money problem" (as Paul puts it), there are plenty of fabulous examples with $2million, $10mil, $50mil in revenue. Study them.
I'd suggest you set your sites higher than $1k/month. $10k/month is a start. $100k/month is a business that pays you and your employees. And there are zillions of them out there to learn from. My blog isn't about the internals of our business, but I'm happy to tell any bootstrapper who asks.
In my experience, the best information businesses are founded on a core of primary research - data that you find/generate that no one else has. Once you build that database, you build the products. You might be surprised, but here's what many information products look like - I'm a fan of doing it in this order:
1. A big honking CSV file of the primary data. For customers that have their own models, which your early adopters will likely have. Ours did.
2. A CSV file of derivative analytics (the output of your prediction tools perhaps?). For customers who want your algorithmic take on the underlying data.
3. Reports (manually written). People buy your analysis of the data. We found a majority of the potential market doesn't want Tools or data files (even if they're Wall Street "quants"). They just want answers - and by virtue of having the data, you're an instant expert. Reports have the nice benefit of being A) tangible B) easy to consume and C) subscribe-able (repeat revenue!) They have a bonus of being delicious chum for the media sharks.
4. Reports (automated, for scale). Subscribers get the latest insights each week, month, etc. Best not to automate until you see which of #3 are most popular.
5. Now come the technology Tools. #3 and #4 above will be excellent test beds for your prediction tools. Doing it in this order, you won't have to build any front end applications until you understand what predictions people pay for. One way to build a tools-based product line is to give the tech away for free and have the customer subscribe to the latest data.
You might also find that a great consumer-facing website is powerful for the information business. We don't have those skills in our company, but have found that when we pull it off even a little, institutional buyers begin as personal, individual consumers. A great consumer facing site/app is a perfect way to reach them.
rock on.