Ask HN: two developers with no marketing skills built an app, then what?
Like everybody else did, we posted a short "Show HN" here on Hacker News, we submitted a link to Reddit, we got a few thousand visits & close to ~100 signups, we were pretty excited initially. Then, a couple days later, once the traffic dried, we're now left in a zombie state of less than 10 visits a day and no new signup any more.
Our target users are science major undergrad/graduate students, postdocs, professors, and researchers in general. But the question is, how do we reach them, how can we let them know that there is this cool app they should definitely check out, what shall we do besides the "Show HN" and submitting to Reddit?
We're just two "average Joe" junior developers, and we have absolutely no marketing experience at all. So, we're here to ask HN: what should we do then? Would appreciate any constructive ideas/advice/suggestions/criticisms. Would love to hear what you have done to market/promote your side projects or startups, what works, what does not work, etc.
12 comments
[ 3.7 ms ] story [ 55.1 ms ] threadHave you thought about setting up some type of system to automatically create profiles for people? You could scan in the front page of a printed thesis (where it lists the advisers), extract the names, and then add pages if they don't exist for those professors and PHD people. Then, when a PHD student googled themselves, the phdtree link would show up.
Or a big "claim my profile" link?
Maybe the colleges will use it in marketing material or a blog post. Free publicity for everyone involved!
Then, whomever is reading the college's blog because they care about that kind of stuff will be compelled to claim their profile.
I'm not an academic, but wouldn't a better strategy be to do co-authorship analysis on papers to generate similar information. That is you could say researchers who co-wrote their initial papers with more senior researcher X (normally indicating a supervisor or mentor relationship) at lab Y tend to end up at Z and have an average research impact score of R.
That way you could get all the data from analyzing public citation databases and avoid the chicken-and-egg problem with trying to crowdsource the data, and go directly to solving the main problem of comparing potential PhD supervisors based on their trackrecord.
http://www.gabrielweinberg.com/blog/2010/04/in-the-pursuit-o...