Track crowdfunding projects and see how much they'll raise

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Hi All, BackerKit co-founder here. we also have a launch announcement here with a bit more detail: The TL;DR is that we worked with some fine folks at Insight Data Science to develop a cool little machine algorthim that helps to predict funding levels of projects and all shapes and sizes. It is based on past project history, so all of the trajectories are based off of funding levels experienced by other projects.
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@maxwellsalz very interesting if your projections are taking into account some econometric regression and projection techniques. What I like in these analysis is that you can determine when the campaign received large amount of pledges and search their project in blogs and media. It might be helpful to track which marketing/media activity worked especially well for them and which didn't. Good to have Indiegogo as well. Great job!
BackerKit has been already working with all the top crowdfunded projects for years. Now they've released a tracking database that lets you see all top trending crowdfunding projects, and also see predictions on how much these projects will actually raise. Crowdfunding continues to grow at a super fast rate, so it just makes sense that we should be able to see better data on every project out there, and also use that to find new products to post on Product Hunt. :-)
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Very useful tool! Thanks, BackerKit :) 1: looked up my own project 2: looked up competitor's campaigns 3: find competitors I don't know about yet
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This adds incredible value to the crowd funding space. How accurate has your machine learning algo been this far?
@dappermarketer Hi Chris, things are getting tighter as we get more data, but we are finding that once we have 5-6 days of data we are about 80% accurate within a few standard deviations. Right now we are showing an overly conservative spread. What is cool about BackerTracker is that it is unsupervised, meaning that data just needs to be added without any massaging or updating of the underlying model. One thing we are considering weighing more is category. An interesting aspect of our data set is since the entire corpus for Crowdfunding isn't huge (maybe only 100s of thousands of projects, all time, plus we don't have **everything**); that means that if you **only** looked at the projects in the same/similar categories, you might be cutting down your sample size to where it might not help the projections right now. Hypothetically, if projects in a certain category have similar funding dynamics, the similarity would be exposed naturally. With that being said, having enough projects in a category could bear fruit.
@dappermarketer with that being said what we built certainly is not even close to being perfect, but gives us a great base to build, iterate, and experiment with in the future. Lots of great ideas out there worth playing with!
@maxwellsalz that's quite impressive this early on. Well done BackerKit team!
Basically just reimplemented. Not very interesting.
@myles_oneill kicktraq is way off all the time on trends. I'm excited to see the accuracy of this one.
@markpecota you hit the nail on the head my friend
@myles_oneill More tools, the merrier.