Re:Weebly's SnapAds: Survival Of The Fittest Meets Madison A...
by greg on Tuesday November 25, 2008 @11:15AM
(#376467)
I wrote the software behind SnapAds. Before that I wrote an optimizer service for web pages that operates on HTML, CSS or Javascript. Check it out at http://demo.genetify.com .
Let me know if there is any interest -- I'd like to open-source the project.
Re:Weebly's SnapAds: Survival Of The Fittest Meets Madison A...
by jbyers on Tuesday November 25, 2008 @03:18PM
(#376731)
That's awesome. Definitely interested in an open-source version. Let me know if I can help, contact details in my profile.
Re:Weebly's SnapAds: Survival Of The Fittest Meets Madison A...
by aneesh on Tuesday November 25, 2008 @02:47PM
(#376688)
Good idea. Actually, I think a platform to make A/B testing super-simple for developers (like us!) could be a business in itself.
Re:Weebly's SnapAds: Survival Of The Fittest Meets Madison A...
by mtw on Tuesday November 25, 2008 @10:22AM
(#376419)
landing pages for user signups,
homepages for media websites (nytimes and other big blogs),
email campaigns,
product promotions and offers or even defining pricing if you do a saas company
Re:Weebly's SnapAds: Survival Of The Fittest Meets Madison A...
by 8en on Tuesday November 25, 2008 @11:39AM
(#376491)
For landing pages, I'd recommend Google Website Optimizer. It's a pretty sophisticated multivariate testing tool. https://www.google.com/analytics/siteopt/splash?hl=en
Re:Weebly's SnapAds: Survival Of The Fittest Meets Madison A...
by dangoldin on Wednesday November 26, 2008 @10:01AM
(#377655)
The guy who wrote Super Crunchers did the same thing. Drank his own Kool Aid.
Re:Weebly's SnapAds: Survival Of The Fittest Meets Madison A...
by drusenko on Tuesday November 25, 2008 @09:27PM
(#377165)
as a point of clarification, the system greg's built goes much further than simple a/b testing. there are quite a few complications with implementing a genetic algorithm in the real world of constantly shifting preferences.
once done right, it can efficiently optimize millions of permutations with millions of ad impressions (<2000 clicks). more permutations means more chance for improvement, and this just isn't possible with a simple a/b testing solution.
Headlines? The images that accompany news stories?